Optimum cereal combine harvester operation by means of automatic machine and threshing speed control

: LANDBOUWCATALOGUS

0000 0086 5713 m Promotoren: ir. A. Moens hoogleraar in de landbouwkundige aspecten van de landbouwwerktuigkunde alsmede de landbouwbedrijfsmechanisatie ir. O. H. Bosgra buitengewoon hoogleraar in de meet-, regel- en systeemtechnie k /^o11ö\,%t

W. Huisman

Optimum cereal combine harvester operation by means of automatic machine and threshing speed control

Proefschrift ter verkrijging van de graad van doctor in de landbouwwetenschappen, op gezagva n de rector magnificus, dr. C. C. Oosterlee, hoogleraar in de veeteeltwelenschap, in het openbaar te verdedigen op woensdag 30 november 1983 des namiddags te vier uur in de aula van de Landbouwhogeschool te Wageningen. Abstract

Huisman,W . (1983)Optimu m cereal combine harvester operation by means of automatic machine and threshing speed control.Doctora l thesis, Agricultural University,Wageningen . (xx+ 293p. , 156 figs,4 6 tables, 132 refs, app.,Eng . and Dutch summaries)

The method bywhic h automation of agricultural machinery can be developed isillustrate d in the case of cereal combineharvesting . The controlled variables are machine forward speed and threshing cylinder peripheral speed. Four control systems have been developed that optimise these speeds on thebasi s of harvest costsminimisation ,whic h includes variable and fixed costs of the machine and those of machine- and timeliness losses. The evaluated systems make use of avaryin g number of input process variables and control the machine speed exclusively,o r both machine speed and threshing speed. The financial benefits from these control systems were calculated by means of a computer simulation. The research required in developing the models and control systems is discussed in detail.Th e simulation results demonstrate that control of low-frequency variations in croppropertie s brings some slightbenefi t and indicate that timeliness losses are of great importance to optimisation.

FREE DESCRIPTORS: cereal harvest optimisation, combine harvester,auto ­ matic control,machine speed control,threshin g speed control,simulation .

This thesis ispublishe d by the Department ofAgricultura l Engineering,Agricultura l University Mansholtlaan 12,670 8P A Wageningen The Netherlands Stellingen

1.Bi jhe t ontwikkelen van geautomatiseerde systemen voor landbouwmachines dientme n zich te laten leiden door een duidelijk en weloverwogen opti­ malisatie-criterium. Bovendien dientme n in een vroeg stadium de tever ­ wachten voordelen kwalitatief en kwantitatief in detail uit te werken om tijdig tekunne nbesluite n over voortzetting, stopzetting of ombuiging vanhe t ontwikkelingsonderzoek.

Ditproefschrift ,alsmed eM.B .McGechan ,CA . Glasbey. J.Agric .Engn .Res .6 (1982),p .537-552 .

2. Het feit dat gemiddeld per maaidorser in Nederland jaarlijks slechts een geringe oppervlakte wordtbewerkt,ka n slechts worden verklaard door de lage machinekosten enhe tverlange n van deboe r om het risico van hoge tijdigheidsverliezen tebeperken .D e lagemachinekoste n zijn een gevolg van de lange economische levensduur vanmaaidorsers .

R.K.Oving ,E .va nEideren ,R.L .d eVries . IMAGpublikati e 143,Wageninge n1980 .

3.D e graanverliesmeetsystemen die thans in dehande l zijn,biede n alleen een economisch voordeel indien de gebruiker zich rekenschap heeft gegeven van het Verliesniveau dathi jwens t aan tehouden . Bovendien moet de gebruiker hetmeetsystee m zeer frequentijken .

Ditproefschrift .

4.He t ontwikkelen van geautomatiseerde systemen voor landbouwmachines vereist een multidisciplinaire aanpak.Voora l een intensieve samenwerking tussen onderzoekers uit devakgebiede n van de Landbouwtechniek en de Meet-,Regel -e n Systeemtechniek iswenselijk . Ditproefschrif t

•-.rJE K 5.Automatiserin g bij maaidorsers levertarbeidsplaatse n op. Ditproefschrift .

6. Bijoptimalisati e van het verschil tussen opbrengsten en kosten van een landbouwproductiesysteem, zoalsbijvoorbeel d de bietsuikerproductie, moeten deproductiemethode n ophe t landbouwbedrijfe n in de fabriek alsee n samenhangend systeemworde nbeschouwd . Indienpremie s en boetes als sturingsmechanisme worden toegepastmoete n deze ook op de korte termijnworde n aangepast aan zichwijzigend e omstandigheden.

7.Bi jd e vergelijking van de diversemethode n van groenvoederwinning, worden de aspectenkwalitei te nverlie s ten onrechte minder nauwkeurig gekwantificeerd dan de machinekosten.

8. Indien adviezen en voorschriften omtrent energiebesparing inwoon - en werkomgeving en inopenbar e voorzieningen onvoldoende effect sorteren, dienen demogelijkhede n van automatisering daartoeme t spoed te worden onderzocht.

9. In de discussie over de invoering vanwerktijdverkortin g moeten argu­ menten diebetrekkin g hebben op inmateriëlewaarde n een zwaarder ge­ wichtkrijge n dan ze thansveela lhebben . Bijd eeconomisch e argumenten dientme nmee r aandacht te geven aand e flexibiliteit van dearbeids ­ markt en de grotere arbeidsprestatie.

10. Macro-economisch onderzoek moet zichminde r richten op de economie van de groei en meer op een economie waarin deverdelin g van welvaart centraal staat.

W. Huisman Optimum cereal combine harvester operation by means of automatic machine and threshing speed control Wageningen, 19septembe r 1983 Vie steeds op de wind let, zal niet zaaien; en wie steeds naar de wolken ziet, zal niet maaien.

Prediker 11:4 Voorwoord

In ditproefschrif t isee nbelangrij k deel van de resultaten verwerkt van ongeveer 15 jaaronderzoe k aanmaaidorsers ,uitgevoer d inhe t kader vanhe t onderzoekprogramma van de vakgroep Landbouwtechniek van de Landbouwhogeschool. In dieperiod e hebbenvele n eenbijdrag e geleverd aan ditonderzoek , die iko p deze plaats daarvoor gaarne mijn dank wil betuigen.

In de eersteplaat s wil ikmij npromotore n bedanken. Professor Moens, joube n ik vooral dankbaar voor de ruime gelegenheid die jem eheb t geboden ditonderzoe k uit tevoere n en voor de stimulans omhe tme t eenproefschrif t af te ronden. Je opmerkingen betreffende inhoud en tekste n denadru k die je legde op de algemene toepasbaarheid van het onderzoek, zijn ergbelangrij k voor mijgeweest . Professor Bosgra,jo uwi l ik vooralbedanke n voord e intensievebege ­ leiding metbetrekkin g totd e aanpak van het onderzoek en de vormgeving. Je onvermoeibare inzetbi jhe toverdrage n van de nodige kennis uit jouw vakgebiedwa s een onmisbare steun. Hetheef t dekwalitei t van ditproef ­ schrift zeer verbeterd.

Demedewerker s van de vakgroep Landbouwtechniek waren degenen die dit onderzoek uiteindelijk hebben mogelijk gemaakt. Oscar Bergman enJa n van Loo,julli e enthousiasme en steun waren on­ ontbeerlijk. Jullie hebben vooral deperiod e vanhe t veldonderzoek samen metLee n de Boer van de ir.A.P .Minderhoudhoeve ,to t een fijne tijdge ­ maakt. Egbert van derWal ,Ee f van Donselaar en Piet Rijpma, jullie waren bij de assistentie inhe t veld zeerbetrouwbaa r en onvermoeibaar. Geurt van de Scheur,Wille m van Brakel en Jordan Charitoglou, jullie steun vanuit dewerkplaat s was debasi s van veld- en laboratoriumonder­ zoek. Voor de ontwerpadviezen voor apparatuur ben ikprofesso r Quast, Jaap Heyninge n Henk de Vries zeer dankbaar. Jan Meuleman, jou dank ik vooral voorhe t overnemen van de taken die ik liet liggen tijdens het schrijven van ditproefschrift . Ook de andere collega's die taken overnamen ben ik daarvoor dankbaar. Guus Tergast,Kare n den Outer enEll y Faber, jullie wil ik vooral bedanken voor deprettig e en correcte wijzewaaro p jullie mijn werk ondersteunen.

Ind e langeperiod e van onderzoek hebben 44 doctoraal studenten en een 10-talpraktijkstudente n aan onderwerpen gewerkt die samenhingen met ditonderzoek . Ikhe b metplezie r met allen samengewerkt en ben dankbaar voorhu n inzet. De student-assistenten Leo van Geel, Henk van Dongen,Fran s Reumkens en Bertva n 'tOoste r ben ik dankbaar voorhe tmake n van enhe t werken methe t simulatieprogramma. Jullie hebben mij veelwer k uithande n geno­ men. Vooral Bertdan k ik voor zijn steun in de avonden en nachten achter de terminal.

Van demedewerker s van de sectie Meet-,regel -e n systeemtechniek van de vakgroep Natuur- enWeerkund e wil ik metnam e bedanken Alexander Udink ten Cate en tevens zijn oud collega's Jimmy Lengkeek,professo r van Dixhoorn en Gerritva n Zee.Voo r de steunbi j computerwerk en signaalanalyse ben ik tevens Dimitri van denAkke r enWille m Driessen dank verschuldigd.

Ditonderzoe k zounie t mogelijk geweest zijn zonder debijdrag e van diverse instellingen enbedrijve n zoals Fa. Sperry New Holland Fa. Van Driel &va n Dorsten Rijksdienst voor de IJsselmeerpolders Instituutvoo r Mechanisatie,Arbei d en Gebouwen Technische en Fysische Dienst voor de Landbouw De vakgroepen Informatica,Wiskunde ,Landbouwplantenteel t en grasland- kunde,he t rekencentrum van de Landbouwhogeschool en de ir.A.P .Minder - houdhoeve. Tenslotte wil ik voor de vormgeving van ditproefschrif t gaarne bedanken: Eef van Donselaar voor de figuren;mr . Smith Hardy voor de correctie vanhe t Engels;Han s Sytsma voor vertaalwerk; Karen den Outer,Cisk a den Herder en mevrouw L.J. Müller voorhe t typen van de diverse concep­ ten en Jakke van der Sluisvoo r het typen en afwerken van de gedrukte versie.

Lieve Jannie,zonde r jouw steunwa s ditwer k niet tot stand gekomen; lieve Geertje enJa nWillem , zonder jullie geduld washe t nietklaar - gekomen; lieve vader en moeder,zonde r jullie opvoedingwa s ik er niet aanbegonnen .

Wageningen, 29 augustus 1983 Contents

text appendix Listo f symbols

1. INTRODUCTION 1 1.1. General 1 199 1.2. Literature 2 205 1.3.Ai m of the study 5 1.4.Metho d of the study 6 1.4.1.Optimisatio n criterion 6 1.4.2.Th e reason for simulation 13 1.4.3. Formulation of the optimisation problem 14

2. SYSTEM MODELS 21 2.1. Model approach 21 2.1.1. Introduction 21 2.1.2. General aspects 22 2.1.3.Metho d used in this study 26 2.2. Costmode l 26 2.2.1. Variable costsproportiona l to theharveste d area 27 215 2.2.2.Variabl e costsproportiona l to theworkin g time 27 215 2.2.3. Fixed costs 28 216 2.2.4. Costs ofmachin e losses 29 216 2.2.5.Cost s of the extrawea r of the threshing cylinder 30 217 drive 2.2.6. Costs of the timeliness losses 30 217 2.3. Process model 31 2.3.1.Heade r and conveyer 36 220 2.3.2. Threshing cylinder 42 222 2.3.3. Rotary separator 42 2.3.4. Straw walkers 44 23 2 2.3.5. Sieve loss 48 2.4. Transmission models 50 2.4.1. Transmission inmachin e A 50 2.4.2.Transmissio n inmachin e B 52 2.4.3.Threshin g cylinder varidrive 54 242 3.MEASURIN GSYSTEM S 62 3.1.Fee drat emeasuremen tdevice s 62 3.1.1.Torqu eo fth eauge ra sfee drat esenso r 65 245 3.1.2.Stra welevato rdisplacemen t 69 245 3.1.3.Auge rtorque-elevato rdisplacemen trelationshi p 72 245 3.2.Measuremen to fgrai nfee drat e 74 3.3.Measuremen to fwalke rlos s 75 3.3.1.Grain-los smonito r 76 3.3.2.Principl eo fa nimprove dlos smonito rsyste m 79 251 81 3.4.Measuremen to fthreshin gseparatio nefficienc y 82 3.5.Measuremen to fspeed s

4.DISTURBANCE S 83 4.1.Introductio n 83 4.2.Disturbance si nfee drat e 84 253 4.3.Disturbance si nthreshin gseparatio nefficienc y 91 4.4.Disturbance si nrotary-separato refficienc y 93 4.5.Disturbance si nwalke rseparatio nefficienc y 94 4.6.Variatio ni nwalke rlos s 96 263 4.7.Conclusion s 101

5.CONTRO LSYSTEM S 103 5.1.Introductio n 103 5.1.1.Genera l 103 5.1.2.Model sfo rcontro lsyste mdesig n 1°4 5.2.Cos tminimisatio n 1°8 5.2.1.Optimu mmachin espee dcalculatio nfo rsyste m2 108 5.2.2.Optimu mmachin espee dcalculatio nfo rsyste m 1 HO 5.2.3.Optimu mthreshin gspee dcalculatio n forsyste m3 HI 5.2.4.Metho dfo rcalculatio no fth eoptimu mthreshin g cylinderspee dfo rsyste m4 114 5.3.Spee dcontro l 116 5.3.1.Machin espee dcontro l 116 5.3.2.Threshin gspee dcontro l 118 5.4.Contro lsystem s 120 5.4.1.Los scontro lsyste m 120 5.4.2.Loss-fee drat econtro lsyste m 123 5.4.3.Loss-fee drat ethreshin gspee dcontro lsyste m 125 5.4.4.Loss-fee drate-threshin gseparatio ncontro lsyste m 126 5.5 Discussion 129 6.SIMULATION S 133 6.1.Metho d 133 6.1.1.Introductio n 133 6.1.2.Simulatio nprogra m CSMP 133 266 6.1.3.Simulatio ninpu t 135 6.1.4.Simulatio noutpu t 139 6.2.Simulatio nmode l 140 6.2.1.Threshin gan dseparatio n 140 6.2.2.Machin espee d 147 6.2.3.Threshin gspee d 148 6.2.4.Contro lsystem s 150 6.3.Simulatio nresult san ddiscussio n 163 6.3.1.Introductio n 163 6.3.2.Manua lcontro l 163 6.3.3.Automati ccontro l 167 6.4.Conclusion sfro msimulation s 189 193 7.FINA LCONCLUSION SAN DRECOMMENDATION S 193

APPENDIX 199

SUMMARY 273

SAMENVATTING 279

REFERENCES 287 List of symbols

a regression coefficient; constant inloss-to-fee d rate relationship A ratioo fpea k valueso feve n straw feed (TE) andirre ­ gular straw feed (TI) l AA harvested areape rcombin eharveste rpe ryea r ha'yr -l AAN AAi nnorma lo rmanuall y controlled situation ha*yr ACAV averageo fth eabsolut e valueso fmachin e forward m's speed accelerations AFC annual fixed machine costs fl*yr "1 AFS straw feed ratepe rm widt ho fthreshin g cylinder kg-s ••nf- (straw= materia l other than grain,m.o.g .dr ymatter ) AFST AFSa tth ethreshin g cylinder entrance kg»s AFSW AFSa tth estra wwalke r entrance kg's AP period overwhic hmeasure d signalsar eaverage d s b regression coefficients;constan ti nloss-to-fee d rate relationship BETA threshing coefficient BL breakage lossi nth egrai n kg*s BLF fractiono fbreakag e loss c constanti nvariou s expressions C correction factori nth ecalculatio n of MFC CD masso fcro p (=straw+grain ) inth efiel d kg-m CL lengtho fcutte rba r m _ CLO costso fgrai n losses arising inth eproces s inth e fl'ha l machine CM totalmachin e costs (MVC+HVC+MFC) f1'ha" CONA concave tothreshin g cylinder adjustment front/rear mm/mm CRL level coefficienti nrotar y separation equation CRS slope coefficienti nrotar y separation equation kg" »•S CS concave separation (grain) kg CTI costso ftimelines s losses fl« ha-1 CM coefficiento fvariatio n amounto fgrai n inth estra wa tth efron to fwalker s kg*sl amounto fgrai n inth estra wa tth een do fwalker s kg*s1 amounto fgrai ni nth estra wa ta give nplac eo n kg"s walkers GY grain yield kg-ha"1

HVC machinevariabl e costsproportiona l toworkin g time fl-ha-1

J momento finerti ao fmoto r m kg*m J momento finerti ao fthreshin g cylinder kg"m 2 k constanti nvariou s expressions Ki,Kz constanti noptimu m speed calculations

L lengtho fV-bel to fthreshin g cylinder varidrive LA concave length factor LI lengtho fthreshin g cylinder m LW functional length of walkers m

MCCS multiple correlation coefficient MCS strawmoistur e content MCG grainmoistur e content MFC fixed costsmachin e fl-ha ML totalgrai n losses arisingi nmachin eproces s kg*s MVC machine variable costsproportiona l toharveste d area fl-ha-1 n numbero ftrial s NE time during combineharvestin g that combine isno t h'ha cuttingan dthreshin g NU densification factori nthreshin g model NV purchase priceo fcombin eharveste r fl

OMOUT threshing cylinder angular velocity rad*s OMWT setvalu e threshing cylinder speed control rad's p probability function P gaini nintegratio n actiono fmachin e speed control mm'm 's c -j P gearbo xgai n m'rad P hydraulic drive gaino fmachin eB rad's 'mm P power generatedb ycombin e engine W m P powerneede d forthreshin g W tn -i_i variator gaino fmachin eA rad«s «mm V grainbreakag e lossi npercentag eo fgrai n feedrat e % PBL gaini nintegratio n actiono fthreshin g speed control rad M •m PCTC PF gaini nintegratio n actiono fauge r torque feedback mm'mV 1#s control system PT harvested area ha-h"1 r correlation coefficient R- working radiuso fpulle y inthreshin g cylinder vari- m drivea tengin e side R. working radiuso fpulle yi nthreshin g cylinder vari- m drivea tthreshin g cylinder side RAH relativeai rhumidit y RPS charge coefficienti nthreshin gmode l RSE rotary separator efficiency RT transmission ratioo fthreshin g cylinder varidrive RV residual valueo fcombin eharveste rB fl s complexvariabl eo fth eLaplac e transform s_1 S grain separationa tgive nplac ea twalker s kg«s '1. m SD strawdensit y inth efiel d kg'm "2 SDAV average straw densityo ftes tru n kg*m •2 SDM straw density calculatedb ymeasure d auger torque kg-m "2 andmachin e speed kg*s "I SL sieve loss SVTA setvalu e auger torqueo fauge r torque feedback mV control system SVTS setvalu e threshing separation efficiency incontro l % system4 D displacemento fth evariato rdisc so fth ethreshin g cylindervaridriv e DO, Dl parametersi nloss-.to-stra wfee drat erelationshi p DE displacementstra welevato rchai n cm s DT sampleinterva lo fth edigita lcontro l DTI derivatet o VWfro m CTI DV controlledpositio no fth evariato rdisc so fth e threshingcylinde rvaridriv e e Naperianconstant ;erro rvalu e EF combineharvestin gefficienc yfacto r

ƒ. breakpointfrequenc yo ffilter s rad«sl FGM grainfee drat emeasure db ymonito r kg«s FGT grainfee drat ea tthreshin gcylinde r kg«s FGTD delayedgrai nfee drat ea tthreshin gcylinde r kg-s FGR grainfee drat ea trotar yseparato r kg*s FGW grainfee drat ea twalker s kg-s FOB forcei nth ethreshin gcylinde rdrivin gV-bel t N FOM valueo f FOBbelo wwhic hwea rcost sar ezer o N FS feedrat eo fstra w leavingth ecombin eharveste r kg«s FSA strawfee drat ea tauge r kg»s FSAV averagestra wfee drat eove ra give nperio d kg-s FSC strawfee drat ea tcutte rba r kg-s FSE strawfee drat ea televato rchai n kg-s FSM strawfee drat esigna lmeasure db ymonito r kg-s FSR strawfee drat ea trotar yseparato r kg-s FST strawfee drat ea tthreshin gcylinde r kg-s FSV strawfee drat ea twalker s kg-s FSWA strawfee drat eo nwalker safte rredistributio n kg-s F frequencyo fpulsewis evariatio ni nfee drat e s

GF\ gaini n exponentialfilte ro fcontro lsyste m1 GFz gaini n exponentialfilte ro fcontro lsyste m2 GS grain-to-strawrati o t,T time s torque causedb yengin e inertia Nm T. torque available forthreshin g in Nm torque frommotorshaf t Nm torque into threshing cylinder Nm out T torque needed forthreshin g .t n Nm TA auger torque Nm TAUW time constanti nfirst-orde r transfero fredistributio n s of strawo nwalker s TE average valueo fpeak si nfee drat ea teve n straw feed TI averagevalu eo fpeak si nfee drat ea tirregula r straw feed TILF timeliness loss fractiona sfunctio no f VW TL threshing loss kg»s l TIF threshing loss fraction TNSE fractiono fgrain ,no tseparate d fromth estra wafte r threshing TOC total costso fharvestin g fl-ha 1 TSE threshing separation efficiency TSEM threshing separation efficiency measuredb ymonito r % TT task time forharvestin g h-ha"1 TÏT totalworkin g timefo rharvestin gpe ryea r h«yr 1

V proportional factor 1 V\ valueo fgrai n loss (exceptbreakag e loss) fl'kg" 1 V2 valueo fbreakag e loss fl'kg" -1 ^3 valueo fth eV-bel twea r fl-N s" 1 VBL valueo fgrai nbreakag e loss fl's" J VE speedo fstra welevato r chain m*s VFL level factori nthreshin g speed-to-feed raterela ­ tionship VFS slope factori nthreshin g speed-to-feed raterela ­ m2-kgT1 tionship VFSC adapted slope factori nthreshin g speed-to-feed rate m2'kg_1 relationship VM machine forward speed VU actualmachin eforwar dspee d VM optimummachin eforwar dspee dcalculate db ycos t minimisatio n VMAV averageforwar dspee d m's 1 VUL valueo fmachin elos s (ML) fl's" 1 VUN averagemachin espee di na manuall ycontrolle d m's situation VT threshingcylinde rrotatio nspee d VT actualthreshin gspee d VT optimumthreshin gspeed ,calculate db ycos tminimi ­ sation VW harvestedare ape rtim euni t (=VM'CL) fl'ha x VWC costso fwea ro fthreshin gcylinde rdriv e WA wageso fcombin eharveste roperato r fl'h -1 WE walker (grain)separatio nefficienc y kg*s •l.m"1 WE(s) WEfo ra certai nlengt ho fwalker smeasure dfro m kg»s fronto fwalker s WEW local WEfo ra certai nlengt ho fwalker sa tan y kg*s arbitrarilychose nplac e WEP walkerefficienc yparamete ri nwalke rseparatio nmode l kg-s WL walkerlos s kg's WLAV averagewalke rlos s kg's WLM walkerlos smeasure db ymonito r WS walkerseparatio n kg«s WS4 walkerseparatio ni ntra y4 kg WW widtho fwalker s m

YIELD averagegrai nyiel d kg-ha*

GREEKSYMBOL S n anglebetwee nth etw oside so fth ethreshin gcylinde r varidrivediscs ;regressio ncoefficien t Y anglei nV-bel tlengt hcalculatio n e difference a standarddeviatio n T timeconstan t y meanvalu e U angularvelocit y (seesubscript so f T) rad's 1. Introduction

1.1.GENERA L

Inth eprogres so fagricultura lmechanisatio ni nth etechnicall yhighl y developedcountrie sdurin gth elas tcentury ,som esuccessiv estage sca n bedistinguished :improvemen to ftool san dimplement sfo ranima ltraction , theintroductio no fmachine san dmechanica lpower ,o fhydrauli can dpneu ­ maticsystem san dincreasin gmachin esizes .Th eapplicatio no fautomatio n andelectronic si nagricultura lmachiner ywil lincreas ei nfutur eowin g toth eavailabilit yo fgreate rtechnica lpossibilities :microprocessors , electronicsensor san dhydrauli cdrives .Whe napplied ,i twil lb ewit h theai mo fincreasin gth efinancia lreturn sb yimprovin gth equalit yo f theagricultura lproduc tan dreducin gproductio ncosts .

Theai mo fthi sthesi si st oestablis hth emethodolog yb ywhic hth econ ­ tributiono fautomate dagricultura lmachiner yt oth eimprove dreturn s canb eevaluated . Thecerea lcombin eharveste rha sbee ntake na sa cas ei nwhic hw eca n considerho wcos tminimisatio nb yautomatio nca nb eachieve dan dasses s theexten tt owhic hcost sca nb ereduced .

Themetho dfollowe di nthi sstud yi st odevelo pa detaile doptimisatio n criterionan dtranslat ethi si nterm so fth etechnica lrequirement sa s toth edesig nan dadjustmen to fth econtro lsystem .Th eproces san dth e costcriteri ahav etherefor ebee ninvestigate di norde rt ogathe rth e requiredknowledge . Inorde rt oestimat eth einfluenc eo fth echoic ean dadjustmen to fa specificcontro lsyste mo nth etota lcosts ,a simulatio nmode lha sbee n madeo fa combin eharveste requippe dwit hvariou scontro lsystems .Th e modelshav ebee nbase do ndat afro mfiel dstudie scarrie dou tfro m196 9 to197 8inclusive .Thi smetho do fstud ywa schose nt ob eabl et ocompar e

1 differentpossibl ebu tno tye trealise dautomati csystem st oeac hothe r andt omanua lcontro lunde ridentica lconditions .

Themetho di sworke dou ti nth efollowin gchapters .Th eharvestin gproces s iss ocomple xa matter ,tha tman ysimplification shav et ob eintroduce d inorde rt ob eabl et osolv eth ecomplicate dproblem sinvolved .Thes ewil l bebriefl yexplaine dher ean dworke dou ti ndetai li nth echapter sdealin g withth emodels . Manymodel sar ebase do ninvestigation sno tye tpublished .I twa sfoun d practicalt opu tth edetail sint oa nappendix.i norde rt oillustrat eth e systematicsan dth emetho do fth estud yi nth emai ntext .Thi sinformatio n islocate dunde rth esam echapte rnumberin ga si suse di nth emai nreport , precededb yth elette r"A" . Forreader sunacquainte dwit hcombin eharvestin go fcereals ,th epro ­ cessan dorganisatio ni sdescribe dbriefl yi nth eappendi x (A1.1.a) . Drawingsan dmachin especification sar eals opresente dthere .Fo rthos e notfamilia rwit hcontro ltheor ya ver yshor texplanatio no fth eterm s usedi nthi sstud yi sals ogive ni nth eappendi x (Al.l.b) .

1.2.LITERATUR E

Automationi ncerea lcombin eharvester sha sbee na subjec to fresearc h since 1956.I nsom ecase sth epurpos ei st oreduc eth eoperato rwor kload . Systemshav ebee ndevelope d tofollo wth eri mo fth ecro p (edge-guide steeringsystem) .Other sadjus tth eheade rheigh teithe rb ysensin gth e surfaceo fth egroun do rb ycontrollin gth emowe dstra wfo rlength .System s haveals obee ndevelope dt ocontro lth eloa do fth ethreshin gcylinde rs o ast outiliz eth eavailabl eengin epowe rt oth emaximum .Fo rman yyear s nowcombin eharvester shav ebee navailabl ewit hsystem sfo rlevellin gth e machineo nslope si nth elongitudina la swel la sth etransversa ldirection . Researchi sbein gdon eo nsystem swhic hadap tth eadjustmen to fth efa n toth ecro ppropertie si norde rt oreduc esiev elosses .Thes esystem swil l notb ediscusse d inthi spublication . Ourmai nattentio nwil lb ecentre do nsystem swhic hcontro lth eforwar d speedo fth ecombin ean dth eperiphera lspee do fth ethreshin gcylinder . Actuallyth epurpos eo fthes esystem si st ocontro lth elosse san di npar ­ ticularth ewalke rloss .I nth eappendi xa revie wi sgive no fth ereference s dealingwit hthes esystems .Th econclusion sar epresente di nthi ssection . 2 Whenth ecro pthroughpu ti scontrolle db yadjustmen to fth edrivin g speedt ovariatio ni nth estra winput ,measure db ya variabl ewhic hi s closelyrelate dt oth estra winput ,thi styp eo fsyste mi sknow na sa stra w feedrat econtro lsyste m (A1.2.2) . Whenth edrivin gspee di scontrolle dvi alos sindications ,th esyste m isknow na slos scontro lsyste m (A1.2.3) . Whenth edrivin gspee di scontrolle db ybot hlos smeasuremen tan dfee d ratemeasuremen tth esyste mi sknow na sloss-fee drat econtro lsystem . Influencingth elosse sb ycontrollin gth espee do fth ethreshin gcylin ­ derha sals obee nresearche d (A1.2.4) .Thes esystem sar eknow na sthreshin g speedcontro lsystems . Thoroughknowledg eo fth edynamic so fth ethreshin gan dseparatio npro ­ cessesfo rdesig no fth econtro lsystem si srequired .Toward sthi send , modelstudie so fth eprocesse si nth ecombin eharveste rhav ebee ncarrie d out (A1.2.5) .

Theai mo fkeepin gth elosse sa ta constan tlevel ,a sformulate di nlite ­ rature,i sbase do nresearc hint ooptimisatio no fth ecerea lharvest .Th e ideao fon eoptimu mlos slevel ,however ,i sbase do na nincomplet etheory . Thistheor yca nb edescribe dbriefl ya sfollows :A nincreas ei ndrivin g speedresult si na ris ei nstra winpu ta sthi si sdetermine db yth epro ­ ducto fworkin gwidth ,drivin gspee dan dth ecro pmas spe runi tarea .A n increasingstra winpu tcause sa nexponentiall yrisin gloss .A reductio n indrivin gspee dno tonl yresult si na lowe rmachin eloss ,bu tals oi na smallerare aharveste db yth emachine ,resultin gi nhighe rmachin ean d labourcost spe rhectare .Wit ha give nacreag epe rcombin epe rseason ,a lowerspee dwil lresul ti nharves tdelay ,causin ghighe rtimelines slosses . Thereforether ei salway sa noptimu mlos slevel .Los scontro lca nthu sb e favourablei fw ear et omaintai nth elos sa ttha toptimu mlevel . Thecalculatio no fth eoptimu mlos sleve lha sbee ndon eb ymode lstu ­ dieso fharvesting .I nthes emode lstudie sjus ton eloss-to-fee drat e relationshipi sused ,resultin gals oi njus ton eoptimu mlos slevel ,give n byth ecos tfactor san dconstraint so fth estudie dsituation .On esingle - feedrat eleve li soptimu mfo rthi slos sleve lalso .However ,whe nth e lossfee drat erelatio nchanges ,no tonl ydoe sth efee drat eleve lchang e butals oth eoptimu mlos sleve litself . Allwriter so nth esubjec tar eawar eo fth efac ttha ta changin gloss - to-feedrat erelatio nindicate stha tth emea nstra wfee drat eo rth ese t valueo fa fee dcontro lha st ob echange da swell ,bu tn ogn erealize d thatth eoptimu mlos sleve li ntha tcas eca nchange ,too .Thi swil lb e explainedi n1.4. 1o fthi sstudy .

Theadvantage sexpecte do fth eautomati ccontro lare ,lowe rmenta lloa d onth eoperator ,a smoothe rfee dint oth ecombin eresultin gi nles sjam ­ ming,lowe rfue lconsumption ,les swea ran dlowe rlos slevels .Th eexten t ofth ebenefi ti sexpresse di nth eliteratur ei nterm so freductio ni n thevariatio ni nstra wfee drat ean dris ei nth efee drat elevel .Th e increasei nfee drat eleve li sonl ycorrectl ycalculate di flosse sar e kepta tth esam eleve la swithou tth econtrol .Benefit so f5 - 30 %ar e mentioned.Thi swid erang ei sdu et oth ecircumstance sunde rwhic hth e researchi scarrie dout :loss-fee drat erelationship ,chose nlos sleve lan d strawdensit yvariatio naffec tth ebenefi t (seeA 1.2.7).Onl ytw oauthor s havetrie dt ocalculat eth ebenefit si nterm so ffinancia lreturns .

Fekete (1981)studie dth ebenefit so flos sfee drat econtro lsystem so n threecombin eharvester si npractic ei nPoland .Reductio ni nth ecos t ofcombin eharvestin gwa sfoun dt ob e6-7% .Thi sresul twoul denabl eth e costso fth econtro lsyste mt ob eamortise di n2 years . McGechan (1982)calculate dth ebenefit so fdifferen tlos scontro l systemsb ysimulatio nbase do ncro pvariabilit ydata .H econclude dtha t thebenefi tfo ra 20 0h agrai nfar mi nScotlan dwoul db ever ysmall ,to o smallt ojustif yth ecos to fa contro lsystem .I nth epresen tstudy ,too , aconstan tlos sfee drat erelatio nha sbee nused ,s otha tvariatio ni n thisrelatio ncoul dno tresul ti na benefi twit ha contro lsyste madapte d tocro pvariability .I nou ropinio nthi spossibl ycause sth ebenefi tt o beunderestimated .

Eimer (1973)reporte do na threshin gcylinde rspee dcontro li ncombinatio n witha fee drat econtrol .Hi sai mwa st ocompensat eth eeffec to fstra w feedrat efluctuation so nlosse sb ycontrollin gth espee do fth ethreshin g cylinderi norde rt oimprov eit sseparatio nefficiency .H estate stha t thiscontro lsyste mallowe da nincreas ei nfee drat eo f40 %i nry ean d25 % inwhea tfo rth esam elos slevel .Ho wthi swa smeasure dwa sno texplained . Comparisono fautomati ccontro lsystem st omanua lcontro li npractic ei s verydifficult .Th emachine ,it sadjustment san dth ecro ppropertie smus t beth esam ethroughou tth etests .Besides ,whe ndifferen tsystem sar ewor ­ kingclos etogether ,th eoperato ro fth emanuall ycontrolle dmachin ewil l beinfluence db yth espee do fth eautomaticall ycontrolle dmachines .Anothe r problemi stha tsystem stha tinclud elos scontro lnee dadequat elos smea ­ suringdevices .Th eacousti c sensorsuse dfo rthi spurpos ea tpresen tar e notye taccurat eenough .

Thefollowin gconclusion shav ebee nreache dfro mth estud yo fliterature . Thecontro lsystem sdescribed,contro la leve lo flos so rfee drat eo r machinepower .Th eleve lt ob echose ni sno targue do noptimisatio ncri ­ teriaan di sthoug ht ob econstant .Adaptio no fthes elevel st ochangin g conditionsha sno tbee nconsidere dunti lnow .I twil lb enecessar ythere ­ foret oinvestigat eth ecriteri afo roptimu mcontro lan dincorporat eth e calculationo fth ese tvalue si nth econtro lsystem . Thedifferen tcontro lsystem sintroduce dar eno tcompare dan dcanno t becompare di nth efiel dbecaus eth elos smeasurin gdevice sar einadequate . Beforedesignin gth esystems ,th eeconomi cbenefit shav et ob eestimate d andcompare dt othos eobtaine dwit hmanua lcontrol .

1.3.AI MO FTH ESTUD Y

Theconclusion sdraw ni nth eliteratur erevie war erestate dbriefl ybelow : -Non eo fth eknow ncontro lsystem sar edesigne d fromth eviewpoin to f optimisingharves toperatio na sa functio no fvaryin gcro pan dweathe r conditions. -Th einadequac yo fth eavailabl elos smonitor smake si tdifficul tt o estimateth erea lbenefit so fexistin gcontro lsystems . -Th evariou sknow nsystem scontro lthreshin gspee dan dmachin eforwar d speedi ndifferen tway sbu tth ebenefit so fthes esystem shav eno tye t beencompared .

The aim of the present study will therefore be to develop different control systems, optimising the forward speed and the threshing cy­ linder speed of the cereal combine harvester and reacting to varia­ tions of the crop properties, each system applying different combina­ tions of input signals and controlled outputs. In addition, the benefits of each system compared to those obtained with manual control will be assessed.

Withthi sen di nview ,th erequiremen ti st o -develo pa noptimisatio ncriterion , -quantif yth eimportan tproces sdisturbance stha taffec tmachin eper ­ formance, -investigat eth ewa yi nwhic hth ecriterio nca nb eoptimised , -develo pcontro lsystem stha toptimis eth ecriterion , -asses sth ebenefit so fth esystem scompare dt othos eo fmanua lcontro l bysimulation . Modelso fth eprocess ,machin edrive smeasuremen tsystem san dcontro l systemshav et ob edevelope d forth esimulation .

1.4.METHO DO FTH ESTUD Y

Inthi ssectio nth emetho do fth estud ywil lb epresente di ncondense d form.Detail sar eexplaine d inth efollowin gchapter san di nth eappendix , butth efundamenta lapproac hwil lb edescribe dhere .Thi sapproac hinclu ­ dessimplificatio ni norde rt oallo wth ever ycomple xproces so fcontro l incombin eharvestin gt ob eresearched .The ,simplifyin gassumption swil l beindicate di nth etex ti nitalics .

1.4.1. Optimisation criterion

Theobjectiv eo ffarmin gi st oproduc eagricultura lproduct sprofitably . Innovationsi nfarmin gar emad et omaximis eo rmaintai nprofi tlevels . Harvestoptimisatio ncalculations ,ar emad eo nth ebasi so fharves tmodel s toasses sth eoptimu msiz eo rnumbe róf -th ecombin eharvester sfo rgive n conditions (Kampen,1969 ;Boyce ,1972 ;Philip s 1974). Onc eth edecisio n onth enumbe ran dsiz ei staken ,th evariou smachin evariable smus tb e adaptedt oth evaryin gcro pan dwalke rconditions .

Ifw etak eth eharvestabl emas so fgrai nan dstra wa sdetermine da tth e momento fcombin eripenes s (seeA 1.1.a )an ddenot eth edecreas eo fhar - vestablegrai nfro mtha tmomen ta sopportunit ycosts ,th emaximu mprofi t canb econverte d intominimu mcosts .Th edecremen to fstra wmas swil lb e assumed tob eeconomicall ynegligible . Wewil lfurthe ronl ytak eint oconsideratio nth ecost saffecte db yth e variationi nmachin eforwar dspee dan dperiphera lspee do fth ethreshin g cylinder.Th esu mo fthes ecost si sth ecos tfunction ,o rtota lcosts .

Thecos tfunctio nha st ob eexpresse di nsuc ha wa ytha tth esu mo fal l importantcos telement sca nb eclearl yshow nan dcalculate da sa functio n oftime .Thi si sdon es otha t -i tca nb eshow nwh ybenefit sca nb eexpecte dfro mcontro lsystems ; -th eexten to fth ebenefit sobtaine d fromth econtro lsyste mca nb eeasil y calculated; -th eoptimu msetting so fth emachin espee dan dthreshin gspee dcontrol s canb ecalculate dcontinuously ,adaptin gt oth especifi ccombin eharveste r andcro pconditions .I ti s assumed thatthi swil lb edon econtinuousl yb y meanso fa microprocesso ro nth emachine . Thevariou scos telement stha tg ot omak eu pth ecos tfunctio nar ewor ­ kedou textensivel yi nchapte r2 bu twil lb esumme du phere .Th ecost s areexpresse d inguilder spe runi tare a (fl'ha )an dno tpe runi ttim e (fl's 1) asth etota lare at ob eharveste di susuall yfixe dan dtherefor e thetota lharvestin gcost sca neasil yb ecalculated .The yare :th etota l machinecost s CM,mad eu pou tof : MVC= Machin evariabl ecosts ,suc ha stechnica lwear ,require dfue lan d lubricants.The yar e assumed tob eproportiona lt oth eharveste darea ; HVC- Machinean dlabou rcost stha tar eproportiona lt oth ewor k timebu t arerecalculate di nfl'h a ; MFC= Annua lfixe dmachin ecost ssuc ha sdepreciatio nan dinterest ; themachin elos scost sresultin gfro mth efinancia lvalu eo fsiev elos s (SL), threshin glos s (TL), grai nbreakag elos s (BL),walke rlos s (WL); thetimelines slosse scost s TILCan dth ecost so fextr awea ro fth eV-belt , drivingth ethreshin gcylinder . Thewa yi nwhic hcost sar eaffecte db ycontro lo fmachin ean dthreshin g speedswil lb eshow nbelow .

The effect of machine speed on costs

Achang ei nth eforwar dspee do fth ecombin eharveste rbring sabou ta changei nth ecapacity ,tha ti sth eamoun to fgrai nharveste do rth eare a harvestedpe runi to ftime .A nincreas ei nth edrivin gspee dwil lresul t 7 ina chang ei nth efollowin gcost-determinin g factors.(Th edetail sar e giveni n2.2. )

Costswil lthe nincreas ebecaus eth egrai nlos sincreases . Costswil ldecreas ebecaus e 1.th eharvestin gperio dbecome sshorte ran dlabou ran dtimelines scost s willb ecu tdown . 2.Th eactua lharvestin gtim eca nb ereduce ds otha tth ecombin estart s whenth ecro pha sreache da nadequat eleve lo fgrai nmoistur econten t naturally,thu sreducin gdryin gcosts . 3.A large rare aca nb eharveste di non eseason ,resultin gi nlowe rmachin e costspe rhectare . 4.Th enumbe ro fmachine st ob euse di na specifi care aca nb ediminished . Thesefou rfactor sar et osom eexten tinterchangeable .Factor s 1an d2 sho w short-termeffect so ncost swhil efactor s3 an d4 sho wlong-ter meffects .

Iti sadvisabl et ostud yth eeffec to fcontro lo nbot hlevels .Fo rthi s reasontw oway so fusin gcombin eharvester swil lb econsidere di nwhic h botheffect sar eclearl yevident . Inth efirs tcas ew econside r cereal farmers who work with a variable harvesting -period and a fixed area, a fixed number of combine harvesters and fixed maximum grain moisture content. Herei nparticular ,th edeter ­ minantsar etimelines slos scost san dlabou rcosts .Th egrai ndryin gcost s arefixe dbecaus eth etimelines slos scurv ei sdetermine db yth eworkabl e hoursresultin gfro mfixe dgrain-moistur elevel s (see2.2) .

Inth esecon dcas ew ehav e a contractor or cereal farmer with such a large area that the number of machines in use can be varied. Theharvestin g period,th emea ngrai nmoistur econtent ,thu sgrai ndryin gcost sar e assumed tob efixed .I nthi scas ei ti sth emachin ecost stha tar eth e determinants.

Thecos telement sar ecalculate d forthes etw oway so fusin gth ecombin e onth ebasi so fdat arelatin gt oth eyea r 1982.Th etimelines slos scalcu ­ lationsar ebase do ntw olevel so fweathe rrisk ,i.e .25 %an d 162/3 %re ­ ferringt oth epercentag eo fyear si nwhic hth enumbe ro fworkabl ehours , usedi nth ecalculatio no fth etimelines slos scurve ,wil lno tb eavailabl e duet oth eweathe rconditions .

8 Whenw estud ythes ecost sa sa functio no fmachin espee dthe nw emus tfirs t realisetha tstra wfee drat e (FSi nkg« s l) arisesfro mth estra wdensit y (SDi nkg* m ),tha ti sth eamoun to fstra wo nth efiel dpe runi to farea , thecuttin gwidt h {CLi nm )an dth eforwar dspee d {VMi nm* s ')o fth e combineharvester ,namel y FS= SD'VM'CL kg-s"1 (1.1) Letu s assume SDan d CLt ob econstan tthe n FSi sproportiona lt o VM. The relationsbetwee nlosse san dstra wfee drat ear ei ngenera la sindicate d infig .1.4.1. 1s otha tincreasin gmachin espee dgive sincreasin glosses .

Losseskg-s _1 Totallos s

FS kg-s-1

Figure 1.4.1.1.Grai nlosse srelate dt ostra wfee drat e (straw= m.o. g =materia lothe rtha ngrain )

Ifth ecuttin gwidt hi sconstant ,th eharveste dare a VWi sals oproportio ­ nalt oth espee do fth emachin ebecaus e VW= VM'CL m2-s-1 (1.2) Allcos tfactor sar ethe nworke dou ta sa functio no f VWan dca nb e plottedi nthi sway .W ethe nhav efig .1.4.1. 2fo rth ecas etha tth ema ­ chinei suse db ya contracto ro ra cerea lfarme rwh owork swit ha fixe d harvestperio dan da variabl eare ape rmachine .I nthi sfigure ,thre eline s oftota lvalu eo fwalke rlosse sar eplotted : VWL(l) , VWL(2)an d VWL{e) . Thisresult si nthre edifferen tline so ftota lcost s TC{1) , TC{2) and TC{e), eachgivin gcos tminim aa tdifferen tcos tlevel san da tdifferen tvalue s of VW,whic hmean sthre especifi coptimu mmachin espeeds . Fromthi si ti sclea rtha tther ear ecos tminim atha tvar ywit hdiffe ­ ringlos scurves .Th eobjectiv eo fspee dcontro li st oadjus tth eactua l machinespee dt oth eoptimu mmachin e speedtha tvarie swit hvaryin glos s costcurves .Ther ear etw oreason swh yth elos scos tcurv evaries . Inth efirs tplace ,cro ppropertie svar ybecaus eo fvaryin gweathe ran d growingcondition san dbecaus eo fth ekin dan dbree do fth ecro pvaries .Th e difference inth ecurve s VWL(X)an d VWL(2)i sa nexampl eo fthat .Thes e variationsca nb econsidere da smea nleve lan dlow-frequenc yvariations . Inchapte r4 the yar equantified .

fl-ha-1 TC[e)

Figure 1.4.1.2.Cost so fcombin eharvestin grelate dt oth eharveste dare a VW {=VM'CL)fo ra fixe dharvestin gperio di nwhic hth eharveste dare a varies. HVC= labou rcosts , MVC =machin evariabl ecosts , MFC= annua lfixe d machinecosts , CM =tota lmachin ecosts , VWL =cost so fgrai nlosse sdu e tomachin eperformanc eunde rth efollowin gthre econdition swit hdifferen t loss-to-feedrat erelations :(1 ) WL= 0^001 5ex p(W-0.58 ), (2 ) WL= 4.5-105 -exp(W-0.40), (e ) WL= 4.5-1 05 ex p(W-0 .50 ). A= minimu mcos tpoin tfo r VWL(2 ), B = minimu mcos tpoin tfo r VWL(e), C= tota lcost sfo rstra wdensit y SD= 1.1'(SD atA) , D= tota lcost sfo r SD= 0.9'(SD atA) ("SD atA "stand sfo rstra wdensit ytha thold s for minimumcos tpoin tA) . (. )= lin eo fminimu mcost spoint sfo r VWL{2)a tdifferin g strawdensities . Theline sar ecalculated ,usin gth evalue sexplaine di n2.2 : MVC=_67. — fl-ha x, WA =40. —fl-h" 1, AFC =425000^ — fl-yr, V\ =0^5 0 fl-kg l, AAN =10 0ha , VMN =1 m- s \ HE =0.2 5h-h a l, CTI= 0 fl-h a'

Itca nb esee ni nth efigur etha tth eoptimu mi sno tfoun da ta constan t losslevel .Th eoptimu mi slocate da ttha tvalu eo f VWa twhic hth eslop e ofth ecurv eo fdecreasin gtota lmachin ecost si sequa lt oth enegativ e valueo fth eslop eo fth ecurv eo fincreasin glos scosts .

10 Thesecon dreaso no fvaryin glos scos tcurve si sth enatura lvariatio ni n strawdensity .I fth elos scurv ea sa functio no fstra wfee drat e FSdoe s notchange ,th elos scos tcurv ea sa functio no fharveste dare a VWbecome s dependento nth estra wdensit ybecaus efro m (1.1)an d (1.2)ca nb ederive d thatth estra wfee drat e FSca nals ob ewritte na sth eproduc to fstra w density SDan dharveste dare a VW FS= SD-VW kg-s"1 (1.3) Thisals omean stha ti f VWi sconstant ,the nstra wfee drat e FSbecome s proportionalt ostra wdensit y SD, sotha twalke rlos s becomesdependen t on SD. Forinstance ,fo rth ecurv eo f VWL(e) infig .1.4.1. 2th esam ewalke r lossfee drat erelationshi pi suse da sfo r VWL{2)bu tth estra wdensit y leveli sincrease db y25% ,givin gth ecos tminimu ma tB instea do fA .Th e costminim afo rjus ton eloss-to-fee drat erelationship ,bu tfo rvaryin g strawdensit ylevels ,ar efoun da tth edotte dlin ei nfig .1.4.1.2 .

COSTSfl.ha- ' 1200- CTI

1000

800

600

400 -V--\ - \

200

Figure 1.4.1.3.Cost so fcombin eharvestin grelate dt oth eharveste dare a VW(=VM'CL) inth ecas etha tth eharves tperio dvarie swit h VWan dth e averagewinte rwhea tt ob eharveste dpe rmachin ei sfixe da t10 0h afo r a farmer ( )an d17 5h afo rth eUsselmeerpolder sDevelopmen tAuthorit y large-scalegrai nfar m ( ). CTI= cost so ftimelines slos scalculate dfo rtw olevel so fweathe rris k givenb yth epercentag eyear si nwhic hth enumbe ro fworkabl ehours ,use d inth ecalculation ,tha ti srespectivel y25 %an d1 62/3% ,ar eno tavailabl e duet oth eweather . TC =tota lcost sfo rth e 162/3 %risk .Fo rth eothe r costfactor sse efigur e 1.4.1.2.

11 The task ofa machin e speed control system ist ocalculat e theoptimu m desired machine speed andt oadjus t theactua l speed inorde r tobecom e identically toth ecalculate d value.Th esyste m must thenhav e information aboutth estra wdensity ,th eloss-to-fee d rate relationship andth eothe r cost functions.

The cost functions differ from thoseo f fig.1.4.1. 2i nth ecas e thatth e harvesting period isvariabl e andth eare a tob eharveste d isfixed .I n that situation the timeliness loss costsar ea functio no fth eharveste d area VW. Inthi scas e thecurve s infig .1.4.1. 3hav e tob euse d tocal ­ culate optimum machine speed.Th etechnique ,however ,i sth esame .Th e timeliness losscos tcurv e tob euse d dependso nth eweathe r risk,are a tob eharveste d andgrai nmoistur e limitations aswil lb eexplaine d in2.2 .

The effect of threshing speed on costs

The threshing speed influences themachin e lossesa sindicate d infig . 1.4.1.4.Whe n threshing speed increases,th ebreakag e ofgrai n increases. As strawbreakag e increases too,th estra w load onth esieve s increases so thatth e sieve losseswil l rise.Threshin g losswil l also decrease, and asth egrai n separation through theconcav e grate increases,th ewal ­ ker loss will also decrease.Th edamage d seeddoe s notalway s affect the valueo fth egrai n soldbu tth eothe r lossbecome s acos t element whose money value is foundb ymultiplyin g theactua l amount lost,by themarke t price ofth egrai nminu s thecost so fdrying ,transpor tan d storage.

Losseskg-s - Totallos s

0L Vt vrm-s-1 4°

Figure 1.4.1.4. Grain losses related tothreshin g speed

12 The shape of the curves isdependen t on croppropertie s and straw feed rate level as in fig. 1.4.1.5.Fro m the figures it iseviden t that there is always anoptimu m threshing speed conditionedb yth e crop properties and the straw feed rate. Since the crop properties vary slowly as a functiono fplac e and time and the straw feed ratevarie s notonl y slowly but alsoquickly , there is a succession of different valid curves and different optimum values for the threshing speeddurin g themovemen t of the machine.Whe n thethres ­ hing speed iskep t constant for anumbe r ofhours ,a s is often the case with manual control inpractice ,th e costs are notkep ta t a minimum.

When themachin e speed varies,there isa n interactionbetwee n the optimum machine speed and the optimum threshing speed thatmake s optimisation even more complex.

Totallosse skg. s- 1

<

VTm.s- 14 0

Figure 1.4.1.5. Total grain losses as a function of threshing speed for two different crop-property situations si, S2 and two different feed rate levels ( )an d ( ).

1.4.2. The reason for simulation

In thepreviou s section the optimisation criterion hasbee n worked out in detail. Itha s alsobee n shown that the speeds atwhic h minimum costs are foundwil l vary inpractice . The aimo f the study is to calculate thebenefi t of automatic machine and threshing speed controlbase d upon such anoptimisatio n criterion compared tomanua l control. Computer simulation was thought tob e a good calculation technique for the following reasons.

13 - By simulation alone,on e can study the various control systems,inclu ­ ding manual control,unde r known conditions inwhic h disturbances in theproces s and otherharves t conditions are made identical. - We can check in detail how the various control systems affectharves ­ ting costs.Al l variables of interest can be studied, so that their role and influence canb e assessed. - The values ofparameter s canb e adjusted separately so that insight into theproces s can easily be increased. One can exclude the inter­ actions ofparamete r values. - The availability ofmeasurin g systems and control systems can be assumed so thatn o investments have tob e madebeforehand,fo r improvement or introduction of systems.Thi s iso f importance for the control systems and the loss-measurement system. - Iti s easy toadjus t the control and themachin e variables at which theharvestin g has tob e performed.

For the above reasons theproble m will beworke d out as amode l study using the simulation as the main tool. In this chapter therefore the optimisation problemwil l be formulated in detail,takin g into account the implementation of the simulation. The process and control systems willb eworke d out in the following chapters. In chapter 2 the technique of modelling is described and cost data and models of theproces s worked out. Chapter 3describe s measurementdevices . In chapter 4 the disturbances are studied andw e statewhic h sample of the disturbances is tob e selected as an inputo f the simulation. The control systems are developed in chapter 5an d in chapter 6 thesi ­ mulation isconsidere d and the results are given in termso f costs per hectare. In chapter 7th e general conclusions about the optimisation are summa­ rised.

1.4.3. Formulation of the optimisation problem

Inorde r tob e able tominimis e costsb y simulation we have in addition to the cost criterion, to formulate the various conditions under which combine harvesting is carried out.Thes e conditions concern the use made of the combine harvester, the course of theproces s and the selection of

14 thecontrollin gvariables .

1. Parameter values for the cost model affected by the use made of the combine harvester Everyowne ro fa combin eharveste ruse sth emachin eunde rhi sow nspe ­ cificcondition sa st oarea ,selectio no fcrop so rvarieties .H eals o makeshi sow nassessmen to fth eweathe rris kaffectin gth etimelines s lossexpectatio nan dmaximu mlevel so fgrai nmoistur econtent .Si xdif ­ ferentcos tsituation sar edefine dt ocove rmos to fth esituation si n whichth ecombin ei sused . IThechose nvalue so fth earea st ob eharveste di n3 situation sar e inth eneighbourhoo do fth eoptim agive ni nth eliterature ,base dupo n harvestoptimisatio nmodel sfo rgrai nfarm sunde rEuropea ncondition s (Baumgartner,1969 ;Boyce ,1972 ;Philips ,1974) .Th eharves tsituation s ofth e3 othe rcos tsituation sagre ewit hth eaverage dharvestin gopera ­ tion,tha ti sth eresul to fharves toptimisatio nbase dupo na harves t simulationmode lo fth eUsselmeerpolder sDevelopmen tAuthority .Thi s modeli si nus ean dha sbee nimprove dcontinuousl y forabou t1 5year s (Kampen,1969 ;Hagting ,1976 ;Fokkens ,1981) . Theare at ob eharveste dpe rmachin eha sbee nmad evariabl ei nsom e situationsi norde rt ostud yth eeffect so fcos tminimisatio nb ycontrol s onlon gter mdecision so nsuc hareas . Thedetail so fthes ecos tsituation sar egive ni n2. 2bu tar edefine d brieflybelow .

Cost situation 1: Thelengt ho fth eharves tperio di sdependen to n machinespeed ,th eare abein gfixe da t10 0h ape rmachin etha tca nb e thoughtt ob ei nus eo non efar mo rb ya grou po ffarms .Th etimelines s lossris ki sse ta t25 %an dth egrai ni sharveste dwhe nth egrai n moistureconten ti s23 %o rless . Cost situation 2: Thesam econdition shol dfo rthi ssituatio na suse d incos tsituatio n1 ,excep ttha tth efar mi sth elarg escal egrai nfar m ofth eUsselmeerpolder sDevelopmen tAuthorit y (IJ.D.A.) s otha tth efixe d areape rmachin ei s17 5h awhea tan dth emaximu mgrai nmoistur econten t is27 %o rless . Cost situation 3: Thesam econditions ,suc ha scos tsituatio n 1hol d forthi ssituation ,excep tfo rth etimelines slos sris ktha ti sse ta t 162/3% .

15 Cost situation 4: Thesam econdition sa si ncos tsituatio n2 (IJ.D.A.) butth etimelines slos sris ki sse ta t1 62/3% . Cost situation 5: Theharveste dare ape rseaso ni sabou t10 0h abu t isdependen to nmachin espeed ,whil eth eharves tperio di sfixed .Th e costfactor sar ecalculate dfo ra contracto ran dharves tcondition sar e likethos eo fcos tsituatio n1 . Cost situation 6: Thissituatio ni slik ecos tsituatio n5 bu tth e costfactor sar ethos eo fth eIJ.D.A .i ncos tsituatio n2 .

2. The timeliness loss expectation is not ohanged during the harvest season Theharves tcos tminimisatio ni nou rsimulatio nwil lno tb eadapte dt o achang ei nexpecte dtimelines slos sdu et oth eweathe rconditions .Th e twotimelines slos sris klevel suse di nth esimulatio nwil lgiv esom e informationabou tth esensitivit yo fth ecos toptimisatio nt oth etime ­ linesslos scurves .Thes ecurve smus tb eadjustabl ewhe na contro lsyste m isuse di npractice .

3. The process of threshing and separation Thecharacteristic so fth eprocesse si nth ecombin eharveste rdefin eth e relationsbetwee nloss ,an dspeed sa swel la sth erestriction si ncontrol . Inthi swa yth eproces sals odefine sth ecos tminimisation . Adynami cmode lo fth ecombin eharvester ,formulate di naccordanc ewit h thedesig nan ddimension so fth ecombin eharveste ri sneede dfo rth esimu ­ lation.Th eproces si sdefine db yth edesig no fth emachin eunde rconside ­ rationan dth ecrop sharvested . Inthi sstud yth ecombin eharveste ri sa relativel y largemachin e equippedwit hthreshin gcylinder ,rotar yseparato ran dstra wwalker s (seeA 1.1.a).Th eproces si sworke dou tfo rwhea t (see2.2) .Th edis ­ turbancesi nth eproces scause db yth evariation si ncro ppropertie sar e definedb yth eDutc hcondition sa tth eFlevopolder sa st ocrop ,soi lan d weather.The yar erecorde di nth efiel dan da sampl ei stake nfo rinpu t intoth esimulation .

4. The selected controlling variables Anumbe ro fvariable sha st ob eadjuste dfo roptimu mperformanc eo fth e process inpractice :siev ean dfa nadjustments ,threshin gconcav eadjust ­ mentan dspeed so fmachin ean dthreshin gcylinder .

16 After a study of the literature on the threshing process itwa s con­ cluded that continuous adaption of the concave adjustment to feed rate was notworthwhile ,an d that adaption to croppropertie s need not be done continuously. For reasons of limitation, the sieve and fan adjust­ ments areno t studied, so thatmachin e and threshing speeds have remained. Costs and process variables have tob e formulated in accordance with these speeds for the simulation. Costminimisatio n by control of these variables depends on the design of the control systems. Indesigning ,accoun tha s tob e taken of the variouspossibl e alternatives.

Consideration of the optimisation problem

The objective of automatic control is to influence aproces s in such a way that theproces s variables evolve according toa previousl y defined plan. In our case thepla n is tooperat e the combineharveste r atminimu m cost according to apreviousl y defined criterion.T o achieve this,w e must solve an optimum control problemhavin g the following characteristics: 1.Thi s control problem includes a dynamic system that evolves intime . This implies that the differential equations that govern the behaviour of theprocesse s in the combine harvester mustb e considered as constraints on theoptimisatio n problem under consideration. 2. The optimisation problem must take accounto f the stochastic nature of the disturbances acting upon the combineharvester . Thusw e have a stochastic optimisationproble m described by models of the harvester process and by models of the disturbances. 3.Onl y alimite dnumbe r ofproces s variables canb emeasured ; themeasure ­ ments of some variables can only be realized with the aid of atrans ­ ducero r measuring systemwhic h introducesmeasuremen t errorso rnoise . This requires dynamic filtering of some measured variables. 4. Someproces s characteristics,notabl y someessentia l parameters used in the cost function,ar e notknow n in advance and mustb e estimated on line during theoperatio n of theharvester . The solution of adynami c optimisation problem for anonlinea r dynamic systemhavin g time delays,unknow nparameters , stochastic disturbances andmeasuremen t noise leads to an intractable situation.Th e formal solution - ifon e manages to compute it- shouldb e available online , that is as an explicitly computable function of the available measured

17 variables. One may expect thatsuc h a solutionwil lb e much too complex tob e of directpractica l use.Therefor e we will simplify theproble m so that an usable sub-optimum solution results.

Simplifying assumptions in the formulation of the optimum control problem

The disturbances in theproces s are stochastic, so thatmeasure d signals have tob e filtered. For optimum filtering, Kalman filterswoul d bebest , butknowledg e of thebehaviou r of the disturbances is too slight to allow their use atpresent . First-order low-pass filters are used instead.

The main disturbances in ourproces s are mean value and low-frequency variations. Croppropertie s especially vary slowly but straw density also does so as canb e seen, for instance in figure 1.4.3.1.Thi s figure shows the straw density variation measured for the 5.9 mwidt h of the combine harvester header over three different stretches of 25m of the same, very-homogeneous-looking field.

20 25 distance m

Figure 1.4.3.1.Variatio n of straw density on three different stretches at the same tieldwit h winter wheat at the IJ.D.A.

In addition thehigh-frequenc y variationswhic h occur dono tmuc h affect themea n loss levelbecaus e their effect on losses due topositive-devia ­ tions from the mean straw feed rate level are compensated by those of the negative deviations.Thi s is the case,becaus e the exponential rela­ tion of loss to straw feed rate applied to awid e range of feed rate, canb e considered approximately linear over the short range inwhic h the feed rate varieswhe n the combineharveste r only traverses a short dis­ tance. This effect isquantifie d in figure 1.4.1.2wher e point C indicates

18 the total costs in the case that the straw density is 10%highe r than the density thatwa s thebasi s of the calculated optimumpoin tA . The costdifferenc e between A and D, referred to costs at a 10%lowe r straw density, is about the same as the difference of A toC .

Thepresenc e of dynamics and delays in theproces s requires dynamic control. Because of the slowly varying disturbances we can consider the optimisation problem as split up into 1)a quas i steady-state optimisa- sion problem thatyield s optimum set-point values for relevant process variables and 2) a controlproble m by which these set-point values are followedb y means of a sufficiently fast feedback control system. In so doing we circumvent the very complicated on-line,nonlinear , dynamic optimisation problem.

Theparameter s of theproces s are unknown inpractic e so theyhav e to be estimated. Thisough t tob e done on-line by means of recursive techniques,usin gmodel swit hmor e than twoparameters .Muc hmor e re­ searchwoul d thenb e needed,henc e it isapproximate d by simple one and two-parameter models,estimated afterwards,off-line .Researc h on this aspect is required when control of speed on combine harvesters is developed for use inpractice .

The optimisation of threshing speed and machine speed should be done in mutual dependance. This ishoweve r a very complexmatter ,s o itwa s sim­ plified by adapting the desired threshing speed to the threshing separa­ tion efficiency instead ofmachin e loss. The optimum adjustment of concave,sieve s and fan should alsob e con­ sidered in their dependance on adjusted threshing speed andmachin e speed and vice versa.Thes e aspects could,however ,onl y be considered in this studyb y calculating threshing loss,breakag e loss and sieve losso n the basis of averaged values ofmode l parameters,an d including them in the totalcosts .

The largenumbe r ofpossibl e control systems is limited to five.Tabl e 1.4.3.1 shows thenames ,input s and outputs of these 5systems .

19 Table 1.4.3.1. The investigated control systems WL - walker loss, FS =stra w feed rate, TSE = threshing separation efficiency, VM =machin e speed, VT= threshing speed.

System Input variables Output variables Symbol Name WL FS TSE VM VT 0 manual control 1 loss control x - X 2 loss-feed rate control XX- X 3 loss-feed rate-threshing X x - X X speed control 4 loss-feed rate-threshing separation control

Wewil l lookbac k to these simplifications when the simulation results are known.A discussion about thismatte rwil l be dealtwit h in 6.4.

20 2. System models

2.1. MODEL APPROACH

2.1.1. Introduction

Modelling and simulation in general comprise the activities involved in constructing amode l of a real-world system and simulating ito n a com­ puter. Themode l of the real-world system has tob emad e smaller and simpler than the realworld , as the reality is too complex and toowide , even fora bi g computer.Th epossibl e reductions and simplifications depend on the aim of the research,i nwhic h themode l isuse d to solve a problem.

The following stepshav e tob e taken after formulation of the aim: Theboundar y between the considered system and the environment has tob e formulated, and input/output relations defined. The essential aspects can thenb e selected, and model hypotheses formulated on the basis ofphysica l laws. Iti s desirable tokee p themodel s as simple aspossibl e for the sake of the simulation technique so that thenee d arises to compare the simulated to the experimental results. Depending on the results of these activities,th e same loopha s to be gone over again toge t satisfactory results.

This approach will be demonstrated for ourproble m in thepresen t and following chapters.Th e model description willb e given in twoiterations . The general aspects of the totalmode lwil l be discussed in 2.1.2. The details of the differentiatedprocesses ,th e control models,th e parameter estimation of themodel s and the comparison of the simulation toexperimenta l results will be discussed in the following sections and chapters. In facta first stepha s already been described in chapter 1.

21 2.1.2. General aspects

Aim Theai mo fthi sstud yha sbee ndescribe di nchapte r 1i nterm so f assessmento fth econtributio no fcontro lsystem si ncombin eharvester s toth eminimisatio no fharves tcosts .Thes ecost sca npossibl yreduce d bycontinuou sadaptatio no fth emachin espee dan dthreshin gcylinde r speedt oth ecro pvariables .Fo rthi spurpos econtro lsystems ,tha t includecontinuou scalculatio no fth eoptimu mspeeds ,hav ebee ndesigned . Themachin ean dthreshin gcylinde rwil lreac ta sa dynami csyste mt o inputsignal sfro mth econtro la st ooptimu mspeed .I norde rt od oso , considerationha st ob egive ni nth emode lt o -cos tfactor so fth egrai nharves twit hth ecombin eharvester , - speedo fmachin ean dthreshin gcylinder , -effec to fthes espeed so ncosts , - cropvariables :stra wdensit yan dproces sparameter saffectin glosse s (=costs) ,especiall ywalke rloss ,whic hi sth emai nloss , -dynami cbehaviou ro fth etransmission s formachin espee dan dthreshin g speed, -contro lsystems ,includin gth eoptimisatio ncalculations .

System border Thisstud ywil lb elimite dt othos efactor stha taffec tharves tcost s byalteratio no fmachin ean dthreshin gspeed .Th ecost so fgrai nharvestin g areno tonl ythos eo fth ecombin eharvester .Th estra wlef ti nth efiel d alsoha sa certai nvalu ei nth eNetherland san dwil lgiv eyield san d costs,bot haffecte db yspeed si ncombin eharvesting .Eve nharvestin g othercrop sfo rinstanc esee dpotatoes ,i ssometime si ncompetitio nwit h combineharvesting ,an dthu saffect sth etota lcost san dfinancia lyield s ofa farm .Thes efactors ,however , will not be included inth emodel . Other restrictions introducedi nth emode lar estate dbelow : -th eharves tcondition srefe ronl yt oth eIJsselmeerpolders ; -th einfluenc eo fcompetin gcrop san dcost so fgrai ndryin gca nonl y befoun di nth e4 differen ttimelines slos scurves ; -n oadaptio no ftimelines slos sexpectation sar eencountered ; -cost san dyield so fstra war eno tconsidered ; -on etyp eo fcombin eharveste ri stake nint oconsideration ,tha ti sa

22 machine with threshing cylinder,rotar y separator and strawwalkers ; - the only crop tob e considered iswheat ; - theharves t conditions are varied at 8differen t levels; - the control systems are considered as representing four systems using an increasing number of inputvariable s and for controlled outputs.Th e necessary inputvariable s were assumed tob e available,tha t is measured speed,measure d feed rate,measure d walker loss and measured threshing separation efficiency; - costs of transport of the grain will notb e encountered.

Inputs The followingwil lb e the inputs from the environment to the system: - straw density variations, - variations in the values of crop-property parameters affecting threshing separation efficiency andwalke r separation efficiency, - constantparamete r values are used in the calculation of: rotary separator efficiency, sieve,threshin g andbreakag e loss, process dynamics,suc h as time delays and time constants of first-order transfers and machine and threshing-cylinder transmission dynamics, - levels and nature ofmeasuremen t errors (noise), - choice of the control, - choice of feed rate measurement device, - choice as tous e of the combine harvester, - choice of the timelinesscurve .

Outputs The total costs will be estimated outof : - thespee d of themachine , fromwhic h the machine costs and timeliness losseswil lb e derived, - themachin e losses,tha t is from sieves,threshing ,grai n breakage and walkers. The walker losseswil l be themai n ones, sothe y have tob e calculated most accurately. The other loss componentshav e tob e known to check any unusual circumstances, - thewea r of the V-beltdrivin g the threshing cylinder,becaus e itca n be expected that such wear will increase,owin g to the threshing speed controls, - a check will also have tob e made of themachin e speeds and acceleration.

23 General model hypotheses Important assumptions havebee nmad ewit hregar dt oth efee drates . Onth ebasi so ffiel dtes tan dlaborator ytes tresult sth econclusio n wasreache dtha tth efee drat ewoul dhav et ob e considered ona dry - matterbasi si norde rt oseparat eth eeffec to ffee drat elevel san dmois ­ turecontent .Th emoistur econten twil lb e regarded asa cro pproperty .

Thestra wfee drat ei nth eproces si s not dividedint ofee drate sfo rchaf f andshor tan dlon gpiece so fstraw .Th etota lmas so fstraw ,includin g chaffan dweeds ,ofte nindicate da sm.o.g . (materialothe rtha ngrain) , isuse da sa functiona lvariable .Th estra wfee drat eca nb eexpresse d inkg* s orkg» s *m l. Thelast-mentione duni ti sth efee drat epe r standardwidt ho fthreshin gcylinde ro rwalker so f 1m . Although,mos teffect so fstra wfee drat eo nth eproces sar ecause d byth evolum eo fth estra wi nth emodel,th edr ymatte rmas sflo wwil l beregarde da sth etransfe rfactor .I ti stherefor e assumed thatth erati o betweenmas san dvolum ei sconstan tfo ron ean dth esam efunctiona lelemen t ofth eprocess ,bu tca ndiffe rfro mon eelemen tt oth eother .I fthi s assumptioni sincorrect ,th e deviation will be regarded asa chang ei n acro pproperty ,resultin gi na chang eo fth ecro pparamete rvalu efo r thatelement .

Thegrai nfee drat ei s assumed tob edirectl ydependen to nstra wfee d rate.I twil lb ecalculate dfro mth egrain-to-stra wratio ,whic hi sregar ­ deda sa cro pproperty .

Thevaryin gcro ppropert yinput si nth emode lar ederive dfro mtest smad e invariou sfield so ndifferen tdays .B ycomparin gresult so fmeasurement s oncombine sove rsevera lyear swit hliterature ,a selectio no fdat awa s madet ocreat ea ninput-dat afil etha t can be considered asa goo drepre ­ sentationo fth eharves tcondition stha ta combin eharveste rwil lmee t duringit soperationa llife .

Physical relations used Thephysica lrelation suse di nth emodel sar ever ysimpl ean dmos to f themar eempirical .The yar eshow ni ndetai li nth efollowin gchapters . Thegenera lrelation sconcer nmas san denerg yflows . -Ther ei sn olos so fmas s (strawo rgrain) . -Th eenerg yuse dfo rthreshin gan dacceleratio no fth ethreshin g

24 5

cylinderdepend so nth epowe ravailabl efro mth eengine . -Th ecu tare ai scalculate dfro mth eproduc to fth ewidt ho fth ecutte r baran dth etraverse ddistance ,thi sbein gth eintegra lo fth espee d ofth emachine .Th ewidt hi skep tconstant .

Mathematical simplifications - Dueimportanc eshoul db egive nt oth efac ttha tth ecro pflo wthroug h thecombin eharveste rha sn owidt ho rheight ,s otha ti nspac ei ti s one-dimensional (kg-s ).Thi smean stha ta nuneve ndistributio ni n widthan dheigh twil lb ea nimportan tsourc eo fvariatio ni nfee drat e effect. -Th eeffect so fcrop-propert yparameter so nth eproces stransfer si nth e combineharveste rar ever ycomplex .I ti sver ydifficul tt ofin drela ­ tionstha texplai nal linput-outpu ttransfers .I twa stherefor eneces ­ saryt oreduc eth enumbe ro fcrop-propert yparameter si nth emodels .A s wewil lse ei nth echapter st ocome ,thi s lumped-parameter approach hasle dt ojus ton esteady-stat eparamete rfo reac hsubmode land ,i n additiont osevera ltim edelays ,on efirst-orde rtransfe ri nth esepa ­ rationprocess .Th edelay sar e assumed tob econstant . -Th econtro lsystem sar econsidere da slinea raroun dth eworkin gpoint , thati saroun dth emea nleve lo foperation .N ohysteresi soccur si n themodels . -Rando mprocesse sar eonl yconsidere dt ob eapparen ti nth einpu tvaria ­ ble,tha ti si nth estra wdensit yan di nth emeasurin gdevic enoise . Inth emeasurin gdevic ethe yoccu ra scoloure dnoise .I nth estra wden ­ sitythes erando mprocesse sar epu tint oth emode lb ya deterministi c variationo fth eso-calle dapparen tstra wdensity,calculate dfro mfee d ratesan dspeeds,measure do na machin ei nth efield .Thi sapparen tstra w densityi scalculate dan dstore di ndat afile sfo rinterval so f0.2 5m .

Comparison of simulated to experimental data Thiscompariso nwa sdon eb ysimulatin gpart so fth emodel ,th ecomplet e modelan da previou scontro lsyste man dcomparin gth esimulatio nresult s withfield-experimen tdata .Thi swil lb eshow ni nchapte r6 .

25 2.1.3. Method used in this study

The steps taken to transfer the conceptual model into aphysica l model and then into amathematica l model and finally themathematica l model into the simulation model should be clearly separated so that the sim­ plifications become visible. In the following sections,however ,i t will be shown that inman y cases a deterministic model wasbuilt , allowing the conceptual model tob e translated into amathematica l model in one step,whil e thismode l could be used without adaption in the simulation model. Inmos t cases,therefor e juston e symbol is used for eachparameter .

The assessment of theparamete r values is also given in these sections, because this is included in thewa y the modelwa s built. Inmos t cases the approach has been as follows: Knowledge tobuil d a theoretical model was obtained from literature; sometimes a conceptual model and sometimes aphysica l one. Ifn olitera ­ ture was available,experiment s were carried out.Wit h the results of new experiments,parameter s were estimated and literature was used to verify theresults . Of the experiments and simulations thatwer e compared, one wasperfor ­ med with machine A, so that amode l of thismachin e alsoha d tob edeve ­ loped.

2.2.COS TMODE L

Asexplaine d in chapter 1si xdifferen t cost situations referring to the way the variation of machine speed affects thevariou s cost factors are considered. The cost factors will allb e expressed in fl'ha .The yare : a)Variabl e machine costs proportional to the harvested area (MVC) b)Machin e and labour costs proportional to the working time (HVC) . c)Annua l fixed costs (AFC) . These three together are also called machine costs(CM) . d) Costs ofmachin e losses (CLO). e)Cost s of extrawea r of the threshing cylinder drive (VWC) . f)Cost s of timeliness losses (C2T). The cost factors will be calculated for the 100 ha wheat harvested by the cereal farmer, the 175 ha wheat of the IJsselmeerpolders Development Authority large-scale grain farm and the harvest of roughly 100 ha wheat

26 by thecontracto rpe ryea rpe rmachine .Th ecalculate d values willb e mentioned inthi s order.

2.2.1. Variable costs proportional to the harvested area: MVC fl'ha-1

Costs, such astechnica l wear,maintenance , lubricants, fuelar epropor ­ tionalt oth eharveste d area.Th ecalculatio ni sgive ni nth eappendi x and thecalculate d valuesar e58. —fl'h a l,54. — fl*ha 1, 66.—fl'h a 1.

2.2.2. Variable costs proportional to the working time: HVCfl'ha 1

The only important cost proportional toth eworkin g time isth elabou r cost (WAfl* h '). Inthi s cost factorth ehour sno tworkable , trainingan d overheads havet ob eincluded ,s otha tth erat e ishighe r thanth epayment . Inaddition ,calculatio n ofthi s factorpe rhectar e iscomplicated ,a sno t onlyth eeffectiv e time,bu tals omachin e down time andextr a allowances have tob etake n into consideration. This means thata thighe r capacities the effective time isincline d todecreas e inproportio nt oth eothe r times.

The time elements aregive ni nh'h a andth edefinition s are(Lint , 1974): 1)Effectiv e time= Machin ei scuttin gan dthreshing . 2) Auxiliary time= Action s required inth ecours eo fth ework :dischar ­ gingth egrai n tank, turningth emachin e anddrivin gt oth een do fth e field,extr a time forth ecorner san dth eheadlane so fth efields ,roa d time toothe r fieldsan dtim e allowance forbreakdow no fth emachine . 3) Relaxation allowance =res t allowance forth esu mo fth eeffectiv e time andth eauxiliar y time together. The 3element s mentioned above aretogethe r considered asth ene tworkin g time. The task time (TT) canb epresente d asth ene tworkin g time plus pre­ paration time,roa d time anddisturbanc e allowance.I ti s assumed inthi s study thatth etas k time minus theeffectiv e time,tha ti sth enot-effec ­ tive time (NE) isproportiona l toth eharveste d area.I nthi s assumption, the field size anddistanc e toth efarm ,etc .ar efixed .I n198 2th e NE for wheata tth eIJ.D.A .wa s0.2 7h-h a,' .Fo rcontractor s andgrai n farms iti slowe ran dwa s estimated at0. 2h'h a l thankst oshorte r road time andwaitin g time andth efac t thatth egrai n tanksar edischarge d while the combine ismowin gan dthreshing . 27 Porth ereductio ni nproportio no fth eeffectiv etim et oth etota lworkin g timea correctio nfacto r EFha st ob eintroduced ,dependen to nth eproduc t ofth espee do fth emachin ean dth ecuttin gwidth , VW(m 2,s 1) andth e noteffectiv etim e NE(h'h a l). Theefficienc y factor EFca nb edefine d as „„ effectivetim e_ effectiv etim e .„. . tasktim e effectivetim e+ NE Knowingtha teffectiv etim e= 1/0.36' Wh'h a (thefacto r0.3 6 isfo rth econversio no fm' s 1 toha' h 1) weca nno w define

FF -1/0-36'V W = 1 (22 ) ~1/0.36-V W+ NE NE'VW-0.36 +1

Theare acapacit yo fth emachin ei nha' h theni s

3 6 FT= W.W.0.3 6 =^;° 0-, 3 6+ t •Cha-h- ) (2.3)

Thereforeth ecost spe rhectar ear e

(flh a 2 4 HVC=W = vîFô^é ' ( - ) Thecalculatio nse tou ti nth eappendi xshow stha t WA =40.- -fl-h" 1,20. —fl-h" 1,32.6 0fl-h" 1.

2.2.3. Fixed costs: MFC fl-haT1

The annual fixed costs AFC are depreciation, interest, insurance, housing and, in the case of contractors also include general costs. They were calculated as being 20 387.50; 35 280.— , - 36 350.— fl'yr"1. These costs should be related to the yearly harvested area AA ha«yr '. If this is fixed, then the costs per hectare are constant and yield MFC = AFC/AA.

If the area is variable, then the costs per hectare are not known before the end of the season. In order to calculate the momentaneous costs a correction factor C is introduced, based on the area harvested in a "normal" situation. In this situation we assume that the harvest is AAN ha'yr ', and this can be completed during the effective time by wor­ king at a constant speed of VMN m*s 1 and a header working width of CL m. This case yields AA = C'AAN ha'yr 1 (2.5)

28 If we assume that the available yearly working time is TYT h'yr then AA and AAN are each equal to TYT-PT. As VMi s the actual machine speed m*s , and VW = VM'CL m2's-1 (2.6) tfc r = ^ TYT'VW'0.36'EF{W) n S5Î7 2T2'«l'MV'CZ>0.36'£,F(l'MV) l2 } Together with the definition (2.2) of EF, this becomes

„ = VW(NE-VMN-CL-0.36 + 1) (2 8) VMN'CL(NE'VW-0.36 + 1) The fixed costs are then

Mvr = ^ = AFC.VMN-CL (NE-VW-0.36 + 1) -i (2 9) AA AAN VW '[NE-VMN'CL-O.36 + 1) For the IJ.D.A. we then have AAN = 175 ha and VMN is 0.9 m-s '. For the farmer and contractor we have AAN = 100 ha and VMN is 1.0 m«s l.

2.2.4. Costs of machine losses: CLO fl-hcT1

The grain losses are calculated by the model in kg«s ' as worked out in the next sections. It should be noted that there are four types of losses: sieve loss, threshing loss, walker loss and breakage loss. The financial value of the lost crop, V\, due to the first three kinds of loss is taken as the market price minus transport and drying costs. In the appendix they are calculated in case of the IJ.D.A. to be 0.505 fl'kg"1 and in that of the farmer and contractor 0.534 fl#kg *. The broken grain depreciation Vz is low. For wheat it is 0.00027 fl*kg_1 for every 0.1% broken grain above 4%, so that the cost of broken grain 1 is VBL = F2'BI>1000'(BLF-0.04) fl's" if BLF > 0.04 (2.10a) VBL =0.0 if BLF < 0:04 (2.10b)

The sum of the financial value of the machine loss is therefore VML = Vi(WL+SL+TL)+VBL fl-s"1 (2.11) These loss costs only incur when the machine is harvesting and then they amount to CLO= VML'10.000/VM fl«ha_1 (2.12)

29 2.2.5. Costs of the extra wearof the threshing cylinder drive: VWCfl'ha 1

Inth ecas etha ta threshin gcylinde rspee dcontro li sused ,intensiv e accelerationan ddeceleratio nincrease sth eV-bel twear .I ncomparin gcost s ofcontro lsystem sthes ecost sma yno tb eneglected .Thi swea ri s assumed tob eproportiona lt oth eV-bel ttensio n FOBabov ea certai nminimu mleve l FOMtha ti s (FOB-FOM) N,whic hca nb ecalculate di nth emodel . _1 1 Ifth evalu e V3(i nfl'N s )i sknown ,the nth ecost si nfl-h a' ar e

1 VWC= V3'{FOB-FOM)'10000/VW fl'ha" (2.13) 6 _1 -1 V3= 1.0-10~ fl'N -s and FOM= 125 0N

Itshoul db enote dher etha tth eextr awea ro fth emachin espee dcontro l isno tcalculated , assuming thatth ecost sar erelativel ysmall .

2.2.6. Costs of the timeliness losses CTIfl'ha l

Thesear eth ecos to fshatte rlos scause db ywin dan dprecipitation ,wil d life,sproutin gan ddr ymatte rdecreas eprio rt omowing ,counte dfro m harvestingripenes san dincludin gheade rlos si nmowing .I nth eNetherland s theaverag etim eo fharves tripenes so fwinte rwhea ti saroun dAugus t15t h (Fokkens,1983 ). Thes elosse soccu rabou t1 5day safte rthi stim ean d increasemor etha nlinearly . Thetim ewhe na certai nare ao fcro pca nb eharveste ddepend so nth e numbero fworkabl ehour si nth epreviou sday san dth eworkin grat edurin g thesehours .Moreover ,th ecro pwil lb e considered aslos ti fi tha sno tbee n harvestedbefor ea certai ndat ei naccordanc ewit hth eIJ.D.A .harvestin g model.W eassume thisdat et ob eOctobe r 1st.Thi si sa theoretica lris k becausei npractic eextr amachine sar ehire dwhe nharves ti sdelaye dtha t much.Stil lthi sgive sextr acosts .Base do ndat afro mth eIJ.D.A . for winterwheat ,a relatio nfo rtimelines slosse sha sbee nderive dan di s giveni nfigur e2.2.6. 1 (fordetail sse eappendix) . Basedo nthi srelatio nan dth edat ao nth eworkabl ehour sfo rth ecerea l harvesti nth eNetherlands ,th etota ltimelines slosse swer ecalculate d fora rang eo fmachin espeed san ddifferen t assumptions. The assumptions concernth esiz eo fth eare atha tha st ob eharveste d (100h afo rth egrai n farman d17 5h afo rth e IJ.D.A.),th ecerea lmoistur econtent sa tth etim e ofharves t( <23 %fo rth efar man d< 28 %fo rIJ.D.A. )an dth euncertaint y

30 Figure2.2.6.1 .Th efractio no fth egrai nyiel d {THF)los twhe n harvesteda tth eindicate dnumbe ro fday safte rdat eo f"combin e ripeness" (aboutAugus t15th ) ofworkabl ehour savailabilit ydu et oth eweather .Fo rth elast-named , calledth eweathe rrisk ,w etoo kth epercentag eo fyear si nwhic hth enumbe ro f workablehours,use di nou rcalculations,wa sno tavailabl ei nth eperio d untilOctobe r lst,duet ounfavourabl eweathe r (25%o r 162/3% ) (seeappendix) . Thisalread yshow stha tth etimelines slos scurve stha taris ei nthi sway , andar eshow ni nfig .1.4.1.3 ,strongl ydepend so nth econdition sand , inou rcase ,o nth e assumptions.

2.3.PROCES SMODE L

Thecombine-harveste rproces si sspli tu pint oelement sa sshow ni nfigur e 2.3.1.Th esubmodel sreferrin gt owalke rlos swer eworke dou ti nmor e detail thanth eothe rsubmodels .The yar edeal twit hi nth enex tsections . Thedesire dspee do fth emachin ean dth ethreshin gcylinde rca nb e adjustedb yth ecombin eharveste roperato r (=manua lcontrol )o rb yon e ofth econtro lsystem s (=automati ccontrol) .

2.3.1. Header and conveyer

Thecro pi scu tb yth ecutte rba ri nth eheade ran di sthe npushe db y thenex tcu tan dth eree lt oth eauger .Th eauge rtransport si tlaterall y towardsth ecentr e (seefig .A 1.1.1 andA 1.1.2).A tth ecentr eo fth e augerther ear eretractin gfinger stha ttranspor tth ecro pt oth econ -

31 straw density on the field «machine speed i threshing VT cylinder mowing speed actual cutting width strawfee drat e

transport ^processan d redistribution anddelay s ^machineparameter s parameters ^j threshing MaP -^relate dt o cylinder flowo i feedrat e straw fraction (- Igraint ostra wrati o m.o.g.) jnseparated grain flowo fgrai n

delayo f delayo f threshing threshing

flowo fgrai na t Jrotaryseparato r

rotary separator

delayo f delayfo r delay / delay rotary seedlosse s ofr. s separator

_f\ _ '^ damaged grain redistributio n onstra w walkers straw T walkers

delay M P yok. 11 delaya t delaya t straw sieve straw threshing walkers loss walkers loss

flowo fstra w sieve walker threshint g breakage ssni leavingmachin e loss loss loss loss

Figure 2.3.1. Flow chart of the combine harvester process for loss calculation

32 veyor.Th econveyo ro relevato rchai ntransport sth ecro pt oth ethreshin g cylinderi na continuou slayer .

Thecuttin gi sdon eove rth ewidt ho fth ecutte rba r CLm ,define db yth e distancebetwee nth ecro pdivider sa tbot hside so fth eheader .Th e combineharveste rha sa certai nspee d VMnr s ,a twhic hspee dcuttin g isdone .I fi nfron to fth ecutte rba rth eaverag eamoun to fstra wi na stretchi sSo 'kg* m2 the nth eamoun to fstra wcu tpe rtim eunit ,th e strawfee drat ean dth ecutte rba r FSCkg* s 1wil lbe . FSC= SD-VM-CL kg-s"1 (2.14) Iti s assumed inthi smathematica lrelatio ntha tn omateria li slost ,tha t meansth emateria lno tgathere dwa sno tharvestable .

Intransportatio no fth estra wt oth eauge r (andfurther )n omateria li s losteither .Onl ya dela yoccurs .Base do na naverag emachin espee do f 1m* s l andth edimension so fth eheader ,thes edelay sar ecalculate d as0. 3s fo rmachin eA an d0. 4s fo rmachin eB (seeA 2.3.1) .Th etrans ­ portationo fth estra wb ymean so fth eauge ri sa complicate dproces s becausether eha st ob ea certai namoun to fstra waccumulate dbefor ei t ismoved .Moreover ,th ecro pi scollecte dcontinuousl yove rth eful lwidt h ofth eauge ran dadde dt oth esideways-movin gmass . Atfirs tthi sproces swa sdescribe db ya first-orde rtransfe rbase do n atheoretica lste pfunction .Thi stheor yi sworke dou ti nA 2.3.1 .However , theide aha sbee nrejected ,becaus ei nsuc htransfe rth ehigh-frequenc y variationsi nth estra wfee drat ewoul db esuppressed ,whic hthe yar e notwhe nth eproces si scontinuous .Th ehigh-frequenc yvariation swil l remainpresen t (see4.2 ) sincethe yca nb eintroduce db yth eauge ra s therei ssom emas sredistributio ncause db yaccumulatio nan dther ear e alsolatera lstraw-densit yvariation si nth estrip .Thes evariation sreac h theelevato ri nth ewa yexplaine dbelow . Schematicallyth ecro pfee drat eca nb espli tu pint othre eflows : vseefigur e2.3.1.1 )C move sstraigh tahead ;A + B ar eadde dt oC ,bu tcom e later.Th evariou scro pmas sflow sar ejoine dan dtake nove rb yth eele ­ vatorchai na tD .Th evariation si ncro pdensit yar earrive da tsimilarly .

Thesimulatio nmode lwa sdefine db yth econditio ntha tsimulatio no feac h controlsyste mmus ttak eplac eunde rconstan tcondition swit hregar dt o thedisturbance si nth eprocess . 33 Variationi nfee drat ei ssuc ha disturbanc ean dbecome simportan t onlya tthreshin gan dseparation .Sinc eth eorigi no fth edisturbance s areth ecro pdensit yvariatio ni nth efield ,th evariatio nwil lb edefine d andrecorde di nterm so fstra wdensit y (kg*mz ). Thetransfe r ofth eheade ran dconveye ronl ywil lb eexpresse db y equation2.1 4an dtim edelays .Al ldeviation sfro mthi sexpressio nar e includedi nth ecalculatio no fth estra wdensit yinpu ti nth esimulation .

Thecalculatio no fthi sstra wdensit yinpu ti sdon eb yusin gth emeasure d signalo fth eauge rtorqu e TA. Thissigna lrelate st oth emas sflo wunde r theretractin gfinger si nth ecentr eo fth eauge rjus tbefor ei treache s D (infig .2.3.1.1 )a swil lb eexplaine di n3.1.1 .Also ,th emachin espee d andcutte rba rwidt har eneede di nth ecalculatio no fth eapparen tstra w density.Th eequatio nca nb ederive dfro m (2.14)an di s SD= TA/(VM-CL) kg-m-2 (2.15) Henceth edisturbance si nth emeasuremen to ffee drat ean dmachin espeed , thevariation si ncuttin gwidt han dcuttin gheigh tdurin gth eexperiments , thevariation si nth eredistributio ni nth eheade rar eal linclude di n thecalculate dvalue so fth eapparen tstra wdensity . Iti sonl yth emeasuremen tdisturbance stha t should not be represented inth ecalculate dvalues ,al lother sma yremain ,a sthe yar edu et oth e processi nth eheade ran dar eth esam efo ral lsimulations .

Thereis ,however ,a complicatio ncause db ya neventua ldifferenc ei n machinespee di nth esimulation san dth eexperiment stha twil lb eexplai ­ nedbelo wwit hth ehel po ffig .2.3.1.1 . Ifw econside ra cro pflo wcarrie dove rt oth e conveyera tD durin g At= 0. 2s the ni tca nb ecalculate dtha tthi scro pmas swa spresen ta s unmowedo nth ehatche dstri pE ,abou t1. 7second sbefore ,i fth ecombin e harvesteri smovin ga ta spee do f1 m" s 1. Henceth ecro pfee drat ea t Dha st ob erelate dt oa stri po fcro proughl yo fshap eE .I fth emachin e speedha dbee n0. 8m- s 1,the nth efee drat ea tD i n ht wouldoriginat e fromstri pF . Inth ecas etha tth emachin espee dvarie si nth esimulation ,th e originalpositio no fth euncu tcro pmus tthu sb ethough ti fa svarying . Whenth eapparen tstra wdensit yvalu ederive dfro mmeasurement swit ha drivingspee do f1. 0m' s1 ,i suse di nsimulation sa ta drivin gspee do f 0.8m* s1 the nthi sstra wdensit yvalu ecorrespond sa sa matte ro ffac t

34 Figure2.3.1.1 .Origi no fcro po nth efiel da smeasure da tD ,i nsitua ­ tionswit hdifferen tmachin espeed s (seetext )

tostri pG i nfigur e2.3.1. 1 (whichi snamel yequa lt oE i nshap ean d area). Thisgive sa specia lcharacte rt oth efee drat evariatio ntha tcanno t beseparate dfro mth eorigina lvariatio no fstra wdensity ,an dwil lthere ­ foreb e neglected. Thisi sallowe dbecaus eth edeviatio ni srelativel y slightan dth ekin do ffee drat evariatio ni sno tchange di nprinciple .

Onthi sassumptio nth etransportatio nproces si sonl ya matte ro ftim e delays.Thes ear ededuce dfro mth edimension si nth emachin ean dth e flowspeed san dar eestablishe db ymeasurement s (seeA 2.3.1) . The conveyerconsist so fa nelevato rcapabl eo fmovin gi nth evertica l directiona tth efront .Sinc ethi smovemen tha sbee nuse dfo rmas sflo w measurementsi twil lreceiv eseparat econsideratio n (see3.1.2) . Consequently themode lo fth eheade ran dth econveye ri sgive nfo r bothmachine sby : Value for Mathematical Para­ machine .Description expression meter A B Strawfee drat ea tth ecutte rba r FSC=SD'CL'VM(kg's" 1) CL (m) 4.5 5.9 Strawfee drat ea tth eauge r FSA=FSC-é ïlS(kg-s l) 11 (s) 0.3 0.4 2S 1 Strawfee drat ea tth eelevato r FSE=FSA'e~~?- {kg-s' ) 12 (s) 0.2 0.3 Strawfee drat ea tth ethreshin g cylinder FST=FSE'e -3S(kg-s ') 13 (s) 0.7 0.6

35 TSE= 1 - exp(-LA-NU'RPS-\VT-VE)BETA) (2.16) inwhic h TSE =Fractio n concave Separationo fth egrai n feedrate . BETA =Threshin gcoefficient .Thi s factoronl ydepend so nth ecro pbein g threshed andamount st obetwee n 1.1an d1.8 . RPS =Th ereciproca lvalu eo fth echarg ecoefficien t (=l/ij )o fCaspers ). This factordepend so nth efee drate . NU =Densificatio n factor.Thi s factor givesa nindicatio no fth edensifica - tiono fth eproduc t inth ethreshin g space.Consequentl y thevalu e ofthi s factordepend so nth econcav e adjustmentan dth estra w feed rate. LA =Concav e length factor.Thi si sth equotien to fth erea l concave lengthan da referenc e concave length (680m mfo rCaspers)(i nou r own case0.9) . VT =Periphera lvelocit yo fth ethreshin g cylinder (threshing speed) m's 1. VE =Velocit y elevatorm* s l i.e.th ecro pintak e speed (inou rcas e 2.6 m's"1),

Since theconcav e length,th econcav e adjustmentan dth eintak e speedar e fixedi nthi s study,th evalu e for LAi scalculate d as0.86 2fo rmachin e Aan d0. 9fo rmachin eB .Fo r NUan d RPSvalue sar ecalculate dwit hrefe ­ rence toth econcav e adjustmentan dth especifi c straw feed rate (=stra w feedrat ei nkg* s drymatte rpe rmetr e concavewidth )(se eA 2.3.2.a ) During simulations thesevalue sca nb eintroduce db ya functio ngenera ­ torwit h linear interpolation and,sinc e theyar ea functio no fth espe ­ cific feed rate,that i sspecifie d fora standar d widtho f1 m , theyar e valid formachin eA a swel la smachin eB . Separationi sthu sdependen to nth efee d rate,th ethreshin g speed, the threshingcoefficien tan dth echose n concave adjustment.I nfigur e 2.3.2.1a nexampl ei sgive no fthi s relationship forth evalue so fvariables : BETA =1.7 , theconcav e adjustmento f8/4 ,whic hmean sa spac e between threshingba ran dconcav eo f8 m ma tth efron tsid ean d4 m ma tth erear ,an d NUan d RPSfo rsprin g wheat. Thisrelatio ni sals oclos e toth eresult s obtainedb yothe rresearchers , forinstanc e Arnold (1964),Coope r (1971)an dEime r (1977)an dth epresen t writer'sow nlaborator y research (seeA 2.3.2.b).I nth emode l that Pickering

38 3 4 5 AFST kg.s-Vm-1

Figure2.3.2.1 .Relatio nbetwee nthreshin gseparatio n efficiency {TSE) andspecifi cstra wfee drat e (AFST) fordifferen tlevel so fthreshin g cylinderspee d (VT)accordin gt oth emode lo fCasper sfo r BETA= 1.7 andconcav eadjustmen t8/ 4mm/m m

(1974)use di nsimulations ,th econcav eseparatio ni ssuggeste dt ob eli ­ nearlydependen to nth estra wan dgrai nfee drate .Th epresen twriter' s ownfiel dresearc hshow sthi st ob ea goo destimat ei ncas ether ei sa slightvariatio ni nfee drat e(se eA 2.3.2.c) .Fo rsuc ha smal lrang eo f feedrat eth emode lo fCasper sshow sals oa nalmos tlinea rrelation ,s o therei sn orea ldifferenc ebetwee nthes emodels .A dependenc eo nth e threshingcylinde rspee di sno tindicate di nth emode lo fPickering ,s o themode lo fCasper swa spreferred .

From thepresen tresearc h(se eA 2.3.2.d )i tha sbee nestablishe dtha t theseparatio ndoesn' tdepen do nth efrequencie si nfee drat evariation s inth eresearche dbandwidt hlowe rthe n1 2rad* s' .I ti s assumed therefore thatever y feedrat evariatio ntha toccur si nth esimulatio nwil lhav e effecti naccordanc ewit hth eindicate drelationshi pbetwee nstra wfee drat e andconcav eseparation .I nth emode lo fPickerin gthi si sth ecase ,too . Inth estra wdensit yinpu tonl yfrequencie slowe rtha nabou t6 rad* s exist,s otha tvariation sabov ethi sleve lar ei nfac t assumed tohav en o impact.Th ethreshin gseparatio nfractio n (TSE) hast ob emultiplie db y thegrai nfee drat ea tth ethreshin gcylinde r (FGT)t ocalculat eth e amounto fseparate d graini nkg' s -Thi sgrai nfee drat ei scalculate d

39 from the straw feed rate FS on multiplication by the grain-to-straw ratio (GS). This simplification is permitted as the variation within one field is slight and the value will differ for each field just as other crop properties do. See also appendix 4.2.1.

Threshing loss

The threshing loss depends on the threshing cylinder speed, the concave adjustment, the intake speed and the feed rate level. Caspers didn't make a model of it, he only presented some measurement results. Based on these results and those of Eimer (1977) a simplified model has been derived using the non-concave separation of the model of Caspers. The fraction of threshing loss of grain feed: TLF = (1-TSE)'0.025 that holds for a concave adjustment of 8/4. The use of this simple model is justified be­ cause the contribution to the total losses is slight. In this way the threshing loss becomes TL = TLF'FGT kg»s-1 (2.17)

Breakage loss

Thebreakag eo fgrai nstrongl ydepend so nth ecro pvariety ,moistur econ ­ tentan dth edru mspeed .Especiall ydr ygrai ni svulnerable ,whil eth e influenceo fth econcav eadjustmen ti ssmall .I nfigur e2.3.2. 2som edat a areplotte d fromtest swit hwhea tcarrie dou tb yArnol d (1964),Casper s (1966,1973 )an dKolgano v (1956).Th etest sdon eb yArnol dshowe dtha t thewhea tvariet yCapell aDespre zi sparticularl ysensitiv et ograi n damage.Al lothe robservation sar ebelo w2% .Kin g(1960 )publishe ddat a fromNe wZealan dwher evisibl edamag epercentage su pt o28 %a t VT=2Q m-s l and 14%grai nmoistur econten twer emeasured . Inth efiel di nWester nEurop eth edamag epercentage sar efoun dt ob e quitelower .Fo rnorma lstra wfee drate so f1. 7an d2. 4kg' s ,fiel d measurements (VanOosten ,1970 )showe ddamag epercentage so f 1.0an d1.1 % at VT=2 5 m-s"1.Severa ltes treport sb y IMAGan dDL G (Anonymus,1976 , 1967)generall ypresen tver ylo wdamag epercentages ,sometime swit ha n upwardspea kcause db yspecia lconditions .Fro minformatio no fth eDutc h cerealtrad ei tappear stha tdamag epercentage shighe rtha n1 %ar erarel y encounteredi nth eNetherland s (Schrier,1982 ).

40 Figure2.3.2.2 ^Grai nbreakag e% (PBL)relate dto_threshin gcylinde r speed (VT)m' s l. Datafro mArnol d (1964),2 kg' s 1, winterwheat : CapelleDesprez : * MCG= 15%,A MCG=19% , n MCG= 30% ,Kog a2 : • MCG= 14% ;Dat aKolgano v (1956),£ winterwheat ;Dat aCasper s(1966 , 1973),3 kg* s :0-wintel rwheat ,• sprin gwheat ; Model PBL= 0.001' (VT)Z and 0.005-(VT):

Theinfluenc eo fth estra wfee drat eo ngrai ndamag eis ,accordin gt o Wieneke (1964),sligh tan dslowl ydecreasin gwit hrisin gfee drate . Eimer (1977)present sa figur ewit hline sshowin ga minimu mamoun to f damagedgrai na t+ 3 kg* s ,bu tth emeasuremen tpoint sgiv ejus ta sman y reasonsfo rconcludin gtha tther ei sn odependence .

Howevera sth equantit yo fdamage dgrai ni sa nimportan tcriterio nfo r selectiono fth ethreshin gcylinde rspeed ,i ti simportan tt oappl ysuc h arelatio ni nth esimulatio nmodel .

41 Onth ebasi so fth eabov e mentioned data, only a relationwit hth e threshing cylinder speedi sconsidered ,namel yth efractio no fdamage d grain BLF - 1*10~5•(VT) 2, fora normal ,favourabl e situationan dfiv e timesa smuc hi na nunfavourabl e situation.Thes e relations areshow ni n fig. 2.3.2.2.Thu s theamoun to fgrai nbreakag e lossi s BL= BLF'FGTkg-s" 1 (2.18)

Separation of small straw parts by the eoneave

Though iti sknow n thata highe r threshing intensity (higher VT, alowe r cylinder-to-concave distanceo ra lowe r straw feed rate), induces the se­ parationo fa highe r percentage ofsmal l strawparts ,thi swil l not be taken into considération byth emode la s 1)th eeffec ti s relatively smallan dha slittl eimpac to nth elosses ; 2)i twa s assumed thatth eeffect so nwalke r lossesan dsiev e losses compensateon eanother .

Straw breakage

Athighe r threshing intensityth estra wi sbeate n harderan dspli tan d brokent oa greate r extent.Thi sca ncaus e arais ei nwalke r loss.A s there weren oexperimenta l datao nthi s effect available,an dth eeffec t was thought tob esmal l underDutc h conditions,n omode lo fthi s factor wasmade .

Delay in straw and grain flow

Because ofth elengt ho fth econcav e (0.63m )an dth espee d ofth ecro p flowwhich ,accordin g toGasparett o (1977)i s7-1 1m's" 1 witha naverag e valueo f9 m* s ,a dela yo fth estra wan dgrai nconveyanc eo fapproxi ­ mately 0.1s ha st ob etake n into consideration.Thi s includesth eslowin g downb yth ecylinde r beater.

2.3.3. Rotary separator

The tasko f therotar y separator differs from thato fth ethreshin gcy ­ linder.I tseparate s anddoe sno tthresh .Fo rtha t reasonth eseparatio n

42 characteristicdiffers ,too .Figur e2.3.3. 1show sth emeasuremen tpoint s oflaborator ytest swit hstore dwinte rwhea tan drye .Thi sfigur eshow s thatth efractio ngrai nseparate da tth erotar yseparato r {RSE)decrease s fairlylinearl ywit hstra wfee drat ea tth eseparato r {FSR) andtha tth e slopei sth esam efo rth edifferen tcrops .Durin gharvesting ,th e crop isusuall ywette rtha ni nth elaborator yan dthu sseparatio ni sreduced , sotha tth elin edraw ni nth efigur e was found to be more realistic for oursimulation .Th emathematica lmode luse di nou rsimulatio nwil lb e therefore RSE = CRL - 0.05-FSR (2.19) CRLwil lvar ydependin go ncro pproperties .I nou rcase ,wher eonl ywhea t isconsidered , CRLwil lb e0.6 . Thedela ya tth erotar yseparato ri s estimated tob e0. 1s .

RSE

0.60

0.55

0.50 -

0.45

0.40

.* 0.35 r. 0 1 6 7 8 FSRkg.s- i

Figure 2.3.3.1. Relation between rotary separator efficiency {RSE)an d straw feed atseparato r {FSR) x,#,0 different trials with winter wheat Û,",D different trials withry e ( )Model : RSE =0. 6- 0.05-FSR

43 2.3.4. Straw walkers

Steady state model

Themateria lleavin gth ethreshin gcylinde ro rth erotar yseparato ra ta speed ofabou t1 0m* s* i sslowe ddow nb ya baffl ecurtai nt oa spee do f almostzero .Thi scurtai ni sfixe dabov eth ewalker s0.6 1 mfro mth efron t walkersfo rmachin eA an d0.6 5m fo rmachin eB .Th eproces so fseparatio n beforean dbehin dth ecurtai ni sdifferen ti nprinciple . Fromlaborator yresearc h (seeA 2.3.4.a )i twa sfoun dtha tth eseparatio n beforeth ecurtai ni sapproximatel ylinearl yproportiona lt oth econcav e separationi nth ethreshin gcylinder .I nth emode lthi sseparatio ni s thought to be included inth ethreshin gseparatio no rrotar yseparation . Justth eseparatio nbehin dth ecurtai nwil lb econsidere dt ob ewalke r separation,s otha tth eactiv ewalke rlengt hi s2.7 5m an d2.6 5m fo r machinesA an dB ,respectively .Th espee do fth emixtur eo fstra wan d grainbehin dth ecurtai nwil lincreas et oapproximatel y0. 5m" s However,th espee dwil lvar ya swil lth etim ei nwhic hth estra wi s accumulatedi nfron to fan dunde rth ecurtain . Theseparatio no fth egrai nan dth estra wi sactivate db ytossin g upth ematerial ,thu sincreasin gth edistanc ebetwee nth estra wparts , sotha tth egrai nca nfal lfurthe rdow nwhe nth estra wi stosse du p againb yth ewalkers . Thedensit yo fth emateria lca nals ob edecrease db yhavin gside - by-sidewalke rpart stha tcarr you tphase-shifte dmovements ,b ymountin g walkerstep san dsawtoot hcams ,o rb ymountin gmovin gpart sabov eth e walkers. Fromresearc hb yBaade r (1969),Sonnenber g (1970),Ree d (1972)an d Souter (1967)th eoptima lfrequencie san damplitude sfo rth emovemen to f thewalker sca nb ededuced .I nou rmachine sA an dB thes eitem sar efixe d atpracticall y theoptimu mlevels .

Forou rmode lw enee dth erelationshi pbetwee nseparatio nefficienc yan d feedrat ea swel la sth eimpac to fcro pproperties .Fo rthi sa separatio n model (givenbelow )wa sstudie da suse db yFilato v (1967),Ree d (1970)an d Glaser (1976): G= G exp(-WE'x) inwhic h (2.20) w o

44 G =quantit yo fgrai ni nth estra wpassin gth ewalker sa t x (kg-s1 «m '); G =quantit yo fgrai ni nth estra wpassin gth ewalker sa tth estar to f theseparatio nproces s (kg»s ''m"1); WE= separatio nfacto rcalle dwalke refficienc ym 1 x =distanc efro mth ebeginnin go fth eseparatio nproces sm Thisequatio ni sth esolutio no fa first-orde rdifferentia lequatio n

dGJdx = - WE'GW (2.21) Inthi sequatio ni ti s assumed thatth estra wlaye ro nth ewalker si s homogeneousan ddoesn' tchang ewhil eo nth ewalkers ,an dtha tth egrai ni s homogeneouslydistribute di nth estra wlayer ,causin gth eseparatio nt ob e proportionalt oth egrai nconten to fth egrain/stra wmixture . Thegrai nconten tjus tmentione dha sth edimensio nkg' s1, m ',becaus e thegrain/stra wmas smove sbackwar da ta give nspeed .I fth emas stranspor t isrecalculate d forth especifi cwidt ho f 1m ,th edimensio nbecome skg ,s-1-m~: Thoughthes eassumption scanno tb ecompletel y justified,th eresul t canb euse dfo rou rpurpos e (seeappendi x b). Theproces si ss ocomple x thatth edisturbance si nth eproces sdu et ounknow nvariable scanno tb e distinguishedfro mincorrec tassumptions .I nth enex tparagrap hth eeffec t ofstra wfee drat eo nstra wseparatio nwil lb eworke dout .Al lothe r variablesar elumpe dtogethe ri non eparamete r WEP.I nthi sparamete r theeffect so fa larg enumbe ro fcro ppropertie san dharves tcondition s areincluded ,th emos timportan to fwhic hare : -Th ecro ppropertie stha tca nb emeasure di nterm so fphysica lproper ­ tieslike :elasticity ;friction ;dimension sbefor ethreshin gan dafte r threshing,whe nbreakag ean dsplittin goccurs ;th erati oo fleave san d chafft olonge rpiece so fstraw ;moistur econten to fstra wo rgrain . Thesepropertie sar edefine db yth ekin do fcrop ,variety ,growin gcon ­ ditions,stat eo fripeness ,cuttin gheight ,diseas ean dweathe rcondi ­ tions. -Amoun to fweed si nth eharveste dcrop . -Machin eadjustments . Eacho fth ementione dfactor sca nvar yan dinfluence sth ewalke rseparatio n ina wa ywhic hi sno talway spredictabl ewhil ether ear esevera linter ­ actionsbetwee nthes evariable sthemselve san dwit hstra wfee drate .

Thevalu eo f WEdepend so nth equantit yo fstra wi nwhic hth egrai ni s embeddedan dth ecro ppropertie si na wa ytha ti smodelle db y WE = WEP/AFSW (2.22) 45 Inthi sfor m AFSWi sth estra wfee drat epe rm widt ho fth ewalker san d WEPth elumpe dparameter . Thevalu eo f WEPvarie si ngenera lbetwee n 1an d4 (seeappendi xb) . Theinfluenc eo fdesig nparameter si slef tou to fconsideratio na sth e parametersar econstan there .Figur e2.3.4. 1show sho wsom edat afro m fieldan dlaborator ymeasurement srelat et othi sequation .Th escatte ro f measuringpoint sca nb edu et omeasurin gfault sbu tals ot oth elumpe d parametermodel .

2 3 AFSW kg.s-1.m-1

Figure2.3.4.1 .Walke refficienc yrelate dt ostra wfee drat efo rmachin e A (LW= 2.75) :X = whea t1976 ,• = oat s1975 ,0 = sprin gwhea t1975 , D= winterwheat ,laborator ytest s1973 . .. : WE= 4.S/AFSW; WE= 2.5/AFSW; — - : WE= —^

Pickering (1974),too ,originall yapplie dthi styp eo fmodel ,bu twit h theexceptio ntha th edidn' tus eth efee drat eo fm.o.g. ,bu tonl yth e feedrat eo fth elonge rstra wpieces .However ,becaus em.o.g .wa sspli t upint ostra wan dchaf fa ta fixe dratio ,a nadaptio no f WEPwoul dhav e hadth esam eresult . Aftercompariso no fon efee drate-to-los scurv ewit hfiel dmeasure ­ ments,Pickerin gchange dth emode lint o G( 1- expi-WE-AFSW) ') (2.23) Inou rmode lthi sadaptio nwouldn' tb enecessary ,becaus e G increases exponentiallywit hth estra wfee drat ean dno tlinearl ya si nPickering' s model,s otha tth efirs tmode lwil lb emaintained .

46 Dynamic model

Asmentione dearlier ,th espee do fth egrai nan dstra wmixtur ei sslowe d downb yth ecurtain .A sa matte ro ffact ,a thi nlaye ro fstra wi strans ­ formedher ea thig hspee dt oa slow-movin gthick ,dens estra wlayer .I n thiswa yth emateria li sredistribute ddependin go nit sspeed ,th estra w feedrat ean dth epropertie so fth estraw . Therotationa lmovement so fth ewalke rpart sresul ti na movemen to f thestra wt oth erear .Th espee do fth estra wwil ldepen do nth econtac t ofth ewalker swit hth estra wwhic hi ntur ndepend so nth emas san d coherenceo fth estraw .O nth ewalkers ,too ,ther ei sa redistributio n ofmateria lwhe nth efee drat evaries . Froma physica lpoin to fvie w it can be •perceived thathighl yfrequen t variationsi nth ethroughpu tove rth ewalker sar ereduce db yaveraging , whilelow-frequen tvariation sremain .Thi s can be described bya first - orderproces si nfee drat etransfe rgivin g FSWA = FSR'( 1+ T-s f (2.24)

Pickering (1974)als oapplie da first-orde rproces sinitiall ywit h t= 2.0 ,bu tlate ro nuse dX=1.0 . Iti sdifficul tt oascertai nwhic hvalu eshoul db etaken .Tha ti sals o thereaso nwh ya possibl ymor eaccurat emode ldoesn' tmak esense .Fro m fieldobservatio no fste pfunction s (seefigur e2.3.4. 2an dA 2.3.4.c )an d

Walkerlos sg d.m./0. 2s WL max

3.0-

0.63 * WL max 2.0

1.0

Figure2.3.4.2 .Respons eo fwalke r losst oa ste pi nfee drate ,givin g anindicatio no fth etim econstan t (TAUW) inth efirs torde rtransfe r atth ewalkers .

47 laboratorytests ,th emos tacceptabl evalu eo fT _ha sbee nascertaine dt o be0.8 .Th edelay ,cause db yth etranspor to fth estra wfro mcurtai nt o theen do fth ewalkers ,i scalculate dt ob e8. 2s (seeA 2.3.4.d) .I nth e fieldthi sdela yvarie sa grea tdeal ,du eapparentl yt oaccumulatio na t thecurtain .

2.3.5. Sieve loss

Incalculatin gth etota lcost sth esiev elosse swil lals ob etake nint o consideration.Th esiev elos smode li sno tworke dou textensively .Thes e lossesar elo wi ngenera lunde rDutc hharves tcondition san di nrelatio n towalke rlosses .Jus tth erelatio nt ostra wfee drat ewil lb eworke dou t asthi si sth emai nfactor . Theinfluenc eo fth ethreshin gcylinde rspee do nsiev elosse s will be neglected. Ahighe rthreshing-cylinde rspee dwil lgiv ea highe rsepara ­ tiono fstra wthroug hth econcav egrat ean dinfluence sth esiev elosse snega ­ tivelyi ngeneral .However ,i nthi scas eth ewalke rlos si sinfluence d positivelyowin gt oth ereduce damoun to fstra wo nth ewalkers .I ti s assumed inthi sstud ytha tth etw oeffect scompensat eon eanother .

Thenumbe ro ffactor sinfluencin gth eleve lo fth esiev elos si slarg e: typeo fstraw ,stra wfee drate ,moistur econten to fth estraw ,amoun t ofweeds ,ripenes so fth estraw ,etc .a si n2.3.4 .I naddition ,th e adjustmento fth esieve s (theopenin gan dth eairflow) ,i sals over y important,bu tonl yth estra wfee drat ewil lb euse da sa variable .Th e reasonfo rthi si stha tth eothe rfactor sar eeithe rbeyon dth einfluenc e ofth eoperato ro rfull ycontrolle db yhi m (forinstanc emachin eadjust ­ ments), whil eth eobjec to fth epresen tresearc hi sth estra wfee drat e asa resul to fth emachin espeed .

Themode lfo rth esiev elos swil lb ederive dfro mfiel dexperiments . Infigur e2.3.5. 1fiel dmeasurement swit hmachin eA durin gth eyear s 1969.. .197 2ar eshown .Th estretche swer eabou t2 5m i nlengt hi nthos e tests.Th eextrem e valuesar eals opresente di ntabl e2.3.5. 1t omak e comparisonswit hth ewalke rlosse spossibl e (VanOosten ,1970 ;Klei n Hesselink,1971 ;Loorbach ,1972 ;Wevers ,1972) .Dat ao fmeasurement swit h machineB o ngrai nfarm si n 1980ar eals opresente d (VanDongen ,1981) . Hereth elengt ho fth estretche swa s 10m .Th eaverage so fmeasurement s

48 SL % 0.8

0.6-

0.4

Figure 2.3.5.1. Sieve losses;measure d atmachin eA i nwinte rwhea t field trials: «1969, *1970,X 1971,• 1972;a tfarmers 'machine sB : A198 0 anda tmachin eB o fth eIJsselmeerpolder s DevelopmentAuthorit y from 1977u pt o1982 : • withmachin eB a tth eIJ.D.A .ar eavailabl e fromth eyea r 1977.Th etabl e showsth evariatio n overth eyear san dth etendenc y forsiev e lossest o bemuc h smaller thanwalke rlosses .

Table 2.3.5.1.Losse s measured infiel d tests

Year Specific straw feed rate Walker loss Sieve loss kg •s *l m l % % min mean max min mean max min mean max 1969 1.1 2.6 0.3 5.5 0.08 0.3 1970 1.3 2.2 0.06 2.6 0.13 0.4 1971 1.3 2.8 0.2 5.2 0.02 0.8 1972 1.2 1.7 0.7 9.1 0.3 1.7 1980 0.7 1.9 0.01 3.1 0.005 0.5 1977 1.4 0.07 0.14 1978 2.0 0.30 0.12 1979 1.4 0.23 0.13 1980 1.7 0.10 0.08 1981 1.6 0.08 0.11 1982 1.6 0.10 0.07

The general tendency isindicate db yth elin ei nfigur e 2.3.5.1 andth e formulao fth efractio n sieve losseso fgrai n feed ratewil lb e SLF =0.001'AF S (2.25) Almostth esam e conclusion isreache d inth eliterature .Ther e isa linea r increaseo fth esiev e lossesb y+ _0.1 %pe rkg* s 1'm 'increas e inth e

49 feedrate .Pickering' smode ldoesn' tcontai na siev ean dKir k (1977)doesn' t givean ydetails .I nthi smode lth estra wfee drat eafte rth eredistribu ­ tiono nth ewalker s AFSW will be applied toth estra wfee drate ,becaus e themeasuremen tpoint si nth efigur erefe rt oaverage dfee drate scoverin g alonge rstretc han d AFSWconstitute sa bette rapproac htha n AFS. Furthermor e SL = SLF'FGT. Actually FGTshoul dhav ebee ndiminishe db y WL,bu tthi s is neglected.

2.4.TRANSMISSIO NMODEL S

Ifth edrivin gspee do rth ethreshing-cylinde rspee di scontrolle dauto ­ maticallyth edynami cbehaviou ro fth etransmission swil lhav ea nimpac t onth eactua lspeed ss othes etransmission shav et ob emodelle dfo rth e simulation.

2.4.1. Transmission in machine A

Onmachin eA th edrivin gspee di sadjuste db ya V-bel tvaridrive .Th e rotationalspee do fth eengin eha st oremai nnearl yconstant ,a sth e speedo fth evariou spart so fth emachin eha st ob econstant .Ther ei s aclutc han da gearbo xbehin dth evaridrive .Th evaridriv ei sadjuste d bymean so fa hydrauli ccylinde rwit ha nadjustmen trang eo f11 3mm . Measurementsshowe dtha tth eadjustmen ttim eove rthi srang ei s2. 4s duringth econtinuou smaximu macceleratio no fth emachin e (Werkman, 1972;Naaktgeboren ,1976) .Se eals ofigur e2.4.1.1 .

Ahydrauli ccylinde rca nb emodelle da sa nintegrato rwit hlimite d extremevalues .Th edisplacemen to fth ecylinde ri ntim e dy/dt is proportionalt oth eflo wo foi l (x) intoth ecylinde r dy/dt = k'X m-s"1 (2.31) orafte rLaplac etransformatio n S'y = k'X m's-1 (2.32) sotha t y = k'x/s m (2.33) Thevalu eo f k'X = PFi sgive nb yth edimension so fth ecylinder ,th eoi l flowcharacteristics ,an dth eadjustmen tneede dfo rcorrec tbehaviou r ofth econtrol .

50 Dey/ ttim VM m.s-1 120- 2.4- 100 - 2.2- 80- 2.0-

60- 1.8-

40- 1.6-

20- 1.4-

1.2- j/o>/r 0- 1.0-

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 times

Figure 2.4.1.1. Forward speed {VM)o f machine A at acceleration and deceleration actuated by the displacement of the cylinder of the varidrive (.DayI). Acceleration: oCylinde r displacement, xMeasure d speed Deceleration:• Cylinder displacement,+ Measured speed

In an auger torque feedback control systemwit hwhic h field tests have been carried out,th e adjustmento f the oil flow hasbee n done by means of apulsatin g oil flowwit h avaryin g passing time (Loo, 1977).

In figure 2.4.1.1. the relation of thepositio n of the cylinder to the driving speed is shown.Th e model is a linear equation dynamically approximated by means of a first-order processwit hX 2=0-3- This isbe ­ cause there are inertnesses in the adjustment of the variator in conse­ quence of the acceleration of the mass of the machine and the deformation of the V-belt. The transfer of the gearbox and thewheel s is linear and depends on the gear selected. Thus variation in driving speed arising from slipping wheels and sagging tyres is neglected. In figure 2.4.1.2. the transfers arequantified. ? is the gain of the varidrive.P is the gain of the gearbox.

51 g mV PF î 1stgear :P F= 329*10~ 3mm«mV_ 1-s 3 2ndgear :P F= 145*10~ mm'm V' • s

•«-minimum 0m m LIMITER J»-maximu m 113m m mm P = 192.91-83.46 0.9686rad's^'m m1 v 113 1+T2*S T2 0.3s rad*s 1 angularvelocit ya tminimu mspee d= 83.4 6rad" s 1stgear :P =0.0058 7m'rad _ g . 2ndgear:P 9= 0.0132 7m'ra d 1 | m»ss VU =machin e speed

Fig.2.4.1.2 .Schem eo fth emode lo fth edrivin gspee dtransmissio no f machineA

2.4.2. Transmission in machine B

MachineB i sdrive nb ya hydrauli cdriv edesigne dt owor ka sfollows : theengin edrive sa variabl epump ,whic hgenerate sa noi lflo wtha t drivesa fixe dhydrauli cengin et owhic hth ewheel sar econnecte db y meanso fa gearbox . Thevariabl epum pca nb eadjuste db ytw oserv ocylinder sfro mwhic h thepositio nca nb econtrolle db ya valv econnecte dt oa contro lhandle .

Fora nautomate dcombin eharvester ,bot hth econtro lvalv ean dth econ ­ trolhandl ehav et ob eadapted .Thi sca nb edon ei nman yways .Th esimples t wayi st oreplac eth econtro lvalv eb yon ewhic hpasse sa (maximized)oi l flowproportionall y toth einpu tsignal . Byanalog ywit h2.4. 1 thedisplacemen to fth ecylinde ri smad epropor ­ tionalt oth evalu efo rth evariabl e P/x . inwhic hT .= 1.6 7s ,derive d c —1 —1 froma nassume dmaximu mpisto ndisplacemen to f6 0mm ,whil eth eadjust ­ menttim efro mminimu mt omaximu mdrivin gspeed,"foun dfro mfiel dtests , is1. 0s (thisconcern sth edisplacemen to fth episto nove rth eabove - mentioned6 0m ma tmaximu moi l flow).Afte rall ,th erea lvalu eo f P /T.i sunimportan ts olon ga s /x.ha sa valu etha tmake sth econtro l ci P 'P, 'P chg-i 52 stablean dth eacceleratio ndoe sno texcee dth emaximu mvalu emechanicall y possible.

1stgear :P =60.4mm-(m- s ) 1 l T. 'S 2ndgear: P =25.0mm-(m- s ) -1 x. 1.67 -l minimum 0m m LIMITER •*-maximu m6 0m m

4.3 rad-s ^mm l

1+T2*S T2 = 0.3 s

rad* s 1st qear: P = 0.00465 m-rad g -l 2ndgear :P =0.0112 4m-ra d m'S VM - machinespee d Fig.2.4.2.1 .Schem eo fth emode lo fth edrivin gspee dtransmissio no f machineB

Inorde rt omak eth emode lclea ri ti susefu lt osho wal lit scomponents . Thegai no fth ehydrauli cdrive ,P isgive nth evalu e4. 3becaus eth e maximumnumbe ro frotation spe rminut eo fth ehydrauli cengin e= 246 3rp m 41.05s 258rad- s Sincethi si sth ecas ea tth emaximu m6 0m mpositio no fth ecylinder , itfollow stha t -1 Kh = bTFTU =4. 3 (rad's )mm Thetransfe rbetwee nth episto npositio nan dth eperiphera lspee di s almost linear.Th emaximu mspeed so fth emachin edurin gfiel dmeasurement s were:i n 1stgear : 1.2m-s -1 ->• P =0.0046 5 m's"1(rad" 1's _1) _1 in2n dgear : 2.9m-s " 0.01124m- s J(rad_1-s' )1 Duringth esimulation s2n dgea rvalue swer ealway sused . Inth edynami ctransfe ro fth ehydrauli cdriv ether ei sals oa certai n

53 inertnesswhich ,base do nfiel dmeasurements ,ha sbee n approached bya 1storde rproces si nwhic h T_2 =0.3 .A ninteractio nwit hth eengin eha s beenneglecte dfo rbot hvariator sbecaus eo fth elo wvalu eo fP .A c recapitulationi sgive ni nfigur e2.4.2.1 .

2.4.3. Threshing aytinder varidrive

Theengin ean dth ethreshin gcylinde rar edirectl yconnecte dt oon e anotherb ya V-bel tvariator .Th etransfe rrati oo fth evariato rdeter ­ minesth erotationa lspee da swel la sth etorque .Sinc eth erequire d powera tth ethreshin gcylinde rvarie sbecaus eo ffee drat evariations , theinerti ao fth ethreshin gcylinder ,engin ean dothe rpart so fth e machinehav eals ot ob etake nint oconsideratio na sa dynami ccircuit . Figure2.4.3. 1show sth ecompositio no fth ecircuit .

Engine FixedIV -bel U EZQ Pm, 1m ff transmission hydr. t0" torn cylinder Vari drive transmission . ratio a \ Threshing Tout, El- cylinderPrntjr (pour

Figure2.4.3.1 .Schem eo fengine ,transmissio nan dthreshin gcylinde r Symbols:J = momen to finertia ;P = power , T =torqu eo nshaft , u= angula rvelocit yo fshaft . Subscripts:i n= i nvariator ,ou t= ou tvariator ,m = ou tengin eshaft , t= threshin gcylinder ,n = neede d

Fromth ethreshing-cylinde rsid e (outo fvariator) ,th efollowin gequa ­ tionca nb emade : Powerneede dfo rthreshin g= powe rfro mshaf to fvariato r+ powe rfro m inertiao fthreshin gcylinder . WhenP stand sfo rpower , Tfo rtorque ,J fo rinerti aan du fo rangula r velocityw ehav e P = T'W (2.34) T= J- ^ (2.35)

54 Thenw eca nwrit eth eequatio n

-dlii P_tn = T ou. t out (2.36) -out dt Thesig no fdû ) isnegativ ebecaus epowe rbecome savailabl e (positive) whend wi snegative .

Atth eengin esid e (intovariator )w ehav eth eequation :powe ravailabl e frompowe rshaf t= powe r fromth eengin e+ powe rfro mth einerti ao fth e enginean dth epart so fth emachin econnecte dt oth eengine . Theformul aread sa s

T -dû) (2.37) m -m m -m ma t

Since Tan dü )determin eon eanothe ra tth eengin ea swel la sa tth e threshingcylinder ,ther emus tb eagreemen tabou tthei rcausa ldependence . Forth esimulatio nw emus tchoos ejus ton edirectio no fth ecalculations . Wepreferre dth edirectio na sindicate di nfigur e2.4.3.2 .Henc eu can becalculate dfro m .and fromu ..Equatio n (2.37)i stherefor e T m T ^ out -out rewrittena s dw P — (-S- T ) (2.38) dt m -mw m'

Inth esimulation ,U ) iscalculate db yintegratin gth erigh than dpar t —m ofth eequatio nfro mth evalue so fP / u and T ofth epreviou ssimulatio n m- m m step.I nth esam ewa yequatio n (2.36)i srewritte nt ogiv e du tn +J . out 2\ + T. (2.39) out dt tn in -out isthu scalculate db ydifferentiatio no fw .(se eals ofigur e2.4.3.7 ) T ou^t -out Thefollowin gvalue sar eals oneede di nthi sequation .

Um W/n (üouf Fixed *|Variator '\ Threshing Motor { Transmission Transmission 0.365 ot wJ Cylinder Tin Tout

Figure2.4.3.2 .Directio no fcalculation so frelate dvariable s T= torque ,t o= angula rvelocit y

55 The value of P P is thepowe r available for threshing, forwhic h calculation the follo­ wing assumptions are made:Normall y theengin e is loaded to about 85%o f itsmaximu mpower ,roughl y 30%o fwhic h is used for threshing. The remain­ der of theengin epower ,tha ti s 100-85=15%, is available foraccele ­ ration of the threshing cylinder ifneeded . The maximumpowe r of the engine of machine B is 131kW . Consequently the availablepowe r for threshing is (0.3-0.85+ 0.15)'131= 53kW . However, only thenecessar y amount ofpowe r is delivered in accordance with the power-speed curve (see figure 2.4.3.3). If the engine isno toverloaded , section BC canb e applied. Here B is themaximu mpowe r of 131k W and C is 131-53=78kW .Th e slope of line BC = 18kW*(rad* s 1)-1. Therefore, in themodel ,th e engine capacity depends on the rotational speed. Thus the available power is P =(w -(i ) )*18k W (2.40) m -max -m thati s limited to 52.92k W atd ) =w . 264.20 rad*s l, because top u = 267.14rad' s 1 -max

P kW

15% reserve 12(H 20 kW

100 Threshing 33 kW

80H

60H

40 W 150 200 250 300 U>m rad-s-1

Figure 2.4.3.3. Engine power related to angular velocity of motor shaft

56 -l Ifu> mwer e tobecom e smaller than 264.20 rad*s the available power would decrease like the dotted line of section BA. In themode l this relation is estimated by the drawn line that isgive nb y the equation = 52920 2 Pm 4-(264.20- a )) w (2.41)

The Value of 1^ (momento frotationa linertia ) Thisvalu ewa s unknown,i npar tbecaus e the other drivenmachin e parts have tob e included in the calculations. Bymean s of simulation, values of 1- 16kg» m havebee n researched. The effect is small atvalue s of Jm > 4 k9"m2- Based on the results of figure 2.4.3.4an d simulation tests a choice for1 ^= 6 kg-m2 has been made.A t J = 4kg«m 2 a certain high- frequency variation of 0.2 rad's"1 still occurs and causes extreme oscillations in some simulation tests.Fo r I =5 oscillation s were also registered,bu tneve r for I = 6.

0 L-^ 1 i i - 12 U 16 18 20 22 24 26 28 30 time s AFST kg.m-1-s-

M

;i ' I » I I A M i :• I'll I .-1 \ f! , M I . i ' i 11 1'Ah'1 M i 11 11 , 1 l W 'I 2- 'JV .1 >, i 11 " -J •! \ H V" w V I II « I i i 1-

oLA/ - —i 1 1 1 1 1 1 1 r~ 12 U 16 18 20 22 24 26 28 30 times Figure 2.4.3.4. Rotational speed of engine (OMMO)a s a function of specific straw feed rate atth e threshing cylinder (AFST) fortw o different moments of inertia of motor and machine (J).Uppe r line J= 6 kg'm2 (L= 263 rad-s l) i lower line J = 4kg.m 2 (L= 264 rad.s"1)

57 The value of Tm 0.365'T. and BT'T Thisvalu ei scalculate dfro m T t,s otha tT in T.i n out out m hence T 0.365'RT'T (2.42) m out while RTdepend so nth econtro l (seebelow) . Equation(2.39 )applie st oth ecalculatio no f T butrequire sth evalu e of P for thepurpose .

The value of P J tn Duringfiel dmeasurement si n 1969 (Oosten,1970 )an dlaborator ymeasure ­ ments,bot hwit hwinte rwheat ,th epowe rconsumptio nwa sa sindicate di n figure2.4.3.5 .Throug hth emeasuremen tpoint so f196 9a regressio nlin e hasbee ncalculate da s P^ =269 1+ 6737-F S (r= 0.79 ) (2.43) Thoughth etest srelat et omachin eA ,the yca nals ob eapplie do nmachin e B,becaus eth erequire dpowe ri sno tdependen to nth ewidt ho fth ethreshin g cylinder.Simila rfee drate swil lhav eth esam epowe rdemand sfo rthreshin g witha smal la swel la sa wide rthreshin gcylinder .However ,th ezero-loa d poweri shighe rfo ra wide rthreshin gcylinde r (assume 10%)s otha tth e relationgive nbelo wi suse d 2960 + STil'FST (2.44) tn Ptnk W 30-

20

10

1 3 FS kg.s-'-m-i

Figure2.4.3.5 .Threshin gpowe r (f^)relate dt ostra wfee drat efo r machineA (FS) •= fiel dtest sfo rwinte rwhea t (MCS =10-13% )an dfitte dlin e =2.69 1+ 6.737'FS( r= 0.79 ) forthes etests ;x = laborator ytest s(M7S*15% ) Ptn

58 The value of I. Accordingt oth emanufacture rthi svalu ei s7.8 5kg #m

œ , The value of -out Accordingt oth edat agive nearlie r 0.365'ÄT-w (2.45) -out

The value of u -m Thisi sw a-smcalculated ,

The value of ST Thisvalu ei sdetermine dfro mth epositio no fth evariato rdiscs ,whic h aremechanicall ycontrolle di nexistin gcombin eharvesters .Whe nthi s typeo fcontro li sreplace db ya hydrauli ccylinder ,the nth erelatio n betweenth epositio no fth evariato rdis c (andals oth ecylinde rpositio n DV)an dth etransfe rrati oA T(a swel la sth espee do fth ethreshin g cylinder VT)wil lb ea sindicate di nfigur e2.4.3.6 .Th ederivatio no f thisca nb efoun di nth eappendix .

VT m.s-1 40-

3 DV,4*10-2m

Figure2.4.3.6 .Relatio ndisplacemen tcylinde rvariato r [DV)an dthreshin g cylinderspee d [VT)actuate db yth espee drati oo fth evariato r [RT)

Sinceth evariato radjustmen tdoe sno tresul tdirectl yi na chang eo f speed,becaus eo fth eelasticit yan dinertnes so fth eV-belt ,a transfe r ofa first-orde rproces si nwhic hT = 0. 3s ha sbee nuse dt orepresen t thisi nth esimulation .Fo rthi stransfe ra rati o RT, alinea rrelatio n likewise,coul dhav ebee napplied ,bu tthi side aha sbee nrejecte dsinc e theworkin gdiamete ro fth evariato rha st ob eknow ni nan ycas et ob e ablet oreac twhe nth etensio ni nth eV-bel tget sto ohigh .Thi sca n

59 •O H 0)

G

O» C

-O C cü

O •P •H >ld

0 •P I

O f 3 -<|CQ fk ü

KO 10 U3 z

60 happenwhe nth emas sinerti ao fth eengin ean dth ethreshin gcylinde r counteract,causin gth evariato rt otransfe rmor epowe rtha nth eengin e cangenerate .I nrealit ythi sinduce sslip .I ti s assumed thatthi swil l occurwhe nmor etha n5 5k Wha st ob etransferre da ta threshin gcylinde r speedo f8 0rad' s .I nthi scas eth etensio ni nth eV-bel ti sabou t 3200N . Inth emodel ,th esli pi ssimulate db ya momentar yfixatio no f RTan d isachieve db ystoppin gth eadjustmen ti nth econtrol .T opreven twea ri n realitythi sshoul dals ob ebuil tint oth econtrol .Th edesire d RTi s adjustedb ycontro lo f DV.Althoug hthi si sno tye tfeasible ,th e simplestwa yt od othi si sb ymean so fa hydrauli ccylinde rwit ha dis ­ placemento f4 2mm .Thi sdisplacemen ti sactivate db ya nI-contro la s describedi nchapte r5 .

Thecoheren taction so fengin evariato ran dthreshin gcylinde rar e showni nfigur e2.4.3.7 .

61 3. Measuring systems

In the various controls of thepresen t study it is assumed that the grain and straw feed rate,th e threshing separation efficiency, thewalke r loss and speedso f machine and threshing cylinder canb e reasonably measured. The more accurately the real values of these variables aremeasured , the better theoptimu m values of threshing speed andmachin e speed canb e calculated. In chapter 5thi s will be explained,bu t itha s tob e stated here that,a smos t control systems are feedback systems inou r case,th e delay in the measurement of a variable should be as short aspossible . There will bemeasuremen t noise.Th e disturbances,includin g the sig­ nal-noise ratio of themeasurements ,wil lb e discussed in chapter 4. In this chapter attention will be paid to - thepossibilit y of carrying out the measurement inpractice , - the accuracy of the measurements and - thewa y themeasuremen t devices are modelled.

3.1. FEED PATEMEASUREMEN T DEVICES

In literature severalpossibilitie s arementione d regarding thewa y in whichparameter s related to the feed rate can be measured. Inou r study some of themhav e been researched, too.Th epossibilitie s referred to are given below.

Measurement of arop density in front of the combine harvester Since variation of the crop density ison e of thebigges t disturbances of theprocess ,measuremen t of itwoul db e really beneficial to control con­ siderations. However,th e crop density measurement technology isno tye t available.

63 The power or forces for the cutter bar drive Themeasuremen t couldb e interesting,becaus e itinvolve sn odela y toth e entrance ofth ecro p into themachine . Itwa sexpecte d that thegreate r the croppresente d toth ecutte rbar ,th emor e stemswoul dhav e tob ecut , and thus thegreate r thepowe r thatwoul db eneede d forcutting . Eimer (1966)ha smeasure d thetorqu e required tomov e thecutte rba r and reported onit .I now nresearc h (Huisman,1974 )th e forceshav e been measured inth ero di n fronto fth etiltin g mechanism thatdrive sth e cutterbar . The conclusion reached inbot h researcheswa stha t these signalsar e unsuitable,a s 1)th esignal-nois e ratio isver ylow , 2)th einfluenc e onth esigna lo f factorsno tdirectl y related toth e feed rate,.sucha sth eamoun to fweeds ,wear ,greasin g and cutting heighti sjus ta shig ha sth einfluenc e ofth estra w feed rateo n thesignal .

The feed auger Depending onth econstructio n ofth efee d auger inth eheader ,on eo r othero fth efee d rateparameter s canb emeasured . Itca nb eth edisplace ­ mentwhe n thefee d auger ismounte d in such awa y that itca nmov eu p and down,makin g thevertica lpositio n ofth eauge r dependento nth e feed rate.Th edrivin gpowe ro r torque dependso nth efee d rate aswell . The relationship between feed ratean dauge r torque islinea r when thebea ­ ringsar eno tmovabl y fixed toth eheader .Accordin g toEime r (1966an d 1973) this relation isno tlinear .Ow nresearc h (see3.1.1 )ha s shown that this relation islinea r ifstra w feed rate ishighe r than 1kg' s

The straw elevator The lower axle ofth ewheel s carrying theelevato r chains ismovabl ei n the vertical direction.Th epositio n of this axle dependso nth equantit y of strawbeneat h it.Accordin g toEime r (1966an d 1973)an dou row nre ­ search (see3.1.2 )th erelatio n between displacement and feed rate straw isals o linear above aminimu m feed rate levelo fabou t 1kg* s The relation between thestra w feed rate andth etorqu e fordrivin g the upper elevator shaftha sals obee n measured (Eimer, 1966,1973 ; Huisman, 1973). This signal ismeasure d later than thedisplacemen to f

64 theelevato ro ra nauge rsignal .Moreover ,correlatio nwit hth efee drat e ispoor ,a sth emeasure dvalu eoriginate sfro mfriction ,dependin go nth e moistureconten to fth estraw .I ti stherefor eunsuitabl efo rmeasuremen t ofth efee drate . Thelaye rthicknes so fth estra wunde rth emiddl eo fth eelevato rha s alsobee nmeasure d (Eimer,1966 ,.1973) .Thi ssigna li sno tlinea rwit h feedrate ,bu tdepend so nth echai ntensio nan di smeasure dlate rtha n thedisplacemen to fth elowe raxle ,s otha ti ti sles sattractiv etha n axledisplacemen tt omeasuremen to ffee drate .

Threshing cylinder Therelatio nbetwee ndrivin gpowe ran dth efee drat eha sbee ninvestigate d byman yresearcher s (seeA 1.2).Thoug hthi srelatio ni sgood ,i ti sno t soattractiv ei na contro lsystem ,a si ti smeasure dlate rtha nother , alsousefu lsignal sreferre dt oearlier .

Engine power Onlypar to fth epowe rrequire dfo rrunnin gth ecombin eharveste r (about 50-80%)i srelate dt ofee drate ,s otha ti ncompariso nt othreshin gpower , theengine-powe rsigna li sles susefu lstill .

Inal lcase sa relatio nt oquantit yo fstra wan dno tt oquantit yo fgrai n +stra wha sbee nconsidered .Thi sca nb eexplaine db yth efac ttha tth e measuredparamete ri srelate dprimaril yt oth evolum eo fth emateria l andno tt oth emass .Th evolume ,i nturn ,depend smainl yo nth equantit y ofstraw ,expresse di nterm so fmass ,i.e .dr ymatte rmass . Themos tsuitabl efee drat eparameters ,auge rtorqu ean delevato r displacementwil lb edescribe di ndetai li nth efollowin gsections .

3.1.1. Torque of the auger as feed rate sensor

Thestra wfee drat ean dsevera lothe rfee drat eparameter shav ebee n measureddurin gth efiel dmeasurement sfro m 1969.. .1976 .I nfigur e 3.1.1.1a nexampl eha sbee ngive no fth eexperimenta ldat ao f 1970fo r themeasurement so fth eauge rtorque .Th eresult sfro mth eothe ryear s aregive ni nth eappendix .

Iti sfoun dtha tth erelatio nbetwee nfee drat elevel swhic hexcee d

65 TA N-m 200 1970 180 160 KO 120 100 80 60 40^ 20 0 1 2 3 FS kg.s - 1 Figure 3.1.1.1. Relation auger torque to straw feed rate of field tests of 30-mstretche s with oats (Astor), MCS = 38.3-58.7% ( ) TA -31.5+74.9'FS (r=0.93),(- )TA = -54.8+102.8-FS-7.57'(FS)^ (r=0.93)

1kg' s l and the auger torque canb e accurately approximated by a linear relation.Fro m data of the year 1970 itha sbee n found that a linear and a squaredmode lha d similar correlation values,r = 0.93 (see fig. 3.1.1.1) (Huisman, 1974a). Thiswa sbase d on the averages of 24measure ­ ments each covering a stretch of 30metres .Thi s 30metr e stretch con­ sisted of 5 separate stretcheso f 6metres .Th e linear model provided a correlation value of 0.90 for these 120values .Th e linear and the squared modelwer e also equal in 1971 (r= 0.82) (see the figures in the appendix). The models and correlations are statedwit h the figures.

There are only slight differences between the various years andcrops . Only the results of 1972ar e extraordinary,probabl y because of a damaged (i.e,curved)auger .Th e scatter ofpoint s isno tonl y a resulto fmeasure ­ ment errors,bu t also of the influence of themoistur e content and ripeness of the strawwhic h varied widely during the tests.Th e scatter ismuc h lesswhe n themeasurement s apply to almost the same crop which canb e achieved with short intervals between the individual tests,a s in 1976.

A variation of the slope doesno t give rise toproblem s inpractice . This isbecaus e the feed rate signal isuse d in a loss control atwhic h the relation between the feed rate signal and lossha s tob e estimated

66

J in any case,an dwher e it isno t importantwha t the transfer ratiosare . The relation will notb e linear at feed ratesbelo w 1kg' s and will tend to zerobecaus e zero load value isalread y subtracted in the givendata . When the auger torque isuse d as a feed rateparamete r this can cause problems in the case of cropswit h little a straw. In such cases the auger has tob e differently adjusted,sotha t a shorter distance to the bottom is realised.

When the signal is studied as to its dynamic aspects,i tca n be deduced from thepowe r density spectrum of the torque signalmeasure d by strain gauges on the shaft,tha tpeak s occur at50 , 100, 150an d 200 rad's ï (see figure 3.1.1.2). These are the frequencies and thehighe r harmonics coherentwit h the rotational speed of the auger andwit h the penetration into the strawb y thepin s in the centre of the auger.Thes epin s are in 4 rowsa t9 0 toon e another.

dB 0-

-12

-24

-36

-48 50 100 150 200 250 Frequencyrad .s -1

Figure 3.1.1.2. Power spectrum of the signal of the auger torque measured by strain gauges at the driving shaft

67 Fromthi si tca nb econclude dtha ta larg epar to fth erequire dtorqu e canb eexplaine db yth epenetratio no fth epin sint oth ecrop .Therefor e themovemen to fth estra wmas salon gth eauge rpin san dbetwee nth etop s ofth epin san dth ebotto mshee twil lexer ta torqu eo nth eshaft . Inadditio nth emovemen to fcro pi nfron to fan dunde rth eauge r windingswil lals orequir epower ,thoug ht oa lesse rextent ,a sth e quantityo fcro pi ssmalle r (excepti nth eeven to fjamming) .Apar t fromthes epeaks ,th epowe rspectru mgive sth eimpressio no ftypica l first-ordernoise ,wit hsom eextr apowe ri nth elowe rfrequencies .

Iti sno tpossibl et ob etrace dwhethe rther ei san yrelatio nbetwee n thetorqu ean dth efee drat efo rfrequencie sabov eabou t0. 3rad* s , becauseth eshortes tstretc hi nwhic hth ecro pha sbee ncollecte dan d weighedi s5 metres .A ta drivin gspee do f1 m' s: thisrepresent sa periodo f5 seconds ,resultin gi na first-orde rlow-pas sfilte ractio n witha breakpoin tfrequenc yo f2ir /(4-5 )=0.3 1rad' s* .I twa s assumed thatth e samerelationshi phold sfo rfrequencie sabov e0. 3rad* s .Fo rth emachin e speedcontro lthi sassumptio ni swithou trisk ,a sth efee drat esigna l useda sinpu tfo rth econtrol ,passe sa low-pas sfilte rwit ha bandwidt h of0. 4rad* sl .Highe rfrequencie sar estil limportan tfo rth ethreshin g speedcontrol .

Todea lwit hth euncertaint yo fthi sassumption ,nois ewa sadde dt oth e calculatedtorqu ea smeasuremen tnois ei nth esimulations .Th eintroduc ­ tiono fnois eint oth emeasurement si sals oessentia la tth elowe rfre ­ quencies,a sw emus tconclud efro mth escatte ro fth eexperimenta ldat a giveni nth efigure stha tther eca nb econsiderabl evariatio ni nth e measuredsigna lfo rth esam estra wfee drate .Withou tnois eth econtro l systemwoul dno twor krealisti ci nth esimulation .,

Inth emodel ,th emeasuremen to fth efee drat eb yth eauge rtorqu ei s representedb ya linea requation . -Whe nth eapparen tstra wdensit ywa scalculate dou to fauge rtorqu e measurementso nmachin eA , theequatio n FS =0.4 2+ 0.0193.E l (3.1) wasused .Thi srelatio ni sth econtinuou slin ei nfig .3.1.1.3 . -Whe nth esam ewa sdon efo rmachin eB ,th erelation sdraw ni nfig . 3.1.1.4wer eused .

68 TA N-m 160 1978 U0

TA N-m 120 100 - / • 100 80 - • 80 60 - 60 40 - 4A- 40 A 20 - 20 • X

0 1 0 1 2 3 3 4 5 FS kg.s-1 FS kg.s-i Figure3.1.1.3 .Relatio nauge rtorqu e Figure3.1.1.4 .Relatio nauge rtorqu e- tostra wfee drat ei nfiel dtest so f strawfee drat ei nfiel dtest so f15- m 15-mstretche s at machineA o fth e stretchesi n 1978a tmachin eB o fIJ.D.A . IJ.D.A.i n 1975.x = wheat ,• = oats , withwinte rwheat :nautic a (•); TA = A= barley {MCS =12.5-49.4% ) 16.2+22.0-.FSan danousk a (o), TA =8. 1 calculatedrelation : +30.6-FS FS =0.42+0.0193-2V 1 (r=0.89) probableextrapolatio n

-I nth esimulatio nmodel ,measuremen to ffee drat ei nth econtro l requiresth eadditio no fnois et oth ecalculate d feedrate .S o FSM= FSA+ nois e (3.2) Thedimensio no f FSMremain sa skg* s1 .Th enois ei swhit enois ecreate d bya rando mgenerato ro fCSM Pan dvarie saroun d0 + _ 0.2'FS average andi sthe ncoloure db ypassin ga high-pas sfilte rwit ha breakpoin t frequencyo f0. 1 rad's' .

3.1.2. Straw elevator displaoement

Themas stransport'ate db yth eelevato ri sroughl yth esam ea spresente d atth epin so fth eauger ,ther ei sn oredistribution .Th erelatio nelevato r displacementt ofee drat ei sa sgive ni nfigur e3.1.2.1 .I tshow stha t thesigna lha sa nuppe rboundary ,sinc eth edisplacemen ti smechanicall y limiteda tabou t5 5mm .Moreover ,a certai nfee drat eo f1 kg' s' i s necessarybefor edisplacemen toccurs .

Themeasuremen tpoint sobtaine dar eshow nan dth ecalculate dregressio n linesdraw ni nfigur e3.1.2. 2an di nth eappendix .Th epresente dvalue s

69 DE mm 40 - 1969/70 / DE mm 35 - 60- 30 - 50- / S 25 - 40- / 20 - 30- 15 - *V* 20- 10 - %/{* ^^ 10- 5 -

0 0 i 0 1 2 3 4 5 6 1 2 3 FS kg-s-1 FS kg.s-1 Figure3.1.2.1 .Relatio nelevato rdis ­ Figure3.1.2.2 .Relatio nelevato rdis ­ placementt ostra wfee drat e placementt ostra wfee drat ei nfiel d formeasurement si n1969...197 3 testso f30- mstretche swit hwinte r probableextrapolatio n wheat,Manell a (o)i n1969 , MCS = measurementsi n197 4 10.3-13.6%, ( ):DE =-20.8+19. 9'FS (r=0.94)an dwit hoat s (+)unde rcon ­ ditionsgive ni nfigur e3.1.1.1 , jr ): DE=-10.3+13 . 1'FS (r=0.96)a n ( Y.DE=-8.14+ll.l'FS+0.753-(ra) 2 (r=0.96)

ofth eelevato rpositio n {DE)giv eth edistance sabov eth elowes tpositio n ofth eaxle .Ther ei salread ya smal lga p (+_2 mm )the nbetwee nth eele ­ vatorchain san dth ebotto mo fth eelevato rhousing . Theresult sobtaine di nth eyear s 1969-1973sho wtha tth ecurve swer e aboutth esam ei nthes eyear san dth emeasuremen tvalue s4 0m mmaximum . In197 4th evalue swer emuc hlowe ra thighe rfee drates .Presumabl yth e springtensio nwa sadjuste dhigher .A nothe rpossibl ereaso ni stha tth e croppropertie sdiffered ,becaus ei twa sfoun dtha tth emeasure dauge r torqueswer eals olo wi ntha tseaso n (seeA 3.1.2). Thisshow stha tth erelatio ni scomparabl ewit hth etorqu eo fth e auger (abovezer oload )an di scertainl ys owhe nonl yth ehighe rfee d ratesar econsidered .Furthermore ,ther ei sn odifferenc ei ncorrelatio n betweenlinea ran dexponentia lregressio nlines . Consequentlyth euppe rboundar ywa sno treache da tver yhig hfee d rates.Wer ethi st ohappen ,i tcoul db ecorrecte db yincreasin gth e tensiono fth eelevato rchai nsprings . Iti sclea rtha tn orelevan tfee drat esigna lca nb emeasure da tver y lowfee drat elevels .Thi sdifficult yca nb eme tb ya naltere dchai n

70 constructionan dpossibl yusin gweake rsprings ,bu ti tremain sa disad ­ vantage. Thedynami cbehaviou ro fth eelevato rdisplacemen twil ldiffe rfro mtha t ofauge rtorque ,fo rth efollowin greasons : -th eelevato rchai nha sa hig hmass , -th eelevato rchai nencounter sa Coulom bfrictio nan dsprin gforc ewhe n iti smoving , -th estra wha selasticity . Thetransfe ro fth eelevato rdisplacemen ti ssimplifie db ya first - orderproces swit h T= 0. 3s .Thi svalu eha sbee nchose no nth ebasi so f visualcomparison so fth emeasure dan dsimulate dsigna lplots .Figur e 3.1.2.3show srecorde dsignal so fauge rtorqu ean delevato rdisplacemen t inth esam efiel dtes t (KleinHesselink , 1971).Figur e3.1.2. 4show s simulatedsignal so ffee drate scalculate do nth ebasi so fapparen tstra w densityinpu t (1978).Th e DElin eha sbee nshifte dupward si nth eplo t by2 kg*s -1.

Inth esimulatio nth eelevato rdisplacemen tca nb euse da sa contro l inputt orepresen tfee drat emeasurement .I ntha tcas ei ti sth ecalcu ­ lated FSEvalu etha tha spasse dth efirst-orde rprocess ,afte rwhic h noisei sadde da swa sdon ei nth emode lo fth eauge rtorqu emeasurement . Sothat : 1 FSEM = FSE-(• (3.3) 1+0.3-s NOISE

times

Figure3.1.2.3 .Signal so fauge rtorqu ean ddisplacemen televato rfo r thesam eperio do ftim ei noat s (1970)

71 70 80 times Figure3.1.2.4 .Signal so fauge rtorqu einpu t (a)an dcalculate doutpu t throughfirst-orde rproces swit hT = 0. 3 (b)( curv e bwa sshifte d 2kg«s -1 upwards)

3.1.3. Auger torque - elevator displacement relationship

Theresult so ftw oyear so ffiel dtest shav ebee nstudie di ncomparin g thetw ofee drat esignals .I n197 0 (KleinHesselink ,1971 )th elinea r correlationwa scalculate dbetwee nal lvariable smentione di ntabl e 3.1.3.1.Th edat ai nth ecalculatio nwer eth eaverag evalue so fstretche s of5 m ,i nal l12 0measurement si noats .

Table3.1.3.1 .Value so flinea rcorrelatio ncoefficient so fth efee drat e signals DEan d TA

Strawfee drat e DE Signalo felevato rdisplacement : DE 0.95 Signalo fauge rtorqu e : TA 0.94 0.97

Fromtabl e3.1.3. 1i tca nb econclude dtha tth ecorrelatio nbetwee nbot h

72 Signalsi so fth esam eorde ro reve na littl ehighe rtha ntha tbetwee n thesignal san dfee drate . Itca nthu sb econclude dtha tthe ,measuremen tfault si nstra wfee drat e measurementar epossibl ygreate rtha ni nth emeasurement scarrie dou ta t theelevato ran dth eauger .Anothe rreaso nca nb eth eredistributio no f strawo nth ewalkers .

Fromth e 1973whea tdat a (Teunissen,1979 )th ecorrelatio nbetwee nbot h signalswa sestablishe dfo rvalue saverage dfo rvariou speriod s (AP). The timela gbetwee nth etw osignals ,establishe db ycros scorrelations ,wa s applied. Anincreas ei nA Pgive sa nincreas ei ncorrelatio ncoefficien tunti l itremain sconstan ta tvalue sabov e2 second s (seeA 3.1.3).Fo r AP= 2 s , datao f 14tests ,20 4s i nduration ,wer ecorrelated .Tabl e3.1.3. 2give s a summaryo fth eresults .

Table3.1.3.2 .Correlatio ncoefficient s (r)fo rth estudie drelation s betweendisplacemen tstra welevato r (DE)an dauge rtorqu e (TA) r minimum maximum average Linearrelatio n 0.53 0.93 0.80 DE= a + h-TA exponentionalrelatio n 0.51 0.93 0.78 la IDE)= a + b'TA

Fromth eabove-mentione dresult sth efollowin gca nb econcluded :Th e relationbetwee nbot hsignal si sclearl ypresen tan dimprove sfo rhighe r APvalues .I tshow stha tbot hsignal shav ethei rspecifi cpropertie san d consequentlysho wdeviation sfro mth erea lfee drate ,whic hi sespeciall y noticeablei nth ehighe rfrequencies .

Whenth eauge rtorqu ean dth edisplacemen to fth eelevato rchai nfo r testsi nwhea tan doat sove ra perio do f5 year sar ecompare dt oon e anothera sa measurin gsigna lfo rth efee drate ,the nth efollowin gre ­ sultsar eobtained : Coherence with the feed rate. Whenth ecorrelatio ncoefficien to f linearmodel sar ecompare dt oon eanother ,th eresult sshow ni ntabl e 3.1.3.3ar eobtained .

73 Table3.1.3.3 .Correlatio ncoefficient sbetwee nfee drat e (FS) andfee d ratemeasurin gparameters :auge rtorqu e (TA)an delevato rdisplacemen t (.DE) ww =winte rwhea t wwe= winte rwhea ta tearl yripenes sstag e wwl= winte rwhea ta tlat eripenes sstag e sw =sprin gwhea t

Year 1970 1971 1972 1973 1974 Crop oats WW WW sw wwe wwl WW sw Correlation fTA 0.93 0.82 0.79 0.86 0.98 0.98 0.98 0.93 Coefficient[DE 0.96 0.78 0.73 0.86 0.99 0.98 0.94 0.94

Thedifference sar eminima lan dno trelevan tt oa qualitativ estatement . Also,the yhav eth esam edependenc eo ndifference si ncro ppropertie s (seeth efigure si nA 3.1.3) . Measurement delay. Dependingo nth eplac ea tth eauge rwher eth eforce s fortranspor to fth estra war ecaused ,th esigna lo fth edisplacemen to f theelevato rchai ni smeasure d0.3-0. 6second slate rtha nauge rtorque .I f itwer epossibl et ocontro lhigh-frequenc yvariation si nfee drate ,i t mightb eimportan tt ous eth efee drat emeasuremen twit hth eminimu mdelay . Technical possibilities for measurements. Thepositio no fth elowe r axleo fth eelevato rchai nca nb eeasil ymeasure dmechanicall yan dtrans ­ formedint oa nanalo go rdigita lsignal .Th emeasuremen to fth eauge r torquei smor edifficul tan dmor eexpensive ,bu tstil lfeasible . Conclusion: Therei sa preferenc efo rth eapplicatio no fth eauge rtorqu e asa fee drat emeasuremen tparameter ,becaus eth etim edela yi sles san d therei sn odifferenc ei nqualit ybetwee nth emeasuremen tsystems .Th e differencei ntota lharves tcost sdu et oth edela ywil lb eestablishe db y simulations.

3.2.MEASUREMEN TO FGRAI NFEE DRAT E

Knowledgeo fth egrai nfee drat ei sessentia lwhe nth eprocesse si nth e combineharveste rar et ob eexamined .Whe nwalke rlos smeasuremen ti s donewit hth ehel po facousti csensor s (see3.3.2 )th ecalculate doutpu t hast ob econverte dint oth euni tkg* s .Whe nth econcav eseparatio n ismeasure di nthi swa y (see3.4 )th ethreshin gseparatio nefficienc y hast ob ecalculate da sa fraction .

74 Measuremento fa grai nflo wi spossibl ei nterm so fweigh tan dvolume . Bothsystem sar ea tpresen tbein gdeveloped . Thesyste mbase do nweigh ti smerchandise d asa "Discharg eMeter " thatca nb eattache dt oth edischarg eauge ro fa combin eharvester .I n trials,th eresponse so fth emete ri nth ecas eo fwhea twer escattere d witha coefficien to fvariatio no f4.6 %an dbarle ywit h6.4 % (Hooper, 1979). Schueller (1982)report so ntest swit ha simula rgrain-flo wmete r mountedunde rth edischarg eauge ri nth egrai ntank .Th eperformanc e wasfoun dt ob epoore ra tlowe rfee drates .Th ereadin gwa sinaccurat e whenharvestin gso ybean swit ha heav yconcentratio no fwe tweeds .Appa ­ rentlyth esyste mha st ob eadapte dt olowe rfee drate san dt ous e inpractice . Volumemeasuremen ti seasier ,bu tneed sa calibratio nt oweight .Thi s caneasil yb edon eb yth eoperato ran dth eresul tca nb epu tint oth e microprocessoro nth emachine .N otes tresult sar eknown .

Themode lo fth egrai nfee drat emeasuremen tfo rth esimulatio ni sbase d onth efollowin greasoning .Th egrai nflo wi s assumed tob emeasure d whenth egrai nleave sth econveye ra tth ebotto mo fth egrai npa nunde r thesieves .I ttake s roughly 5second sfro mth etim eo fseparatio na t thethreshin gcylinde ran drotar yseparato rt oreac hth econveye rthroug h thesieves .A smal lpar to fth egrai ni sseparate dfro mth estra wa tth e walkersan dreache sth econveye ra tleas tanothe r5 second slater . Inth esimulatio nmodel ,th egrai nfee drat ei s assumed tob eknown , forth epurpose so fth ecalculatio no fth ethreshin gseparatio nefficienc y TSE, neededa sinpu ti non eo fth econtrol s (see3.4) .Th evalu eo f TSE isonl yknow nafte ra dela yo f9 seconds .Th emeasuremen tfault sar e introducedint oth emode la snois ean dadde dt oth ecalculate dthreshin g separationefficiency .

3.3.MEASUREMEN TO FWALKE RLOS S

Thewalke rlos si sth emai nlos soccurrin gwit hcombin eharvester si n WesternEurope ,becaus eo fit sexponentia lcharacter .I ti sa ninpu t variablei nal lcontro lsystem sconsidere di nthi sstudy .I ti sa nim ­ portantcos tfactor ,no tonl ybecaus eo fit sow nfinancia lvalue ,bu t alsobecaus ei taffect sth espee do fth ecombin eharveste rse tb yth e

75 costminimisatio noutpu to fth econtrol .Therefor ei ti sver yimportan t tomeasur eth elos saccurately .

Thelos suni ti nth ecos tcriterio n (VWL)i sfl'h a' ,whil ei nth erea l processi ti skg* s (WL).Th etransfe rfro mth esecon dt oth efirs ti s easilyobtaine db ymultiplicatio nb yth evalu eo fth egrai ni nfl'k g (V2)an ddivisio nb yth eare aharveste dpe rtim euni t (VW)m 's or better (W/10000)ha's -1 1 WL =WZ>F 2'10000/W fl-ha" (3.4) Thisi sals oth emos tinterestin ginformatio nfo rth efarmer ,s oknow ­ ledgeo fVJ/( = VM'CL)i snecessar y forth ecalculatio no floss .

Thelos sfractio no ftota lgrai nfee drat eo ro fgrai nfee drat et oth e walkersi smor einstructiv ewhe nth equalit yo fth eproces si sobserved . Inthi scas eth egrai nfee drat eha st ob eknow nalso .Th ewa ylos smea ­ surementsar edon enowaday swil lb ediscusse di n3.3.1 .A sw eshal lsee , thismetho di sinaccurate ,henc ea suggestio nfo ra bette rprincipl eha s beenintroduce di n3.3.2 .

3.3.1. Grain-loss monitor

Nowadaysso-calle dgrain-los smonitor sbase do nth eprincipl eo facousti c sensors,ca nb ebough tfo rus eo ncombin eharvesters .Th eprincipl ewa s introducedb yFeiffe r (1967)an dRee d (1968)an dconsist so fa sounding - boardwit hmicrophone ,attache dt oa nextensio na tth een do fth ewalker s (orsieves )an dsom eelectroni cdevices . Seedsan dbit so fstra wwil ldro po nth esoundin gboar dan dgenerat e anoutpu tsigna ltha twil lb eprocessed , sotha tgrai nimpact sar ediscrimi ­ natedfro mnois ean dothe rmateria lstrikin gth esounding-board .Grai n impactsar econverte dint ounifor msquare-wav epulse stha tca nb econver ­ tedint oa nanalo gvoltage ,mad evisibl eo na meter . Thesounding-board svar yi ndesign .Th eelectronic sca ndiscriminat e thedifferen tkind so fseed sfro mstraw .Som esystem stak eth emachin e speedint oconsideratio ni nconvertin gth emete routpu ti nlosse spe r area.Th emete routpu tha st ob ecalibrate dt orea llosses ,becaus eth e ratioo fseed sstrikin gth esounding-boar dt otota llosse sha st ob ees ­ tablished.

76 Therelatio no fmeasure dlos st orea llos si sfairl ygoo dan dlinea r undernearl yconstan tharves tconditions .Puls esaturatio noccur swhe n morean dmor eseed sfal lo nth eboard sa tnearl yth esam etime .I nfigur e 3.3.1.1result so ffiel dtest sdon ei n197 4ar eshown .Thi sfigur eshow s thepatter njus tdescribed . However,whe nth eharves tcondition schang econsiderably ,a swa sth e casei nth efiel dtest so f 1971,th eresult sar elik ethos eshow ni n figure3.3.1.2 .Thi sresul ti sfoun dbecaus eth erati obetwee nseed s fallingo nth eacousti csenso ran dth erea llos schange sdurin gth eda y orseaso na sdescribe dbelow . Whenwalke rseparatio ndecreases ,losse sincreas ean dth efractio n separatedabov eth esoundin gboar ddecrease sa swell ,wit hth eresul t thatmete routpu tincrease sles stha nth erea llosse sdo .A noutpu to f about5 pulse spe rsecon di nfigur e3.3.1. 2ca nsometime sindicat ea losso f0.0 5kg* s and0.2 0kg* s atothers .Thi sca nb eregarde da s 0.1kg«s -1 +100% . Moreresult sar egive ni nth eappendi xan dlea dt oth esam econclusio n asca nb edraw nwhe nal lliteratur eo nthi ssubjec ti sstudied .Th emete r outputgive sn oindicatio no frea llos swhe ncalibratio nfo rvariou scon ­ ditionsi somitted .

WL kg.s- 0.25 -

0.20

0.15

0.10

0.05 x x„

10 20 30 40 50 WLM s-'

Figure3.3.1.1 .Relatio nwalke rlos smeasure db ygrai nlos smonito r (WLM) tolos smeasure db ymean so flos smeasurin gmachin e (WL)ove rstretche s of3 0m i nfiel dtest so f197 4

77 behind thepoin twher e the correct exponential separation starts (kg's"1), G =quantit y of grain in the straw at x = 0 (kg's 1), and WE= walke r efficiency m The grain separation at x, (S, )i s then the derivate toa ;o f G, ,s o that w w d{G)/dx =S WE'G exp(- WE'x) (3.6) w w According toGlase r (1976)wh oworke d this out for a shaking grain sepa­ ration conveyer instead ofwalkers ,th ewalke r loss G for x = I =en d of w walkers, canb e calculated from (3.5)whe n WEan d G are estimated by measurements of the grain separation S for twodifferen tvalue s of x. w We assume that thisprinciple ,show n in figure 3.3.2.1, alsowil l work for strawwalkers .Th e grain separation canb e measured by monitors at various points under thewalker s as described in thepreviou s chapter. With these monitor signals thewalke r loss can be calculated asexplai ­ ned below.

Figure 3.3.2.1. Walker separation (S )a s a function of the distance from the front (b)o f thewalker s (a;)fo r two (Aan d B) different crop property situations. Ml and M2 =separatio n measured bymonitor s at X\ and xi. WLM= separation measured at the end of thewalker s (£) o = theplac e where the theoretically correct exponential separation starts late

Twopossibl e separation curves A and B are shown in figure 3.3.2.1. The separationproces sbecome s correctly exponential at 0 after a starting process from b to 0. The end of thewalker s isa t i, so thatth e hatched area at the right sideo f Ürepresent s thewalke r loss. The losses can be calculated by using twomonito r outputs fromwel l chosen places under thewalker s for instancex i and X2. InA 3.3.2 the formulas and results

78 WL kg.s- ' 0.2 5- X

0.20- X X

X X X X X X 015- * X X X

X x x X X X Xx X X 0.10- * xx x x X X X X X 0.05 - X * X

0 12 3 4 5 6 7 WLM s-1 Figure 3.3.1.2. Relationwalke r lossmeasure d by grain lossmonito r (WLM) towalke r lossmeasure d by rethreshing the straw,gathere d on sheets of 6 m in field testso f 1971 (WL)

Calibration is omitted in general practice orno t applied frequently enough,because it isno t simple and needs either a second man to do it, or includes machine stops.Farmer s use the system tochec k for sudden changes in losses,bu t they dono t refer the meter output to real losses in termso fkg'h a 1 (Dongen, 1981a).

The conclusion tob e drawn from these results is that such monitors cannot be used for automatic control.The y can only be used formanua l control if calibrated at least every hour,especiall y when harvest conditions change.

3.3.2. Principle of an improved loss monitor system

A mathematical model of grain separation at strawwalker s wasworke d out in 2.3.4 andA 2.3.4-b. In thismode l an assumption wasmad e about the constancy of separation efficiency behind the curtain. The separation, as a function of distance from the curtain decreases exponentially in awa y that canb e derived from themodel ,s o that

G = G exp( r - WE'x) (3.5) W o Note that quantity of grain in the strawpassin g over the walkers at1 i

79 of some laboratory tests are given.Thes e tests show that the estimation of loss ismuc h better thanwit h juston e monitor at the end of the wal­ kers. Field testswil l have to show thepractica l use,s o that further research is necessary.

Some remarks on thismeasurin g technique are be madebelow . 1)Th e time delaybetwee n theoutpu to f the twomonitor sha s tob e taken into consideration. 2)A redistribution of grain in the areabetwee n the twomonitor s will give rise tomeasurin g errors. 3)Th e measuring signals showmuc h measuring noise,s o a long averaging periodwil l be necessary for loss calculation. 4)Th e dimensions of themonitor s have tob e chosen so thatn o pulse saturation will occur. 5)Th e monitors need tob e calibrated often tochec k theirprope r functio­ ning,bu t also toobtai n information on the transfer frommonito r out­ put (pulsespe r second) tokg* s .Bot h actions could be done by cal­ culation of the total separation through thewalker s from 0 to SL as well as from b to 0 and through the concave grates of threshing cylin­ der and rotary separator by additional monitors and comparing the calculated separation in the unitpulse spe r second to ameasure d grain flow inkg- s toobtai n the ratio. Itwil l be clear thata micropro ­ cessor isneede d for these calculations.

6) Having anumbe r ofmonitor s in the combineharveste r offers thepossi ­ bility of supervising theprocesse s in the machine.Thi swil lb e an important advantage of this complex measuring technique.

To avoid misunderstanding itha s tob e explained that the use of one monitor for lossmeasuremen t isprincipall y different from the use of two ormor emonitors . If amonitor , connected at theen d of the walker,measure s the grain separation WLM,indicate d by the cross-hatched column at l_i n figure 3.3.2.1 thewalke r loss isno t uniquely defined. For instance, ifw e consider curves A and B, the loss is represented by adifferen t surface below the curve at the right-hand side of I, butbot h curves show the same separation WLMa t £. If twomonitor s are used, for instance at X\ and I curve A is defined

80 by Mi and WLMan d the assumption of exponential separation. If the separation is alsomeasure d (M2) at a thirdpoin t the assumption can be verified and corrected.

Themode l of the measurement ofwalke r loss for the simulation is easily represented by the value of thewalke r losscalculate d in the process model. In this case also coloured noise is added in samewa y as in the measurement of feedrate .

3.4.MEASUREMEN T OFTHRESHIN G SEPARATION EFFICIENCY

Inon e of the control systems studied the threshing separation efficiency will be used asa n inputvariable .A s threshing separation efficiency cannotb e measured by any known system the intention is topu t one for­ ward in the followingparagraphs .

The measurement system canb e based upon measurement of concave separation by acoustic sensors,mentione d inparagrap h 3.3.Th e sensorshav e to be very small to avoidpuls e saturation. The design of the electronic device canperhap sb e adapted to the large amount ofkernel spassin g the concave. Several sounding-board sensors have tob eplace d under the concave. The separation pattern isnonlinea r so thata t least three sensors,situa ­ ted in the direction of rotation,ar e required for a goodestimate . A check of the concave adjustment ispossibl e too then,a s the correct adjustmentha s to show apatter n of decreasing separation towards the end of the concave.Mor e sensors are also required in the transverse direc­ tion for good estimation of total concave separation. Frompreliminar y laboratory tests itwa s concluded that such amea ­ surement system could estimate the separation satisfactorily. Itha s alsobecom e clear that amicroprocesso r will be needed toperfor m the calculations and calibrations to the unitkg* s 1. More research will be needed.

The threshing separation efficiency, the ratio of concave separation to total grain feed rate,ca n only be calculated ifbot h values are known in the same unit.I f the rotary separator andwalke r separation andwalke r loss are also estimated by the use of acoustic sensors (see 3.3) the total separation canb e calculated, too.Th e walker separation andwalke r loss

81 canonl yb ecalculate dafte ra dela yo fabou t8. 0 san dsom etim efo r averaging.

Inth esimulatio nmodel ,th evalu eo fth ethreshin gseparatio nefficienc y istake nfro mth ethreshin gmode lbu tdelaye db y9. 0 s.Th eexpecte d measurementerror sar ebrough tint oth emode lb yaddin gnois efro ma whit e noisegenerato rpassin ga high-pas sfilte rwit hadjustabl ebreakpoin t frequency.Th enois edefaul tleve li smaxima l+ _3 %aroun d0 .

3.5.MEASUREMEN TO FSPEED S

Allth econtro lsystem sstudie dnee dcorrec tinformatio no nth eactua l speedso fth ethreshin gcylinde ran dth emachine . Thespee do fth ethreshin gcylinde rca nb emeasure dver ysimpl yan d accuratelyb yal lkind so frotationa lspee dsensor savailabl ecommercially . Nospecia lattentio ni stherefor epai dt othi ssubjec ti nth emodel .I t hasbee n assumed thatth emeasuremen ti sdon eaccurately .

Thespee do fth emachin eca nb emeasure dfro mth erotationa lspee do fth e wheels.Th edrivin gwheels ,however, 'wil lb esubjec tt oslip ,dependin g onth esoi lpropertie san dth eweigh to fth emachine .A sthi sweigh ti s influencedb yth eamoun to fgrai ni nth etank ,th esli pwil lvary .Th e measuringerro rwil lthu svar yroughl yfro m1 %t o5% . Measuringth erotationa lspee do fth esteerin gwheel sa tth een do f themachin ewil lgiv eris et oa smalle rerro rdu et osli pbu tals ot o anextr aerro rdependin go nsteerin gactivity .Th eexpecte dtota lerro r isestimate dt ob e1% .

Themeasuremen to fspee dca nb edon emor eaccuratel ybu tmor eexpensivel y byultrasoni creflection .N ospecia lfeature swer etherefor eintroduce d inth emodel . Inth eoptimisatio ncriterio ni ti si nfac tth eproduc to fmachin e speedan dcuttin gwidt hwhic hi sused ,s otha tth ecuttin gwidt hha st o beknown ,too .Th ecuttin gwidt hi sgenerall yconstant ,bu ti nspecia l circumstancesth eoperato rdoe sno tus eth efull'widt ho rdoe sno tstee r accurately,s otha tth ewidt hwil lvary .I tcoul db esignifican tthere ­ foret odevelo pa syste mt omeasur eth eactua lwidt ho fth ecutte rba r whena contro lsyste mneed stha tinformation . Inou rmode li twa s assumed thatth ecuttin gwidt hi salway sconstant . 82 4. Disturbances

4.1. INTRODUCTION

In control systems design,study of thewa y inwhic h process disturbances occur isnecessary . The disturbances are one of the most common reasons why a controlled variable tends todeviat e from itsdesire d value andwh y feedback control is required. The disturbances in the processes of the combineharveste r are mostly due to thenatura l variation in cropproper ­ ties causedb y growing andweathe r conditions.Thes e conditions change as a function ofplac e and time. As combineharvestin g isdon ewit h a locomotory machine taking crop from a certain area ata certain speed, the place variations also become time variations.Th e control systemha s to react to these variations. Other disturbances are due to themeasuremen t systems of the control. These disturbances are inevitable and the control systemwil l react to them, so thataccoun to f this factha s tob e takenwhe nw e develop acontrol .

Knowledge of the disturbances in the process of combine harvesting is necessary as 1)i t ispossibl e todevelo p anopinio n aboutwha t canb e expected from control. 2)Th e design of the control system isaffecte d by the disturbances. 3)A realistic situation, including all important disturbances has tob e considered for calculating thebenefit s ofcontrols .

In some cases the disturbances themselves canb emeasure d but inmos t cases it isonl y the results,th e outputs ofprocesse s that canb e measured. The disturbances of theproces s being considered are those affecting losses: straw density on the field, andproces s variables at threshing and separation. The disturbances on themeasure d signals considered are feed rate,concav e separation andwalke r loss. Iti s important to realize in advance thati t is

83 notonl yth ehigh-frequenc y disturbancestha thav et ob econsidered ,bu t thatth every-low-frequenc ydisturbances ,i nfact ,th emea nleve lvariation s areo fgrea timportance ,too .Th efollowin gchapter swil lals odiscus sth e wayi nwhic hth edisturbance sar emodelle dfo rth esimulations .

4.2.DISTURBANCE SI NFEE DRAT E

Aswa sstate di nth epreviou schapters ,th efee drat eo fstra w (kg*s ) orgrai ni sobtaine db ymultiplicatio no fth emomentar yspee do fth e machine (m*s '), thecuttin gwidt h (m)an dth eyiel do fth estra wo rgrai n onth efiel di nkg* m2 ,th eso-calle dstra wo rgrai ndensity . Whenth espee do fth emachin ean dth ecuttin gwidt har ehel dsteady , thedensit yvariatio nan dth eredistributio no nth ecuttin gtabl egive s thefee drat evariation .

Thedensit yo fth estra wan dgrai no nth efiel dha sbee ninvestigate db y manyauthor s (seeA 4.2.1a) .The yrepor to nth evariatio ni nweigh to f strawan dgrai no ffield so f0. 5m 2 upt o15 0m 2 inarea . Fromthes estudie si tca nb econclude dtha tth evariatio ni nstra w yield,expresse di nterm so fcoefficien to fvariatio no nfield swit h anunifor mcro pgrowth ,show sfigure sbetwee n5 an d30% .Ther ei sn oevi ­ dencefo rconcludin gtha tthes efigure sdepen do nth esiz eo fth eare a considered.Fo rth egrai nyiel dth esam econclusio nca nb edrawn .

Thequotien to fth egrai nyiel dan dth estra wyield ,th egrain-stra wratio , however,give sa coefficien to fvariatio ntha ti sabou thal fth estraw - densityvariation .Thi si sbecaus eth egrai nproductio nha sa direc trela ­ tiont oth estra wproduction . (Inth esimulatio no fth ecombin eharveste r processth efee drat egrai ni stherefor edirectl ycalculate dfro mth epro ­ ducto fth efee drat estra wan dgrai nstra wratio. ) Figure4.2. 1 showsth evariatio ni nyiel do fsuccessiv e5-m-wid eplot s (thewidt ho fth ecutte rba ro fa norma lcombin eharvester )an d1.5-m-long , infac tth estra wdensit yoffere dt oth ecombin eharvester .Th etes twa s donei na draine dfield ,s otha tth edifferenc ebetwee nfig .a ,workin g directionperpendicula rt otha to fth edrainage ,an dfig .b paralle lt o thedrainage ,ca nb eclearl yseen .

84 Yield kg- m-2

0.6-

0.4-

0.2-

30 40 distance m

Figure 4.2.1.a.Yiel d of winter wheato £plots ,5-m-wid e and 1.5-ro-long,harveste d in thedirection , perpendicular to thato f the drainage.

Yield kg- m-* — straw — grain

0.8-

06-

0.4

0.2-

10 20 30 40 distance m

Figure 4.2.1.b. Same as fig.a,butdirectio n parallel to thedrainage .

85 When we consider areas larger than 150m 2 we can compare the yields of different fields in various years so as to geta n impression of the long- term variation in yield. From agricultural practice and research iti sknow n thatthi s variation is considerable, too.Fo r instance,i npractice ,a t the IJsselmeerpolders Development Authority Grain Farm the coefficient ofvariatio n in grain yield of 19 fields of 30h a (!) was calculated. In theyea r 1978i twa s found tob e 19.6%a ta mea n yield of 6280 kg*ha-1.

Whenw e consider a combine harvester moving at a constant machine speed and constant cuttingwidt h along these fields,th e cropdensit y variation generates a feed rate variation as a function of time.Th e character of this variation willb e taken tob ewhit e noise in the frequency band of 0 to 1rad* s with extra variation at0 tob e due to sudden steps in the mean level.Thi s canb e explained as follows.Th e coefficient of variation, asmentione d earlier,i s defined (Cool, 1979) as' CV= 0 /u .Define d -x -x indiscret e time the variance is n a-\,d= i=lW 2/""1' «•" and defined in continuous time it is . T/2 22x a= li»f ƒ<*<*>•- UJ2 dt (4.2)

Ifw e want to transform the discrete variance of straw density into the continuous variance of feed rate it canb e doneb y assuming a constant machine speed and cuttingwidth .Le t us take the cuttingwidt h as 5m and a realistic average machine speed of 1m* s 1 so that straw density varia­ tions of 7.5 m2 plots,fo r instance from fig. 4.2.1,become feed rate variationspe r averaged 1.5 s. In this case the variations within the 1.5 s are unknown,henc e information on frequencies above 2ir/4*1.5*1. 0rad* s* is lostbecaus e averaging acts as a first-order low-pass filter with that breakpoint frequency (Verbruggen, 1977). For a length of 5m this is roughly 0.3 rad*s-1.

Thevarianc e is also affected by the total area taken into consideration at the field tests.I fa t these field tests,yield s aremeasure d which are comparable with, let us say,20 0m traversed distance of the combine harvester,onl y information was available on themea n level] J for aperio d of 200 s.Thi smean s that frequencies smaller than about 2TT/200 = 0.03 rad*s*

86 couldno tinfluenc eth evalu eo fa . Whe na nimpressio no fth epowe rspectru m ofth efee drat evariation si st ob eobtaine dfro mth evalu eo f a ,w eca n useth edefinitio n

CO

in which 2 S (u) = lim TT %£ <4-3> x -, Au isth epowe rfo ra give nfrequenc yband .I nou rexample ,however ,th e integralha st ob ecalculate dfo ra smalle rband ,e.g .

1 1

*'" ¥ 0.03 x

Thevariou scoefficient so fvariatio nmentione di nliteratur ean dcalcu ­ latedi nou rresearch,concer nvalue so fgreatl ydifferin gsituations , makingi tdifficul tt otranslat ethes efigure sint opowe rspectra .Ther e are,however ,n ospecia lreason st oexpec tmor epowe ri nspecia lfrequen ­ cybands ,excep ti nsituation swher ea systemati cvariatio ndue ,fo rinstance , todrainag eo ra repeatin gsoi lvariatio noccurs . Closet ozer other eha st ob emuc hvariatio ndu et oth emea nleve l variationstha toccu rever ytim eth ecombin eharveste rstart si na nothe r field,wit hanothe rcro po rvariet yo runde rothe rsoi lfertilit ycondi ­ tions.Continue dresearc hi sdesirable ,bu tfo rou rpurpos eth econclusio n asstate dearlie rwil lsuffice .

Thesignal so fth emeasure dauge rtorqu erepresentin gth efee drat esigna l werestudie dfo rth efrequencie sgreate rtha n 1rad* s .Th emeasuremen t disturbancesar ethe nincluded .Figur e4.2. 2 showsa nexampl eo fsuc ha signala smeasure di n1978 .I nfigur e4.2. 3 anautospectru mo fa signa l periodo f15 0second si sshow na tdoubl elogarithmi cscale . Fromthi sspectru man dother s (seeappendix )showin gth esam echaracte ­ risticsi tca nb econclude dtha tther ei srelativel ymuc hpowe r (hence variation)i nth efrequencie slowe rtha n0. 6rad' s l andpeak si nth e frequencieso f 18an d3 6rad' s 1. Thesepeak sar ecause db yth erotatio n ofth eauge r (3.2s 1) andth e4 row so fauge rpin spenetratin gth ecro p fortransport .Th epea ka t3. 1rad' s isals ofoun da teac hspectrum .A 87 possible explanation isth econveyin g action ofth ereel . From theplo t of theautocovarianc e function in figure 4.2.4ca nb e con­ cluded that theautocorrelatio n decreases very rapidly with time lag,s o

FS kgs-1 6-

10 15 20 25 time s = distance m

Figure 4;2.2. Variation in straw feed rate at constant machine speed of 1m* s *i nwinte r wheat (anouska) atFlevopolder s in197 8

20-1*10~ 3

10-

5-

0-5

0.2

0.1 0.050. 1 10 20 frad -

Figure 4.2.3. Autospectra ofmeasure d walker loss ( )an d measured auger torque ( )fo rdat a averaged per0.0 5s an dfo ra period of 180 s Barlett window 10%(se eappendix )

88 -0.1 T 1 1 1 r -2.5-2. 0-1. 5 -1.0-0. 5 0.5 1.0 1.5 2.0 2.5 LAGs Figure 4.2.4.Autocorrelatio n function of straw feed rate ( )an d walker loss ( )signal s aswel l as crosscorrelation Data averaged per the delay is corrected up toth e difference of 1 s.a averaged per 0.25 m for a total stretch of 187.5m (see A 4.2.)

that after about0. 4 s the levelha s dropped to 1/e,s o that the prediction of feed rate based on ainstantaneou s measurement ispoor .

The following conclusions canb e drawn. 1.Th ehigh-frequenc y variations inmeasure d feed rate include a large deal ofmeasuremen t disturbance causedb y the design of the auger and redistribution at the auger,whic hmake spredictio n of high- frequency variations of feed rate based on themeasuremen t of auger torque difficult. 2. Itca nb e expected, on thebasi so f the lesuits given in paragraph 3.1, that the accuracy of the relation of auger torque to straw feed ratewil l increase with the lengtho f the averagingperio d of the signal,wit h the result that it is the low frequency variations,whic h arebes t estimated. 3.Th emos t important feed rate variations are the low frequency variations and change inmea n level between various fields.

89 Model of the disturbances in feed rate

Thefee drat ei son eo fth edisturbance si nth eproces stha tha st ob e controlled.Variou scontro lsystem swil lb ecompare di nthi sstudy ,s otha t thecalculation shav et odea lwit hth esam ekin do ffee drat edisturbance s foreac hcontro lsystem .On eca nus erandoml ygenerate ddisturbance sfo r thispurpos ebut ,a swa sstate dearlie rth echaracte ro fth edisturbance s hasno tbee nintensivel ystudied ,s otha tth ecompositio no fth edisturbance s wouldb edifficul tt oestablis han dempirica ldisturbance scoul db euse d tobette rpurpose .

Forthi sreaso ndat afile so fapparen tstra wdensit ywer emad efro mfiel d measurementsobtaine dwit ha combin eharveste r (typeB )o fth eIJsselmeer - poldersDevelopmen tAuthorit ylarge-scal egrai nfarm .Th edetail sar eex ­ plainedi nA 4.2.I.e .Th emea nvalue so fth eapparen tstra wdensit yar ecal ­ culatedfo reac h0.2 5m traverse di n8 fiel dtest so f 187.5m . Themachin eoperato rha dbee ninstructe dt owor ki nth ewa yh ewoul d havedon ei fther ewer en oregistratio no fdata ,s otha tth einformatio n ona realisti cmanual-contro lsituatio nwa sals oobtained .Tabl e4.2. 1 gives someinformatio no nth edat afile screate do fapparen tstra wdensit yi nth e sequenceuse di nth esimulations .

Table4.2.1 .Averag edat ao fth efiel dexperiments ,use dt ocalculat eth e inputfil eo fapparen tstra wdensit yan dmanual-contro lsituatio n FSAV= averag efee drate , VUAV= averag emachin espeed , SDAV =averag e apparentstra wdensity , WLAV= averag ewalke rloss .

Nr. Variety SDAV FSAV VUAV WLAV kg*m 2 kg*s * m*s * kg*s l 61 Anouska 0.49 2.81 0.96 0.007 39 Nautica 0.62 3.29 0.90 0.007 12 Nautica 0.66 3.81 0.99 0.016 55 Anouska 0.42 2.29 0.94 0.017 57 Anouska 0.45 2.53 0.95 0.030 52 Anouska 0.52 3.10 1.02 0.026 37 Nautica 0.49 2.89 0.98 0.050 33 Nautica 0.60 3.50 0.99 0.110

90 The simulations were donewit h CSMP IIIwit h a calculation interval of 0.1 s.Th e straw density values required for each step.were calculated by a function generator using linear interpolation technique to avoid negative values that are liable tob e createdb y interpolation techniques ofhighe r order at valuesnea r to 0. Using the values of apparent straw density averaged over 0.25 m, means thatvariation s with frequencies above about6 rad*s are reduced,assu ­ ming machine speeds of 1m*s _1. Itwa s concluded inA 4.2.l.b that thepower , hence the amplitude in feed rate variations of frequencies above 6.0 rad*s are reduced very rapidly.

Model of the feed rate measurement

In the model of the combine harvester, the momentaneousmachin e speed, the constant cuttingwidt h of 5.9 m and the straw density generated by the function generator of CSMP simulation language create the instantaneous feed rate at the cutter bar.Afte r a delay of 0.4 sth e straw reaches the auger and generates a "measured feed rate".Th e measurement errors were introduced into the model by white noise added to this feed ratewit h a default levelo f 20%o n the average valuementione d in table 4.2.1, based on resemblance to registered signals alone. To avoid disturbances in themea n level the noisewa s coloured by fil­ teringb y first-order high-pass filterwit h defaultbreakpoin t frequency of 0.1 rad's l. The same noise waspu t into the elevator displacement output,when thiswa s used asmeasure d feed rate.

4.3. DISTURBANCES INTHRESHIN G SEPARATION EFFICIENCY

Fromparagrap h 2.3.2 we know that the threshing separation efficiency is dependento n several factors.Thes e factors can be splitu p into three groups: a)machin e design and adjustmentvariables , b) feed rate of straw and c)proces s variables affected by cropproperties . In this research themachin e design and adjustment variables,excep t threshing speed, arekep t constant. The threshing speed will in some cases be the controloutput . The effect of straw feed rateha sbee n discussed inparagrap h 2.3.2 and

91 thevariation si nfee drat ei nparagrap h4.2 .Th edisturbance si nth eproces s variableswil lb econsidere di nth epresen tchapter .Th eproces svariable s inth emode lo fthreshin gar e NU, RPSan d BETA.Th econcav eadjustmen tan d kindo fcro pi sno tvarie di nthi sstudy ,s otha t NUan d RPSI aredependen t justo nfee drate .I nfact ,th ecro ppropertie sals owil laffec t NUan d RPSI, butther ewa sno tenoug hinformatio navailabl efro mfiel dtest s onwalke rseparatio nitsel ft oestimat emor etha non eparameter . Thethreshin gcoefficien t BETAi smos tsuitabl efo rconsideration ,a s thisfacto raffect sth erat eo fchang eo fseparatio ndu eno tonl yt ocro p propertiesbu tals ot othreshin gspeed .

Thevariatio ni nthreshin gseparatio nefficienc yca nb edu et oa numbe ro f causes,fo rinstanc e 1)grai npropertie saffectin gth eforce sbindin ggrain st oth eear .Impor ­ tantvariable sher ear eth ekin do fcrop ,variety ,ripeness ,moistur e contento fgrain ,change si ntemperatur ean dmoistur econten tfo rsevera l daysbefor eth eharvest .Th elate rth egrain sar edislodge dfro mth eear s inth ethreshin gcylinde rth eles schanc ethe yhav eo fbein gseparate dfro m thestra wan dpassin gthroug hth econcave . 2)Th estra wpropertie saffectin gth eseparation .Som eimportan tvariable s herear eth ekin do fcrop ,variety ,ripeness ,moistur econten to fgrain . 3)Th estra wfee drat eha sbee ndiscusse di nparagrap h2.3 . 4)Th eamoun to fweed si nth estra wwhic haffect sth eseparation . 5)Th epositio no fth eear si nth estra wlayer . 6)Th edirectio no fth este mo fth eear si nrelatio nt oth edirectio ni n whichth eea ri saccelerate db yth ethreshin gbars . 7)Th edistributio no fth estra wan dear sove rth ewidt ho fth econcave . 8)Th espee do fstra wintak ean dtha to fth ecro pi nth espac ebetwee nth e threshingcylinde rbar san dth econcave . 9)Concav estoppag edu et owe tcondition san da larg eamoun to fweed si n thecrop . 10)Noncontrolle dvariatio ni nthreshin gcylinde rspee ddu et oengine-spee d variation.

Thevariatio ni nseparatio nefficienc yca nb esubdivide dint ohigh-frequenc y disturbancesdu et orando mprocesse smentione dunde ritem s5 t o1 0abov e andlow-frequenc ydisturbance s oreve nchang ei nmea nlevel ,owin gt o changei ncro pproperties ,t owhic hpoint s 1t o4 abov erefer .

92 Thehigh-frequenc ydisturbance sar eno tye tquantified ,becaus ethe y dono taffec tth emea nleve lo fseparatio ncalculate dove rsevera lseconds , theperio dove rwhic hth eseparatio nwil lb eaveraged . Thelow-frequenc ydisturbance sar equantifie db yparamete restimatio n overeac h 187.5m tes tru ni nth esimulatio n (seechapte r 6). Thevalue s areliste di ntabl eA 4.2.1.3 .Th eeffec to fthes evalue so nlosse sar e showni n4.6 ,bu ti tshoul db eborn ei nmin dtha tth eeffec to f BETAo n walkerlos si simportant .Fo rinstance ,i fth ethreshin gseparatio neffi ­ ciencydrop sfro m0. 9 to0.8 ,th eamoun to fgrai ndelivere dt oth erotar y separatoran dstra wwalker si sdoubled ,s otha twalke rlos swil lb edoubled , aswell .

Thevariatio ni nlow-frequenc ydisturbance sca noccu rwithi na fe wseconds , whenth esoi lpropertie so rmoistur epropertie ssuddenl ychange ,causin g croppropertie st od olikewise .I nthi sstud ythe yar esimulate db ycon ­ nectingth edat afile so nth evariou scro ppropertie st oeac hother ,BETA and WEPchangin gwithi na fe wsecond s (see ch. 6). Thisi ss osimulate d becausei ngeneral ,th edisturbance sca nb eregarde da slow-frequenc yvaria ­ tionsan dsudde nchange si nmea nlevel .Thi ssignifie sthat ,fo rcontro lpur ­ poses,th ethreshin gseparatio nitself ,o rth eresultin gwalke rloss ,ca n bemeasure dwit ha naveragin gperio do fabou t2-1 0s ,s otha tth econtro l canb equas istead ystate .

Themeasuremen to fthreshin gseparatio ni sbase do na theoretica lsystem , theaccurac yo fwhic hi sno tye tknown .Th emeasurin gerro ri sassume dt o berandom ,wit hwhit enois echaracteristics ,whos emaximu mamplitud ei s 0.06 arounda separatio nefficienc yo fabou t0.85 .Th enois ei scoloure d byfilterin gb ymean so fa high-pass ,first-orde r filterwhic hha sa break ­ pointfrequenc yo f0. 1rad* s 1.

4.4.DISTURBANCE SI NROTARY-SEPARATO REFFICIENC Y

Notmuc hinformatio ni savailabl eo nth evariatio no fth eseparatio no f therotar yseparator .Th eonl ydat atha tca nb euse dar ethos eplotte d infigur e2.3.3.1 .I tca nb econclude d fromthes edat atha tcro pproper ­ tieswil laffec tth erelatio no ffee drat et oseparatio nefficiency ,s o thatlow-frequenc ydisturbance so r mean-valuedrif to fthes eparameter s willoccur .

93 Change in thekin d of cropo rvariet y will give otherparamete r values,bu t in this study only wheat is taken into consideration, sotha t the mean levelwil l not change much. High-frequency disturbances will occur forth e same reasons as mentioned inparagrap h 4.3. For thepurpose s of thepresen t study the relation of feed rate to separation efficiency isassume d tob e constant.

The disturbances thatoccu r in thepractica l situation are simplified for the simulation model tovariation s in BETA in the threshingproces s and WEPi n thewalke r separationprocess .

4.5. DISTURBANCES INWALKE R SEPARATION EFFICIENCY

Walker separation, like threshing separation, isdependen t on the three following groupso f factors: a)machin e design and adjustment, b) straw feedrate , c)proces s factors affected by cropproperties . The design and adjustmento f the machine are notvariabl e in our study. The straw feed rate is avariabl e asha s already been explained. The process parameters affected by croppropertie s and other variable conditions will be considered in this chapter.

Thewalke r separation isth e only dynamically tob e modelled process in the combine harvester as isshow n in chapter 2.Thes eproces s dynamics are modelled by a first-order transfer in the straw feed rate and by the delay of strawo n thewalkers . The time constant of the first-order transfer was estimated tob e 0.8 s. Notenoug h details of the dynamic process transfer are available to enable us todiscus s a variation of this constant. Further research has tob e done on this subject. More information is available on the variation of the time delay. From A 2.3.2.4.d and A4.2.1. C it is seen that the delay varies considerably owing to the stoppage of the straw at the curtain in front of the walkers.Th e speed of the straw at the walkers alsovaries . In field observations amea n speed of 0.5 m*s was registered. In laboratory research by Gubsch (1969) the speedwa s found tob e depen­ dento n straw feed rate and the slope of the strawwalkers .A t a straw feed

94 rate levelo f 1.6 kg^s'1'!!!* th e speed varied from 0.35 to 0.66 m*s *.A t a straw feed rate level of 4.7 kg#s 1#m *th e speed varied from 0.64 to 0.77 m*s .Whe n the slope was changed,the speed changed too.Unde r Dutch harvest conditions the slope isalway s about 0, so that this isno to f any importance.

The time the straw remains in themachin e was studied in some of our field tests (Wevers, 1972)b y measuring the displacement of coloured straw to the ground. Inmachin e A,wit h winter wheat,a variatio n between 7.0 and 13.0s wasmeasure d around the mean value of about9.7 5 s.Thi s variation can be explained by both the stoppage at the curtain and the speed of the straw on thewalkers ,becaus e the speeds elsewhere in themachin e are roughly constant. This effect isver y importantbecaus e it impedes themeasuremen t of the relation of loss-to-straw feed rate.Fo r thispurpos e an averaging time of loss and feed rate of at least8 swoul d be necessary to calculate a stable loss-feed rate relation (seeA 4.2.1). In 4.7 anumbe r of results on loss- to-feed rate estimation willb e given.

The disturbances inwalke r separation will have the same character as threshing separation and rotary separation.No t only high-frequency random disturbances,bu t also low-frequency variations and changes inmea n level of the separation occur. The random variations are mainly causedb y the redistribution of the straw on thewalker s in the longitudinal and transversal directions.Th e low-frequency variations are due topropertie s of the grains aswel l as those of the straw. Thesepropertie s are dependent on the kind and variety of grain, ripeness and moisture content, surface moisture from dew and rain and weathering of the straw.Th e croppropertie s canb e established from various physical properties, such as friction, strength, straw length distribution and soon , but itprove d tob e very difficult to explain walker losses by the values of these properties (Huisman, 1978). The grain-straw separation process onwalker s isver y complex andno tpredictabl e on thebasi s of the known physicalproperties .

95 4.6.VARIATIO NI NWALKE RLOS S

Thevariatio ni nwalke rlos si sth eresul to fth edisturbances ,drif tan d suddenchang eo fmea nleve li nth eparameter sdeal twit hi nth epreviou s sections.Th eprocesse so fgrai nseparatio na tth ethreshin gcylinder , rotaryseparato ran dstra wwalker sal ldepen dclosel yo nth estra wfee drate . Theexten tt owhic hstra wfee drat eaffect seac ho fthes eseparatio nproces ­ ses,wil ldiffe ra grea tdeal ,henc eth eexten tt owhic hthe yaffec twalke r lossvaries ,bu ta nincreas ei nfee drat ewil lalway sresul ti nincreas e ofloss . Theimpac to nwalke rlos sb yth ethreshin gcylinde ri sver yimportan t becauseabou t70-99 %o fth egrai nflo wi sseparate dher efro mth estra w flow.Thi si sver yofte nforgotten .Th ewalke rseparatio ni sresponsibl e forhig hlosses ,especiall yunde rwe tcondition san dunde rthos ei nwhic h thestra wi sshortene do rspli tb yth ethreshin gactio ni nsuc ha wa ytha t separationbecome sdifficult .Mostl ya nincreas ei nmoistur econten tha s theeffec to fincreasin gth eloss ,bu ti nsom ecase sth erevers erelatio n ismeasured .Surfac emoistur eo fth estraw ,eithe rfro mde wo rshor tperiod s ofrainfal li smor eimportan ttha nth eaverag emoistur econten ti nwhic h themoistur ei sa nelemen to fripeness .

Figures4.6. 1 and4.6. 2 showgoo dexample so fthes ephenomen abase do n resultso ffiel dtest sobtaine dwit hmachin eA i nwinte rwhea t (Snel,1977) . Atthes etest sth emachin espee dwa sconstan tan dth esam ei neac htest , sotha tfee drat ewa smaintaine da ta fairl yconstan trat eo fabou t2. 5 kg*s_1.Th ewalke rloss ,th estra wmoistur econten tan dth eai rhumidit y inth ecro pa t0. 5m abov eth esoi lar emeasure ddurin gon eevenin gan d thefollowin gevenin gan dnight . Onth efirs tnigh t (figure4.6.1 )th emoistur econten tdi dno tchang e much,bu tai rhumidit yincreased .I nthi scas eth esurfac emoistur eaffecte d strawpropertie ss oa st oreduc eloss . Infigur e4.6. 2 therei smor escatte ri nth edat abu tth egenera leffec t wastha tlosse sincrease da tth een do fth enigh tan d thenfel lrapidl y whenth eai rhumidit yan dcro pmoistur edecrease dthank st oth esunshine . Thesedifference sar eals ofoun di nth ecours eo fth eday . Fedosejev (1969)als opresent sfigure so ftha tkind .

96 WL 10- 9- 8- 7- 6- 5- U- 3- 2- 1 0L^ V 18 19 20 21 22 timeh

Figure4.6.1 .Walke rlos s (WL, o—) relatedt ostra wmoistur econten t {MCS, '—) andrelativ eai rhumidit y (RAH,x )a sthe ychange ddurin g the testsi nwinte rwhea ti n197 6a tth esam eforwar dspee d

WL g-s-i 10- 9- 8 7 6- 5- U 3- 2- 1- 0M ^ 20 21 22 23 2U

Figure4.6.2 .Se efigur e4.6. 1bu tfo rtest sdurin ga nothe rnigh ti n 1976,howeve r

97 Thedat ao ffiel dtest swit hmachin eA i nth eyear s 1970.. .197 6wer e investigatedi nsearc ho frelation sbetwee ncro ppropertie san dwalke r loss (Huisman,1974b) .Findin gth erea lrelation sprove dt ob eto ocomple x atask .I nth epresen tstudy ,i ti sonl yimportan tt olear nth eexten to f thevariatio no fth eloss ,t ose eth etota leffec to fseparatio nprocesse s inth ecombine . Thetest swer ecarrie dou teac hyea rthroughou tth eharves tseasons , todiscove rho wth ecro ppropertie svarie di npractice .Th efee drat e wasals ovarie dfro mlo wt oth ehighes tleve ltha tcoul db eachieved .I n figure4.6. 3 theresult sar eshow no flos sa sa functio no fstra wfee d rateo nth esam escal es otha tth edifference sbetwee nth eyear san dth e cropsbecome sver yclear .

Measurementswer eals ocarrie dou twit hcombin eharvester so ffarmer san d contractorsan dshowe dth esam evariation .A tabl ei sgive ni nA 4.6.4 , showingwalke rlos smeasure di n198 0whic hvarie dfro m0.7 5t o232. 0kg'h a l, whilestra wfee drat epe rmetr ewidt ho fthreshin gcylinde rvarie dfro m 0.5 to1. 9kg-s -1'm-1 (Dongen,1981a) . In197 2th esiev ean dwalke rlosse swer esumme du p (Jansen,1972) .Th e totalamoun tvarie dfro m3. 3t o418. 0kg'h a 1o fwhic hth ewalke rlos s contributedth egreate rpar tt oth etota li neac hcase .Th edetail so f thisresearc har eals ogive ni nA 4.6.4 . Figureso fthi skin dar eals ofoun di nliteratur e (Anonymus,1969 ; Brown,1967 ;Klinner ,1979) .I tca nb econclude dfro msuc hresearc htha t thelosse svar yver ymuc hi npractice ,no tonl ybecaus eo fth evaryin g circumstances,bu tals obecaus eth efarme rdoe sno tchec kupo nhi slos s intensively.I nmos tcase sth efarme rdoe sno teve nkno wwha tlos sleve l heshoul dtr yno tt oexceed .Thi sca nb eunderstoo dwhe nw econside rtha t lossmeasuremen ti sver ydifficult .Farmers ,wh oow na grai nlos smonitor , arebette rawar eo fth elos sleve lthe yinten dt owor kwith .

Theloss-to-fee drat erelatio ni sa ver yimportan tthin gt okno wa sregard s speedcontrol ,b ei tmanua lo rautomatic .Knowin gthi srelation ,i nfact , meanstha tth eseparatio nparameter sar eestimated ,an dca ntherefor e beadapte dt oth edisturbanc eo fthes eparameters . Iti sgenerall yclaime di nliteratur ean dconfirme db you rresearch , thisrelatio nbein gexponentia l (Huisman,1974b) . (Seeals oth egenera l shapeo fth escatte ro fth emeasure dvalue si nfigur e4.6.3. ) 98 1 WL kg.s- WL kg.s-' 1973 0.2 5- 0.05-

x Orfi** ° u

0.20- 1970 0 1 2 3 4 ;• 5 6 FS kgs-'

1 0.15 WL kg.s- 1974 0.2 5-

0.10 - * + 0.20 + .+ + 0.05 0.15

5 6 0.10 FS kg.s-1

0-05 0.2 5- X °o°

*** xx.

0.20- X* 5 6 FS kg.s-1 1971 *x 0.15- Xx X VW. kg.s- X 0.05- X X X 1975 & X 0.10- x X x**ï 5 6 FS kg.s-1 0.0b - LW.kg.s-' x^lLäÄ? *x * 0.05- _ .—xJxËË 1976

X X FS kg.s- .,T_J*1*; * 5 6 WL kg. s- FS kg.s-1 010-

-aaa 0 1 2 3 4 5 6 FSkas- 1 Figure4.6.3 .Walke rlos s [WL)relate dt ostra wfee drat e [FS) formachin e Ai ndifferen t crops (+= oats ,x = winte rwheat ,o = sprin gwhea t inth eyear sindicated . In1970-197 2th estretche sconsidere dwer e5 m i nlength , in 1973,1974th estretche sconsidere dwer e4 0m i nlengt h andi n 1975,1976th estretche sconsidere dwer e3 0m i nlength . 99 Nyborg,1968 ,foun dth ebes tfi tfo rthe-.percen tlos s= a(fee drate ) equationb ylinea rregressio nanalysi so fa larg eamoun to fexperimenta l datafro mliterature .Unde rwester nEuropea ncondition sthes econclusion s areals odraw nbu tth eequation :los s= a«exp(b'FS )fit swell ,to o(Goss , 1958;Baader ,1966 ;Anonymus ,1967 ;Lint ,1968 ;Kroeze ,1970 ;Eimer , 1974b;Claesson ,1972 ;Anonymus ,1976) .Whe nth euni to flos si skg' s 1 orkg*h a thesam eequation sca nb euse da swell . Ifth efeed-rat erang ei ssmal la linea rrelatio nwil lals oserve , beinga smal lpar to fth eexperimenta lrelation .Thes econclusion sar ei n conformitywit hth emode lo fth ecombin eharveste ra swil lb eshow ni n chapter6 .

Forsimulatio no fth edisturbance so fth eseparatio nparameter sfo rth e model,realisti cdat aar eneeded .Th eparameter sshoul db echose ns otha t thevariatio ni nlos scurve sar ei nconformit ywit ha wid elos srang e arisingfro ma realisti crang eo fcro pproperties . Therang eo flosse sincurre di nth efiel dexperiment sshow ni nfigur e 4.6.3wa shel dt ob erealistic .Eigh ttes trun swer eselecte do nthi sbasi s fromth eavailabl erun so fth efiel dtest so f 1978.Th edetail so fth e methodo fcalculatio nar egive ni nA 4.2.2 . Thelos scurve so fth eselecte dtes trun sar edraw ni nfigur e4.6.4 . Therear elos scurve sshowin gsmal llosse sa swel la slarg eone sroughl y inth esam erati oa smeasure dlos soccurred .The yca nb ecompare dt oth e measureddat agive ni nfigur e4.6.3 . Thesecurve sar eo fexponentia lshape : WL= exp {Do+D\'FS). Thevalue s of DQan d D\ aregive ni ntabl eA 4.2.1.3 .The yrepresen tvalue scalcu ­ latedb ylinea rregressio no fth evalue so flos san dfee drat eaverage d over8 m .Thi saveragin gdistanc ewa srequire di norde rt ofilte rou tth e stochasticvariatio ni nlosse sdu et oth erando mdisturbance si nth ese ­ parationprocesses .Averagin gdistance so fmor etha n8 m di dno tchang e thecurve smuch ,bu twhe nshorte rdistance swer eused ,th ecorrelation s deterioratedan dcurve sdeviate da sa result . Ifth eloss-to-fee drat ecurv eha st ob eestimate db yth econtro lsyste m onth ecombin eharvester ,specia ltechnique shav et ob edeveloped .Furthe r researchi nthi ssubjec ti snecessary .

100 0.10-

0.05 -

Figure 4.6.4. Curves ofwalke r loss (WL) related to straw feed rate (FS) calculated by linear regression of the equation In Wl = DO + Dl'FS of of the selected test runs (seenumber ) used for the simulation

4.7. CONCLUSIONS

The most frequently occurring type of disturbance in theprocesse s of separation in the combineharveste r is low-frequency disturbance and sudden changes in themea n level in those cases inwhic h the harvest is tob e started in another field or on another day. There is ahig h degree ofmeasuremen t disturbance in frequencies/tha t arehig h compared to those in the above-mentioned process disturbances.Thi s means that,fo r good 'measurement, filter action with a large time constant isneeded . More field research isneede d to establish the optimal filter techniques. For simulation of the control systems deterministic disturbances are calculated. On comparison with the variability measured over anumbe r of years, they seem tob e realistic.

101 5. Control systems

5.1. INTRODUCTION

5.1.1. General

The aim of the control system is stated in chapter 1a s theminimisatio n of the cerealharves t costsb y control of themachin e speed and the threshing cylinder speed. The financialbenefi t of automatic control compared to a manually controlled system, depends onho w correctly theoptimu m speed level canb e calculated and onho w capable the system is of realizing a relatively small deviation between the calculated optimum level and the actual speed. The correct choice of the leveldepend s inparticula r on the correctness and extento f the used information, thati s the control inputs. The correctness dependson : 1)th e costinformatio n of the cerealharves tparameters , 2) the choice of the inputvariables , 3)th e observability of the inputvariables .Thi s refers to the accuracy and integration time of themeasurements . By the extent of the used information ismean t thenumbe ro fmeasure d or calculatedproces sparameter s taken into consideration. The differences between calculated optimum speed and actual speed will be minimisedb y speed feedback control systems.Th e extent towhic h the system really works atminimu m costs isdetermine d by its controllability. For the combine harvester there are some unfavourable conditions,suc has : a) The time delays arequit e large in theprocess ; 0.4 s for the straw feed rate and 10s for the grain losses after the intake.Moreove r these are not constant. b) The observability is lowbecaus e of the low signal/noise ratio. For these reasons the speed can onlyb e controlled for low-frequency dis­ turbances, so that aquas i steady state approach canb e established for calculation of optimum speed.

103 5.1.2. Models for control system design

5.1.2.1. Models

The models of the relevantprocesse s in the combine harvester, considered in chapters 2an d 4 arepresente d briefly togetherwit h the disturbances in figure 5.1.2.1. From this it is clear thatbot h themachin e speed VM and the threshing cylinder speed VTaffec tth ewalke r loss ML. Thesieve , threshing andbreakag e losses are leftou to f further consideration as they are relatively small compared to thewalke r lossi n general. In con­ ditions of relatively high sieve loss the totalo f sieve andwalke r loss canb e taken as input.Th e remaining adjustableparameters ,suc h as the concave adjustment and the walker frequency are not variable in thisstudy . Itha s tob e realized that the transfers of theprocesse s arenonlinear , so that the disturbances have nonlinear effects on loss.

*sd •pt rPs threshing separation proces proces *5 variables*^* varibles+ K>

VM Pfeedrate FS '1 FS= SD"CL»VM f^

VT Pthreshin g TSE Pseparation tWL TSE=g(FS.VT) WL=g(TSE.FS) L. Disturbanceso f measurement \FSM ITSEM \WLM

Figure 5.1.2.1. Simplified scheme ofproces s (P), disturbance s (Z)an d measurement ofvariable s (FSM, TSEM, WLM) , g =nonlinea r functions

The control input factors are:th e straw feed rate FSM, the concavesepa ­ ration TSEM, and thewalke r losses WLM.Th e Mi sadde d to indicate the addedmeasuremen tnoise . When the inputvariables ,th e cost factors ofmachin e and crop and the cost criterion mentioned in chapter 1ar e combined in acost-minimi ­ sation calculation, this should result inoptimu m values for the driving speed VM and the threshing cylinder speed VT . Two feedback speed controls will ensure that the actual speeds VM and VT will follow the optimum

104 speeds. The subsequentmodel s of the control systemswil l systematically use more inputvariable s or control more output variables in the following way. System 1, the loss control system, isobtaine d when the measured loss WLMi suse d as the input signal and VM becomes the output of the optimum speed calculation (see figure 5.1.2.2). The VM is the actualmachin e speed, that is the outputo f the controlwhic h is also used as input for the cost minimisation.

VMa Pvw Proces •—J I—

\ • VWLM VM Clw J s;— t Cost minimisation Figure 5.1.2.2. Loss control (system 1) P =process ,C control, VM =optimu m machine speed, VM = actual machine speed

System 2, the loss feed rate control also controls justmachin e speed but, for reasons of observability and controllability, uses the measured feed rate FSMa s inputi n addition to WLMan d VM(se e figure 5.1.2.3).

VMa PV Proces

1 1 i ,FSM ,WLM VM, Cl'M WV Cost minimisation

Figure 5.1.2.3. Loss feed rate control (system 2)

In thepreviou s systems the threshing cylinder speed VTi s fixed. If this speed is also controlled on thebasi s of the inputvariabl emea ­ sured feed rate, FSM, then system 3 isobtained , that isth e loss feed rate cylinder speed control (see figure 5.1.2.4).

105 P/M Proces P/r

WLM 1/7, VMa FSM CvT HS cw|»-o* VW, Cost minimisation

Figure 5.1.2.4. Loss feed rate cylinder speed control (system 3)

VTQ= optimum threshing speed, VT =actua l threshing speed

If, in addition to this, the threshing separation efficiency TSEMi s used as inputi n the costminimisatio n criterion then system 4 is the result, that is the so called loss feed rate threshing separation control (see figure 5.1.2.5).

VMa PVW VTg] Proces PVT T~ VMa FSM JTSeMjyfLM cvr lyr. £w]«-<> -# VM. Cost minimisation

Figure 5.1.2.5. Loss feed rate threshing separation control (system 4)

5.1.2.2. Observability and controllability of the control output variables

Various parameters have tob e measured in order to control the systems mentioned above.Fro mpreviou s chapters the following review canb e given below,togethe rwit h the conclusions as to controllability: VT. The measurement of the threshing cylinder speed canb e performed rather accurately. VM. The value of the machine speedwil lb e used in the optimisation calculation,multiplie d by the cutting width. The product canhav e a steady state deviation of atmos t 5%. This isbecaus e of slipwhic h depends on the soilpropertie s and themas s in the grain tank andbecaus e of the assumed constantworkin g width.

106 FSA. There isa n unknownmeasuremen t noise component in the straw feed rate measured by auger torque.A n estimation hasbee n made of the correlation between straw feed rate and auger torque,varyin gbetwee n 0.6 and 0.9 for frequencies below 0.63 rad's 1 (see 3.1.2). The measurement of the feed rate by auger torque isdelaye d 0.4 s compared to the intakemomen to f the feed rate. The covariance function shows a time constant alsoo f about 0.4 s. Hencepredictio n of the feed rate isbad . The combination of delay and measurement noise makes itdifficul t to control the high-frequency distur­ bances. Only the low-frequency disturbances canb e controlled sufficiently.

TSE. Inmeasurin g the threshing separation efficiency,measuremen t noise canb e expected aswel l as variation caused by the varying grain-to-straw ratio (see 3.4).Th e measurement isexpecte d tob e only reliable for the low-frequencypar twit h an estimated error of 0.03 at the level of about 0.85. Thismeasuremen t alsoha s a time delay of about 10s . WL. The variation of the time delay of the straw on thewalker s is responsible for a considerable amount ofmeasuremen t noise onwalke r loss. Themeasuremen t technique also introduces a considerable amounto f noise in thehig h frequencies.Onl y the variations of the frequencies less than about 0.2 rad's 'ca nb e measured reliably. The variations inwalke r loss as a consequence of disturbances in the separation processes Z and Z are also of low frequency. Generally these variations occur in the frequency rangebelo w roughly 0.2 rad's (see4.6) .

The influence of straw feed rate onwalke r loss isnoticeabl e in the frequency below the estimated level of 1.25 rad's ' (first-order process with T = 0.8).Th e variations in straw feed rate,i n frequencies between 0.15 and 1.25 rad's 1 are,despit e the disturbances,mor e or lessmeasu ­ rable by auger torque.Moreover , themeasuremen t of the auger torque takesplac e 10.1 sbefor e measurement of the corresponding loss. From thepoin t of view ofmeasurabilit y and controllability it is attractive for these reasons topredic twalke r lossbase d on auger torque and estimates of theparameter s of the transfers of the separationprocesses . The following equation,base d on field measurementsmentione d in chapter 4 hasbee n chosen for this. WL{t) = cz-exp{2>-FS(i-lo.l)} (5.1) An estimate of a andb canb e made after filtering the high-frequency noise outo f themeasurement s of loss and feed rate.Thes evalue s can then be used in the costminimisatio n criterion,resultin g in abette r esti-

107 mationo fth eslop eo fth elos scurv ean dconsequentl y ina nimprove d optimummachin espeed .

5.2.COS TMINIMISATIO N

Themai ndisturbance sar elow-frequenc yones .The yca nb econtrolle db y adjustingth emachin ean dthreshin gspeed st olevel scalculate di na cost - minimisationalgorithm .Th eprinciple so fthi salgorith mar eworke dou t inthi schapte ra srequire dfo rth esimulations .I fthes ealgorithm sar e usedi npractica lcontro lsystems ,th ecalculatio ntechnique smus tb e adaptedfo rus ewit hmicroprocessors . Thecalculatio no foptimu mmachin espee di sno tth esam ei nsystem s 1an d2 .Th eprincipl ean dprocedur ei smos tclearl ydemonstrate di n system2 ,s otha ti tshoul db edeal twit hfirst .

5.2.1. Optimum machine speed calculation for system 2

Thepoin to fminimu mcost so fth eoptimisatio ncriterio nca nb ederive d fromth eshap eo fth etota lcos tcurve so fth emachin ean dlos scost s (seefigure s1.4.1. 2an d 3).A ta nincreasin gharveste dare a VWth ecos t curveo fth e machine costs descendsi ncos tsituation s5 an d6 ,i naccor ­ dancewit hth eequation sderive dfro m2.2 ,givin gtota lmachin ecost s(CM) asth esu mo f MVC, HVCan d MFC,s otha t CM = MVC+ (NE'0.36+l/VW)'Ki (5.2) inwhic h „ WA AFC-VM'CL 1 0.36 AAN'iNE'VMN'CL'0.36+ 1) l ' Thecos tcurv eo f walker loss ascendsi naccordanc ewit h VWL= Kz'a-exp{b-FS)/VW (5.4) inwhic h Kz= lOOOO'^ i (5.5) Thetota lo fbot hfactor sgive sth etota lcost s TC= CM + VWL (5.6) Theminimu mcos tpoin toccur sfo rtha tvalu eo f VWa twhic h d(TC)/d(VW) =0 (5.7) sotha t d(CM)/d(VW) + d(VWL)/d(VW) =0 (5.8) Itca nb ederive dfro m (5.2)tha t d(CM)/d(VW) =- Ki/VW2 (5.9)

108 Itshoul db erealize di nth ecalculatio no f d(VWL)/d(VW) that FSi sa functiono f VW,namel y FS = SD'VW (5.10) sotha twit h (5.4)w ege t

d{VWL)/d{VW) =d(K2>a-exp{b-VW-SD})/d{VW) = (5 lia) 2 or d{VWL)/d(VW) = K2-a'exp{b'VW-SD) • {b-VW'SD-1)/VW (5. lib) 2 hence d(VWL)/d{VW) = K2'a'exp[b-FS) • {b-FS-l)/VW (5. 12) Insertingbot hderivative st o VW,(5.9 )an d (5.12)i n (5.8)give s 2 2 - Kx/VW + K2'a-exp(b-FS) •(b'FS-l) /VW =0 (5 13) or K\ = K2'a-exp(b'FS)- (b'FS-l) (5 14)

Thederivativ et o FSo fth erigh than dpar to fthi sfunctio ni s

K2-b'FS'a-exp(b'FS) (5.15) Thisderivat ei salway spositiv ea s a'exp(b'FS) = WLand ,sinc ea negati\j e lossi simpossible , awil lalway sb epositive .Moreover ,th elos si s expectedt oincrease ,s otha t b ispositive ,too . Thismean stha tth erigh than dpar to fth eequatio nalway sincrease s withincreasin gFS ,startin gfro ma negativ evalu ea t FS =0 .Therefor e therei salway son esolutio nfo r FSfro mthi sequation .Thi si sth eoptimu m feedrat eleve lappropriat et otha tsituatio nfro mwhic ha noptimu m VW followsfo rever y SD.

FS . = SD'VW .. - VW , =~^- (5-16) opt. opt. opt. SD Itha sbee ncalculate dfo rth esituatio ngive ni nfigur e1.4.1. 2fo rth e losscurv eo fth efiel dtest so fth eAnousk awinte rwhea tvariety ,tha t #S =3.14kg* s 1 fromwhic hi tfollow sfo r WL(2)i ntha tcurve ,tha t VW = 7.85 m2's_1 and for VWHe) that VW = 6 Pft m2.=_1 opt. opt. u-^o m s Thenecessar yvalu eo f SDi nequatio n (5.16)ca nb ecalculate dfro mth e measuredvalue so fstra wfee drat e FSMan dharveste dare a VWM,namel ytha t SDM= FSM/VWM (5.17) Acomplicatio noccurs ,becaus ether ei sa tim edela ybetwee n FSMan d VWM. Actuallyi tapplie stha t SDM(t) = FSM{t+T)/VBHt) , etc. (5.18) Theinfluenc eo fthi sphenomeno ni sneglecte dbecaus ei ti ssmal lsinc e T= 0. 4an donl yth elow-frequenc yvariation sar eo fimportance .

Thecos tfunctio ni sa littl ebi tmor ecomplicate dfo rth ecos tsituation s

109 inwhic hth ecost so ftimelines slosse s CTIoccu r (situations1 .. . 4). Thecost so fthes etimelines slosse shav et ob eadde dt oth etota lmachin e costso fwhic hth efixe dcost scomponen t MFCi sno tdependen to n VW.I n thatcas e d[CM)/d(VW) = WA/[0.36'VW2) (5.19) CTIi sno tknow na sa functio nbu tfro ma functio ntable ,s otha t d(CTI)/d{VW) canals ob ederive dfro ma tabl ea sa functio no f VW.Thi s functionwa scalle d DTI.I nth esam ewa yequatio n (5.8)holds . d{CTI)/d{VW) + d(CM)/d{VW)+ d(VWL)/d(VW) =0 (5.20) sowit h d[CTI)/d(VW) =DTI an dbot h (5.12)an d(5.19 )w efin d 2 DTI'VW + WA/0.36= K2'a-exp(b-SD'VW) • {b'SD-VW-1) (5.21) Soher ealso ,fo rever y "measured" SDvalue ,on eoptimu m VWapplies .

5.2.2. Optimum machine speed ealeulation for system 1

Ifa syste musin gexclusivel yth einformatio nabou tdrivin gspee dan d loss weredeveloped ,the nth ecalculatio no fth eoptimu mspee dwoul db edif ­ ferent.The nth erelatio nbetwee nstra wfee drat e FSan dwalke rlos s WL isno tknown ,s otha tth edirec trelatio nbetwee nth eharveste dare a VW andwalke rlos s WLha st ob eused .Thi si sdifficul tt oascertai nbecaus e VWdoesn' tvar ymuc hwherea sth evariation si nstra wdensit yd ocaus e variationsi nth ewalke rloss . Thereforei ti sno tpossibl et oobtai na goo destimat eo fth eshap e ofth ecurv edescribin gth erelatio nbetwee n VWan d WL.Fo rthi sa greate r rangeo f VWshoul db eprocessed ;th eoperato rshoul dperfor mspecia lcurv e calibrationrun swhic hshoul db eregularl yrepeated .Thi si sver yimportan t sinceth eminimu mcos tsyste mi sestablishe db yth eslop eo fth eloss .

Ifthi sha st ob edispense dwith ,the nth eknow nleve lo fth elos san d theknow ngenera lshap eo fth ecurv eca nb ecombine dt oaone-paramete r lossmodel ,e.g . WL = e-exp(q-VW) (5.22) o doesn'thav et ob eestimate di nthi smodel ,bu ti sadjuste da ta lo wbu t realisticvalu et ole tth ecurv ealmos tpas sthroug h0 a talo wVW. The n

VWL= Kz-a-exp{q-VW)/VW (5.23) sotha t

2 d(VWL)/d{VW)= K2-{c'exp(q-VW)'(q-VW-l)}/VW (5.24) Now (5.24)ha st ob einserte di n(5.8 )an d(5.20 )i norde rt ocalculat e 110 theoptimu m VWfo r system 1. iti seviden t that the choice of cha s a great influence on the calculation of the optimum value of VWcalculate d accor­ ding to the minimum costprocedure ,a s inparagrap h 5.2.1. In fact, a is estimated in the case thata curve calibration run ismade .

5.2.3. Optimumthreshing speed calculation for control system 3

As indicated in 1.4.1 there isa noptimu m speed of the threshing cylinder when minimum costs arepursue d (see figures 1.4.1.4an d 1.4.1.5). The opti­ mum speed canb e ascertained foreac h feed rate level. The shape of the curve isinfluence d by the croppropertie s and the concave adjustment,tha ti s the distance between the raspbar s of the cylinder and the concave grate.Unde r given conditions (concave adjustment and cropproperties ) there willb e a relationship between the straw feed rate and the threshing speed atwhic h the losses,henc e the losscosts , areminimum . Eimer (1977)ha sworke d this out for anumbe r of different cropproperties .

Figure 5.2.3.1 shows lines of constant threshing separation deficiency, thisbein g the ratio ofnon-separate d grain to grain feed. The walker losses closely coherewit h this deficiency aswa s shown in 2.3. Here it concernswhea twit h strawmoistur e contents of 12%an d a grain moisture content of 14%,a grain-straw ratio of 1:1.75an d a concave adjustment of 16m m at the front and 8m m at the rear. In figure 5.2.3.2, curveshav e been drawn of the threshing loss for the same crop.Figur e 5.2.3.3 shows the appropriate curves for damaged seed. When these losspercentage s are embodied in the contribution to the loss costs,thi s results in curves of similar losspercentage s as those indicated by ( )i n figure 5.2.3.4.Th e threshing loss is completely incorporated,whil e thebroke n grain is incorporated to the extent of a 0.4thpar t asno tal lbroke n grain isworthless .Th e grain that is not separated by the concave ispasse d on at apercentag e representing the notb y thewalker s separated grainwhic h depends on the feed rate level. The most favourable combinations of feed rate and threshing speed are indicated by thehatche d field A in fig. 5.2.3.4. Hatched areas B and C originate in the samewa y for just ripe harvested wheat {MCS= 18%, MCG = 18%, GS= 0.8) andwhea tmoistene d after storage (MCS =26% , MCG= 22% , GS =0.7) ,respectively . The shortcurve s in the hatched area indicate the lines or the same total losspercentages . Ill 2 3 4 5 6 2 3 4 5 6 AFS kg.s-1m-1 AFS kg.s-1m-1

Figure 5.2.3".1. Figure 5.2.3.2.

l r 2 3 4 5 6 4 5 6 7 1 AFS kg.s-'m- AFS kg.s-1m-1 Figure 5.2.3.3. Figure 5.2.3.4.

Figure 5.2.3.1. Curves of constant concave separation deficiency (1-TSE) ofwhea tA related to threshing speed (VT) and specific feed rate (AFS) MCS= 12%; MCG= 14%; GS =0.6 ,concav e adjustment: 16/8m m

Figure 5.2.3.2. Curves of constant threshing loss ofwhea tA related to threshing speed (VT) and specific feed rate {AFS)

Figure 5.2.3.3. Curves of constant grain breakage ofwhea tA

Figure 5.2.3.4.Tota l corrected losspercentage s of wheatA ( )an d wheat B and C (/*"" " )hatche, d area shows optimum combinations (least loss) of VTan d FS. WheatA : MCS=12% , MCG = 14%,G S= 0.6; wheat B: MCS= 18% , MCG=18% , GS =0.8 ;whea t B: MCS= 26%, MCG= 22%, GS= 0.7 Line ( )i s VT= 20+ 2.4 AFS

112 Observationo fth ehatche darea sa tfee drate sbetwee n2 an d5 kg* s bringst oattentio ntha tthe yhav et osom eexten ta nequa lslop ea sth e lineso fa constant ,concav eseparatio ndeficiency .Thi si slogica l becauseth ethreshin glos san dth econcav eseparatio ndeficienc yhav e thisslope ,th equantit yo fbroke nsee di ssmal lan di sonl yimportan t ata hig hfee drate . Alin efittin gthes edat afairl yi s VT= I + 2.4-AFS. Thislin e isdraw ni nfigur e5.2.3. 4fo r &= 2 0an di sles sstee pwhe ncompare d toth econcav eseparatio ndeficienc y lines.Suc ha lin ei s VT=9+4.0'AFS fora concav eseparatio no f 10%o fth ecro pbelongin gt oth ehatche d areaA .

Theinfluenc eo fthreshin gspee dcontro lo nth efee drat eca nb eclearl y shownb yassumin ga threshin gspee d VTo f2 4m* s l at AFS= 2. 0kg* s *m . Thenth elos sa tcro pA woul damoun tt oabou t0.45% .I f FSincrease st o 4kg* s 1#m ',th elos swoul dris et o1 %a tth esam e VT. However,th elos s willdecreas et o0.9 %b yincreasin g VTt o3 0m* s .Th eadvantag ei s greaterwhe nth eslop eo fth eequa llos sline sdiffer sconsiderabl yfro m thato fth eoptimu mthreshin gspeed-to-fee drat erelationship .

Thebenefi to fsuc ha syste mha stw osources .I nth efirs tplace ,contro l ofth emea nleve lo fthreshin gspee di norde rt ooptimis ei naccordanc e withth elo wfrequenc ydisturbance san dmea nleve lvariation si ncro p propertiesaffectin gth ethreshin gprocess . Inth esecon dplace ,contro lo fth eactua lthreshin gspee di norde rt o adaptt oth evariation si nfee drat ea smeasure di nth emachine .Thes e areth evariation swhos efrequencie sar eabov eth ebandwidt ho fth efee d ratecontro lan da twhic ha fee dforwar dthreshin gcylinde rspee dcontro l cani nfac treact .Th edriv esyste mo fth ethreshin gcylinde rtolerate s ratherfas tchange si nspee dan dth emeasuremen to fth eauge rtorqu e takesplac e+^0. 9second sbefor eth ecro penter sth ethreshin gcylinder . Thebenefi ti sver ydependen to nth eaccurac yo fth emeasuremen to f thefee drate .A saccurac yi sbette ra tth elowe rfrequenc yvariation s thana tth ehighe rones ,th ebenefit shav et ob eexpecte dfro mcontro l ofth elowe rfrequenc yvariations .

Theconcav eclearanc eals oaffect sth econcav eseparatio nan dth ethreshin g loss.A continuou sautomaticall ycontrolle dadjustmen to fth eclearance ,

113 however,i sno tye tworthwhil ebecaus eth einfluenc ei sver ysmall ,accor ­ dingt oArnol d (1964)an dCasper s (1973),an dno tobviou ssince ,a ta greateradjuste ddistanc estartin gfro m4/ 2mm ,th econcav eseparatio n firstincrease san dthe ndecreases .Moreover ,th epositio no fth eoptimu m settingsdepend so nth etyp eo fcrop ,threshin gcylinde rspeed ,cro pintak e speed,etc .I fal leffect so fthreshin gcoul db emeasure dlik egrai nbreakage , threshingloss ,threshin gseparatio nefficienc yan dstra wdamage ,th e adjustmentcoul db eautomated .Muc hresearc hha st ob edon et odevelo p suchsystem .

Theconclusio no fthi schapte rwil lb etha ta threshin gcylinde rspee d controlca nmak ea contributio nt ominimizin gth elos scost san dtha tth e optimumspee d VT isdetermine db yth estra wfee drat ean dcro pproperties . Tothi sth efunctio nwhic happlie si s VT = VFL+ VFS'AFS, inwhic h VFL o hast ob echose no nth ebasi so fth ecro pproperties . VFS=2. 4m 2,kg lapplie st oal lth ecro pdeal twit hi nth eresearc hb y Eimer (1973)an d VFL= 2 4m -s i appliest owhea tB (justripe) .A threshin g cylinderspee dcontro lca nb ebase do nthi sequation . Eimer (1973,1974a ,1974b )applie dthi si npractic e (seeals oA 1.2) . Presumablyth eabov ementione dequatio nha sbee napplie di nthi ssystem , althoughi tha sno tbee nexplicitl ystated .Thi sequatio nwil lb euse d forth esimulatio no fcontro lsyste m3 .

5.2.4. Method for calculation of the optimum threshing cylinder speed for system 4

Croppropert yvariation swil lhav eth eeffec ttha tth erelationshi pbetwee n optimumthreshin gspee dan dfee drat ederive di nparagrap h5.2. 3wil l notb eoptima li nal lcases .Fo roptimisatio no fth emea nthreshin gspee d thisequatio nha st ob eadapte dt oth echang ei ncro pproperties .Th e equationi slargel ydetermine db yth econcav eseparatio ndeficienc ys o thisinformatio ncoul db euse dfo radaptio no fth edesire dequation . Otherfactor slik estra wbreakag eaffectin gwalke ran dsiev elos sshoul d alsob econsidered ,bu tthi si sa ver ycomple xmatter .Firs toptimisatio n willb eresearche dusin gth econcav eseparation .

Itca nb ededuce dfro mfigure s5.2.3. 1an d5.2.3. 4tha tth edeficienc y curvesar eno tcompletel yparalle lt oth erelatio n 18+ 2.4'AFS ,whic h

114 wouldb echose nfo rcro pA .However ,whe nth ethreshin glos san dth e walkerdeficienc yar eunknown ,th ecorrec trelatio ncanno tb ecalculate d either.Fro mth ewa yi nwhic hth ehatche d (optimum)are aha sbee nchose n forcro pA ,i ti sapparen ttha tth eare aha sn oprecis eboundary ,s otha t thecurv eo fabou t8 %deficienc yi nfigur e5.2.3. 1come srathe rclos e toit .

Onconsideratio no fth edeficienc ycurve so fth ecro pwit hwhic hCasper s (1973)performe dhi sresearch ,i tca nb econclude dtha tthes ecurve s correspondbette rt oth eoptimu mcurv eo fEime r (1977)a sfa ra sth eslop e isconcerned .Figur e5.2.4. 1show sthi scurve(curv e1 , )an dth e optimumarea sA ,B an dC a swel la sth e10 %(curv e2 , )an dth e 20% (curve3 . )deficienc ycurve so fEimer .A tth esam etim e thefigur eshow sth ecalculate dpoint so f 10%an d20 %deficienc yfro m themode lo fCaspers ,fo r BETA= 1.8 .Thes epoint sar ecalculate dfo r3 differentconcav eclearances .Fo r20 %deficienc y 8/4 (+),12/ 6 (o)an d 16/8 (D) ar edrawn .A wel lfittin glin e ( )fo rthes epoint si s

VT m.s -'

35 ^ B \\\WvN ^

30 .^ > ^^ 25 O:^ S>--<0 20

0 12 3 4 5 6 AFS kg.s-i.m-' Figure5.2.4.1 .Threshin gspee drelate dt ospecifi cstra wfee drate . Threshingdeficienc ycurves :Eime r (1977):20 %( ),10 %( ); Caspers (1973)fo r BETA =1. 820 %( ),10 %( )an dfo r BETA =1. 7 ( ).Threshin gdeficienc ypoint sfo rdifferen tconcav eclea ­ rances (mm/mm)Casper s (1973)fo r BETA= 1.8 :20% ,8/ 4(+) , 12/6(0), 16/8(D); 10% 8/4(»), 12/6(x),16/ 8(A) ; for BETA =1.7 :10 %12/6(D ) Optimumthreshin gspee dare afo rcrop :A ,B ,C (seefigur e5.2.3.4) . Relationuse dfo roptimu mthreshin gspee di nmode l3 : ( )

115 VT= 14+ 2.75-AFS. For10 %deficienc y8/ 4 (•),12/ 6 (x)an d16/ 8 (A) aredraw nwit hth eappropriat elin e ( ): VT= 1 9+ 2.75'AFS. Thelin e(—• •— ) an dpoint s (D)appl yt o BETA= 1.7 ,concav eclearanc e 12/6an da deficienc yo f10% .Fro mthi si ti sapparen ttha t BETAi n particularha simpac to nth eslop ean dtha tth eseparatio ndefici tdeter ­ minesth eleve lo fth eequatio ni nparticular .

Thereforea contro lsyste madjustin gth eoptimu mthreshin gcylinde rspeed - to-feedrat eequatio nshoul doperat eo nth ebasi sof :1 )a nadjuste dleve l VFL,base do nth edesire dconcav eseparatio nan do nknowledg eabou tth e influenceo fcro ptype so nit ;2 )a nadjustmen to fth eslop e VFSdependin g onth edifferenc ebetwee nth edesire dan dmeasure dconcav eseparation . Theuni to fth emeasure dconcav eseparatio nha st ob eth efractio no f thegrai nfee drate ,tha ti sth ethreshin gseparatio nefficienc y TSE, becauseit svalu eha st ob ea proces sparamete rtha tca nvar ywit hth e croppropertie sbu tno twit hth emomentar ygrai nfee drate . Thusth egrai nfee drat eha st ob eknow nan dit smeasuremen tha st o bea saccurat ea spossible .Fo rtha treaso na dela yo f 10s ha st ob e takenint oconsideratio ni nth emeasuremen to fth ethreshin gseparatio n efficiency (seeals o3.4) .

5.3.SPEE DCONTRO L

Costminimisatio ncalculatio n resultsa noptimu mmachin espee dan da n optimumthreshin gspeed .Thes espeed shav et ob eadjuste db ymean so f feedbackspee dcontrols ,i nou rcas ea machin espee dcontro lan da threshingspee dcontrol .

5.3.1. Machine speed control

Thetas ko fthi scontro li st oreduc eth edifferenc ebetwee nth ecalcu ­ latedoptimu marea , VW. an dth eactua lare a VW asmuc ha spossible .Th e o a relation VW= VM'CLi sapplie di nthis .Th ecuttin gwidt h CLi sassume d tob econstan ts otha tfo rou rsituatio ni tapplie stha t CL =5. 9an d VM= W/5.9. Inth ecas etha t CLdeviate sstrongl yfro mthi si npractic ethe nth e factshoul db ereporte dt oth econtro lvi aa switchboard .Measuremen t

116 systemsar eunde rdevelopmen tfo rthi sparameter . Thediagra mi nfigur e5.3.1. 1describe sth econtro lan dindicate sth e transferso fchapter s2 an d3 .

VM, m.s-i mm 4.3 rad.s- 1 ms -1 1 001124 Pc 1.67s 1*0.3s ? CYLINDER VARIATOR GAINBO X VM -025s e Vi SAMPLE INTERVAL

Figure 5.3.1.1. Machine speed control

Iti sals oeviden tfro mth efigure stha ta nintegratin gcontro lha sbee n chosen.Th eintegratio nactio ni srealize db ya hydrauli ccylinder .A n initialvalu eo f4 5ha sbee ncalculate dfo rP ,base do nth eNyquis tplo t infigur e5.3.1.2 .Th este prespons eo f VWwa sstudie di nth esimulation . o

M=1.0 6M = 1 0 M=1. 3

Figure5.3.1.2 .Nyquis tdiagra mo fmachin espee dcontro lfo rP =4 5

117 Fromfigur e5.3.1. 3i tbecome sclea rtha tunnecessar ywea ro fth edrivin g systemi sbes tprevente db ytakin gth evalu eo fP = 15,bu t P =2 5ca n alsob eused .

0-95

0.90

Figure5.3.1.3 .Respons eo fmachin espee d (VM)t oa ste pfunctio ni n theoptimu mmachin espee dinpu tfro m0.88 3t o 1.125m* s ( ) fordifferen tvalue so f P ofth emachin espee dcontrol . VUline s for P =15, for P =25, for P 35, for P 45 c c

5.3.2. Threshing speed control

Thetas ko fthi scontro li st oreduc eth edifferenc ebetwee noptimu m threshingspee dan dth eactua lspee d VT -VT asmuc ha spossible .Th e speedi sadjuste db ya hydrauli ccylinder ,s otha tintegratin gactio ni s alreadypresen tan di sadequat efo rthi scontro lloop ,show ni nfigur e 5.3.2.1.Sinc ew ear econcerne dher ewit ha periphera lspeed , VTca nb e transformedvi aa constan ttransformatio nfacto rt o OMOUT, theangula r velocityi nrad' s 1. 118 FOB ENGINE I [ NON LINEAR oc VT,. OMWT,.e 1 at 1 OMOUT 3.33 ï > SLIP —» SüTRAN S PCTC s 1*0.3S OM/N 'S? MISSION VARIATOR

OMOUT

Figure5.3.2.1 .Threshin gspee dcontro l

Inorde rt opreven tslip ,ther ei sa bloc ki nth eloo ppreventin g OMOUTfro mincreasin gto omuc hwhe nth eforc ei nth evariato rV-bel t exceedsa certai nvalue ,i nthi scas e320 0N .I nth esimulatio nthi sha s beenrealize di nth econtro lsyste mb ymakin gth efirs tfollowin gtim e stepe = 0 . Thevalu e320 0N correspond st oa transforme dpowe r (dependingo n OMOUT) ofabou t5 5kW .

Simulationshav ebee nperforme dwit ha sinusoida lsigna lo nth econtro l inputa tfrequencie sbetwee n0. 5an d6 rad* sx i norde rt oascertai nth e valueo f PCTC.B ythi smean sth eamplitud ecorresponde dt ovariation s inth estra wfee drat e {AFS)o f0. 6kg* sl aroun da naverag e AFSo f 2.5kg's" 1. VT was thencalculate dvi ath ethreshin gspeed-to-fee drat e equation VT - 19+ 2.7 5 AFS. Figure5.3.2. 2show sth eNyquis tdiagra m ofth econtro lwit h PCTC= 8 x 10~" .Althoug ha PCTCvalu eo f10«10~ " alsogive sa stabl esystem ,th evalu eS'io" 1*ha sbee npreferre dbecaus e atthi svalu eth ephas eshif tbetwee nth eactua lfee drat ean d VT for w= 0. 5- 3 rad" sl i sabou t0.80 ,whic hcorrespond sexactl yt oth e timedela ybetwee nauge rtorqu emeasuremen tan dthreshin gcylinde r (at 10x 10~H thiswa s+ 0.65) . Therei sn omeasuremen ttim einclude di nth emeasuremen tloop ,becaus e iti sassume dtha tthi scontro lwork sfast .A sampl einterva lo f0. 5s forinstanc ewil lb eto oslo wcompare dt oth edela yo f0. 8s . Figure5.3.2. 3show sth este prespons eo f OMOUTfo ra ste po f AFS from2. 5kg* s* t o2. 1kg' s 1. Therei sa littl eovershoot .A hig hover ­ shootcause sexcessiv ewea ro fth eV-bel tdrive .

119 M=1,3 M OMOUTrods- 1 87-

Figure 5.3.2.2.Nyquis tplo t Figure 5.3.2.3. Step response of angul; of threshing speed control speedo f the threshing cylinder{OMOUT for PCTC= S'lO-1* to a step function in specific feedra - {AFS) from 2.5 to 2.1 kg's l for a PCT( value of 8-10-"

5.4. CONTROL SYSTEMS

Aswa s stated in 5.1.2, four different control systems will be studied. Theywil lb e discussed in detail in the following chapters as far as the implementation for the simulation is concerned. The simulation will be dealtwit h inparagrap h 6. However,som e results will already be discussed in thenex t chapter tosho w the effects of control adjustment.

5.4.1. Loss control system

This control system comprises the machine speed control and the cost minimisation calculation using themeasure d walker loss and the measured machine speed andestimatin g themomentar y optimummachin e speed (see figure 5.4.1.1). Owing toth e time delay of 10.5 s in theproces s only low frequency variations inwalke r loss canb e controlled. Thesevaria ­ tions are causedb y the disturbances in theproces s variables and straw density levels.Th e higher frequencies in lossmeasuremen t have tob e filtered out.

120 FS^ PVM- •Pfeedrote 1 * ' VT WL. PROCES * Pthreshing—' Pseparatio n

MEASURING s s CL 4 1- VMa VMF. estimation of qi n WLM Delay.Filte r 1Filter WLM'C.explf/.VMF.CLf CALCULATION ANDCONTRO L OVM» Q? cost minimisatioIEn

Figure5.4.1.1 .Los scontro lsyste m

Thelow-pas sfilte ruse dwa sa nexponentia lsmoothin gfilter ,tha ti s adiscret etim efilte ractin ga sa first-orde rlow-pas sfilte r (Verbruggen, 1975).

Themeasure dmachin espee dha st ob ei nphas ewit hth emeasure dwalke r losss otha tth emeasure dvalu eo fth espee di sdelaye d 10.5s . Thevalu eo f qwa sthe ncalculate dfro mth eequatio n WL~= o'exp(q'VW) inwhic h c =3.4*1 0"* .Thi svalu ei schose nbecaus ei ti snea rth eesti ­ mated DQ valueso fth emode l WL= exp( D +D{'FS) (seetabl eA 4.2.1.3) . Thenecessar yadjustmen to fth efilte ri sexamine db ysimulatio no f thesyste mi ntw oways .Th erespons et oa 25 %ste pi nstra wdensit y levelo f0. 6kg« m2 wa sstudie di nth eoutpu to fmachin espeed ,fee drate , walkerloss ,an dcalculate d q. Thevalu eo f q showsth einpu to fth ecos t minimisationcriterion .Figur e5.4.1. 2show sth erespons efo ra breakpoin t frequencyo fth efilter so f0. 2 rad-s"1.Th erespons et oinitia lvalue s canb esee na tth ebeginnin go fth ecurves .Th este pi nstra wdensit y canb esee na tt = 1 1i nth estra wfee drat ea tth ecutte rbar .It seffec t onwalke rlos s 10.5s later ,th erespons eo f q andth emachin espee di s recogniseda tt = 22 .A sa resul to fthat ,agai n10. 5s later ,th ewalke r lossdecrease s (att » 33 )s otha t q alsoreacts .Thi swil lcaus ea sligh t resonance,whic hi sa reaso no fdecreasin gth ebreakpoin tfrequenc yo fth e filter. Thiseffec tca nals ob esee ni nfigur e5.4.1. 3i nwhic hth ebehaviou r ofcontrolle dmachin espee di sshow ni na proces ssimulatio nbase do nth e inputo fapparen tstra wdensit yvalue sobtaine di ntes tnr .61 .Th ethre e

121 Figure5.4.1.2 .Response sfo rth elos scontro lsyste mo fproces svariable s toa ste pfunctio no nstra wdensit ya tt = 11 .Lin e 1represent sstra w feedrate ,measure da tth ecutte rbar .Lin e2 represent smachin espeed . Line3 represent swalke rlos san dlin e4 th einpu to fth ecos tminimisa ­ tioncriterio ni.e .th evalu e qo fth eequatio n WL = cexplq'VW)

120 130 times Figure5.4.1.3 .Simulate dactua lmachin espee d (PMa).Outpu to fth elos s controlsyste mfo rdifferen tvalue so fth ebreakpoin tfrequenc y (ƒ) o f thelow-pas sfilte ri nth econtrol_system .Lin e3 :ƒ =0.40 ,line bl: 1 fh =0.32 ,lin e2 : f^ =0.1 6rad- s . Inputo fth esimulatio ni sth e apparentstra wdensit ydat afil e

122 breakpointfrequencie so fth efilter swer e0.40 ,0.3 2 and0.1 6rad' s' . Thelas tname devince sreasonabl ystabl ebehaviour ,fo rwhic hreaso nthi s breakpointfrequenc ywa suse di nth efirs tsimulations .

5.4.2. Loss-feed rate control system

Theinput so fthi scontro lsyste mar ewalke rloss ,fee drat ean dactua l machinespeed .Th eoutpu ti sth emomentar yoptimu mmachin espeed .I nfac t thisoptimu mspee dha st ob ecalculate da sshow ni nfigur e5.4.2.1 .

FS PVM Pfeedrate PROCES WL. VT Pthreshin g *|Pseporation

MEASURING \ S 1 VMa FSM FSM Filter Delay 1Filter VMa»CL SDM parameter estimation CALCULATION Filter WLM*a exp lb FSM) SDM' VM. CVM*-Q ? cost minimisation

Figure5.4.2.1 .Los sfee drat econtro lsyste m

Thevalue so fa an db hav et ob ecalculate di na no nlin eparameter - estimationprocedure ,usin gth emeasure dvalu eo fth ewalke rlos s {WLM) andth edelaye dmeasure dvalu eo fth efee drat e {FSM).I nthi sestimatio n procedure,filteringi sneede dt ob esur etha tth evalue so fa an db ar e goodestimates .Preliminar yresearc hshowe dtha tth euse ddat ao fmeasure d augertorqu ean dwalke rlos shav et ob etake nfro ma nestimate dperio do f about3 0t o5 0s .Onl ylong-ter mvariation si ncro pcondition swil lthereb y betake nint oconsideration .Th eoptimu mtechniqu efo rthi sparamete r estimationstil lha st ob eworke dou ti nfurthe rresearch .I tha st ob e somekin do frecursiv etechniqu ewit ha forgettin gfactor .I nth esimu ­ lationsdeal twit hi nth enex tchapter ,value s aan d b areuse dtha tar e calculatedof flin eove ra perio do fabou t15 0s .The yar ethe nhel dcon ­ stantdurin gtha ttime . (In4. 6an dA 4.2.l. c aan d bwer ecalle dex p (DO) and Dl, respectively.) 123 Thisi sa simplificatio nneede dfo rth esimulatio nbu ti tdeviate sfro m therea lsituatio nwher eonl yon-lin eestimatio nca nb eused .Estimate d valueso f a and bwil lchang emor erapidl ythe n (seeals o5. 5an dchapte r6 )

Thebehaviou ro fcontrolle dmachin ean dthreshin gspeed si nth ehighe r frequenciesi saffecte db yth evariation si nstra wdensity ,dela yan d accuracyo fth emeasurement .Th estra wdensit yi sestimate dfro mth efee d ratean dth eactua lmachin espeed .Th eestimate dvalu eo fth estra w densityha st ob efiltere dt ob esur eo fquie tbehaviou ro nth epar to f thecontrol . Thisi steste db ysimulatio no fth erespons et oa ste po f0.1 5kg*m~ 2 inth eapparen tstra wdensit yinpu twit ha mea nleve lo f0.6 6kg*m~ zan d inspectiono fth econtro lbehaviou ro fth eoutpu to fth econtrol ,tha ti s therealize dmachin espeed .Figur e5.4.2. 2show sth eresponse sa tth e breakpointfrequencie so fth efilter so f0.33 ,0. 4an d0. 5rad's" 1.Th e behaviouro f0. 4rad' s l waspreferre da si twa squie tenough .Th eeffec t oncost so fothe rlevel swil lals ob eteste dan ddeal twit hi nchapte r6 . Infigur e5.4.2. 2th eacceleratio nvalue so fth esimulatio nwit hbreak ­ pointfrequenc yo f0. 4rad' s areals oplotted .A nadditiona lconstrain t forthi scontrol ,namel yi sth ecomfor to fth eoperator ,wh oha st obea r thecontinuou sacceleratio nan ddeceleratio no fth emachine . Formerresearc hwit ha fee drat econtro lsyste m (Huisman,1974 ;Va nLoo , 1977)ha sshow ntha tth econtrolle rha st ob eles sstringentl yadjuste d thanwa snecessar yfo rstabilit yreason s (seeals o6.2.2) .Th evalue so f theacceleratio nan ddeceleratio nthe nmeasure di nth efiel dwer emaximu m 0.4m* s2 .Ther ear en ostandard so facceptabl elevel so facceleratio nan d decelerationfo rthes esituations .Onl ylittl einformatio nabou tstandard s governingpassenge rtrain si savailabl eo nthi ssubjec t (Rookmaker,1967) . Fornorma lacceleratio nan ddeceleration ,limitin glevel sbetwee n0. 7 and 1.5m' s arementioned .Fo ra noperato ro na combin eharveste rth e speedo fwhic hi scontinuousl ychanging ,th elimitin glevel shav et ob e lower,fo rwhic hreaso nw eadop tth eleve lo f0. 4m' s (seeals o6.2.2) . Anacceleratio nlimitatio nelemen tcoul db eintroduce di nth econtro l systembu tth esimulation swit hth este pfunction san ddat afile sshowe d thatthi swoul dno tb enecessar ya tth euse dbreakpoin tfrequencie so fth e filter.Th emaximu mdeceleration sa sa reactio nt oth efee drat este p functionsi nfigur e5.4.2. 2fo rth ebreakpoin tfrequencie so fth efilter , thati s0.33 ,0.4 ,0. 5rad's" 1 were0.04 ,0.0 6 and0.06 5m's" 2.

124 1 l/Ma m.s- LOA

1.02-

L00-

2 098 4Cms- 0.02

0.96- O00

0.9U

--002 0.92

a90 --0.04

0.88 --0-06

Figure 5.4.2.2. Simulated response of actual machine speed (VM ) and acceleration [AC) to a step function in straw density f°r different values of the breakpoint frequency (ƒ,) of the low-pass filter in the loss feed rate control system. The measured feed rate includes measure­ ment noise. VM_ lines: for /K = 0.33, for ƒ. = 0.4, 1 foi fh = 0.5 rad-s ; Atfllne for/ b= 0^ 4rad* s*

5.4.3. Loss-feed rate-threshing speed control system

Thiscontro lsyste mcomprise sth eloss-fee drat econtro lan da nadditiona l threshingspee dcontro l (seefigur e5.4.3.1) .Thi smean si nfac ttha t theloss-fee drat econtro lreact st oth elow-frequenc ypar to fth edistur ­ banceso fth ecalculate dstra wdensit yan dt oth eproces sdisturbance so f threshingan dseparatio nmeasure db yth evariatio ni n aan d b ofth elos s feedrat erelation . Thethreshin gspee dcontro lreact st oth evariation si nth emeasure d feedrat ea si sexplaine di n5.2.3 .Th esource so fthes evariation sare : -variation si nth ecalculate dstra wdensit yo ffrequencie swhic hth elos s feedrat econtro lcoul dno tdea lwit hbecaus eo fdela yi nth eheader ; 125 - feed rate variations introduced because of redistribution in theheader ; - variation on thepar t of the estimated parameters in the loss feed rate relation giving rise toothe r feed rate levelsbecaus e such other feed rate levels mean other threshingspeeds . The response in total machine losses to a straw density step and threshing efficiency parameter willb e shown in 5.5.

1 J I I I ,) cyr*-U*—VFS«FSMlTL

•&

Figure 5.4.3.1. Loss feed rate threshing speed control system

5.4.4. Loss-feed rate-threshing separation control system

This control system canb e regarded as the loss feed rate threshing speed control inwhic h the feed rate tooptimu m threshing speed relationship is adapted to the threshing separation characteristics.Thes e characteristics change very slowly due to differences in cropproperties , so that the adaption canb e done slowly, too (see figure 5.4.4.1). It can then alsob e done more correctly,becaus e we can filter thehigh - frequency disturbances during measurement of the threshing separation efficiency.

Ideally we should like to adaptbot h the level and the slope in the threshing speed-to-feed rate equation. For the purpose of this study it

126 Figure5.4.4.1 .Loss-fee drate-threshin gseparatio ncontro lsyste m will do to adapt just one of these, becausei tunderline sth efac ttha t wear eneve rlikel yt okno wth erea loptimu mrelationship . Asi sargue di nparagrap h5.3 ,w ewil ladap tth eslop eo fth erelation . Forth ecalculatio no fth eestimate dslop e (VFSC)w ewil lus eth esteepes t descentmetho da sdescribe db yEykhof f (1977). Theprincipl eo fthi smetho di st ominimiz eth edifferenc ebetwee nth e outputo fth erea lproces sa si tshoul db ean dth eoutpu to fth eproces s asinfluence db yth eestimate drelatio n (seefigur e5.4.4.2) .Le t Nb e thetransfe ro fth erea lproces san dP th etransfe ra sinfluence db yth e estimation.The n e = N-FS - P'FS. Ifw ewan tt ominimiz eth eerro rfunctio n

/-5 pthreshinq =N

1—» model threshing -X* e estimation method { fi

Figure5.4.4.2 .Metho dfo rparamete restimatio ni nth ethreshin gsepa ­ rationtransfe r

127 E = e2 with monotonie convergence then dP ,3 £ — = - V—x- dt W because 3£ „ 3e . dP 3e -TT=2e«—* • is 2ve 3P 3P dt 3P Wekno wtha t

%-- FS 3P andthe n SP — = 3* 2ve'FS and P = f2v 'FS'e'dt

Therea lfee drate-to-separatio nrelationshi pi sno tknow ni npractice , butw eonl ywan tt orealiz eon especifi cseparation ,s otha tthi sleve l (SVTS) canals ob euse dfo rth e N'FS input.Henc eth ecalculatio no fVFSC isdon ea sshow ni nfigur e5.4.4.3 .Th evalu eo f 2v canb elo wbecaus eo f theslo wactio ntha ti sneeded .Th evalu eo f2.5*1 03 give sa smal lover ­ shootan di schose nb ysimulatio no fa ste pfunction .Figur e5.4.4. 4show s theresponse so fth ethreshin gseparatio nefficienc yt oa ste pi nth e valueo f BETAfro m1.7 6 to1.6 1 forthre edifferen tvalue sfo r 2v, namely 1.0-10-3,2.5'10~ 3an d5.0'lCf 3.

VMa FS * Pfeedrate VTa Pthreshin g m M 1 SVTS '-iS 2/ \ FSM T TSFM VT0 =VFL* t FSM FSM/LTY^Ot VFSC* LT I: Vs

Figure5.4.4.3 .Estimatio nprocedur efo rth eslop ei nthreshin gspee d tofee drat erelatio n VFSCo f controlsyste m4

128 TSE 0.85 -

0.80-

075

070

065

060- 1 10 20 30 40 50 60 70 times Figure 5.4.4.4. Response of threshing separation efficiency to a step function in BETA, from 1.76 to 1.61 for different values of thepropor ­ tional factor 2v in the adaption procedure of the slope in the feed rate to threshing speed relation

5.5. DISCUSSION

The control systems described in thepreviou s chapters are designed to minimize totalharves t costs and tocalculat e thebenefits . The systems themselves are not optimized in the sense of finding the best control adjustments or thebes testimatio n techniques,becaus e much more field research has tob eperforme d for that.Th e aim of the design was toobtai n systems thatcoul db e simulated, on the basiso f empirical disturbances to geta n impression of the differences in the expected levels ofbenefit ,s o as todecid e on the field research thatha s tob e continued and the control systems whichhav e tob e improved. The control systems and, inparticular , theparamete r estimating tech­ niques are simplified at someplace sbecaus e the simulation would become too complicated and time-consuming. The following simplifications have beenmade : - thevalu e of c in the loss control system isno t adapted to crop conditions;

129 - the estimate ofparameter s a and b of the loss feed rate control system wasperforme d "off line"ove r the rather long distance of 178.5 m; - the threshing speed optimisation criterion canb e improved. However, the differences between the fourcontro l systems are great enough todecid e on the differences in thebenefit s tob e expected.

The differenceswil lb e shown on thebasi s of figure 5.5.1. In this figure the responses of walker loss to twoste p functions areplotted . The first step is in straw density. It steps from 0.6 to 0.75 kg*s-1. The second step is 20 s later and BETA then steps from 1.76 to 1.61. Both steps affect walker loss and therefore machine speed. The abscissa has the travelled distance dimension, so that the second step doesno t occur at the same place, depending on themachin e speed in thepreviou s period. The manually control(syste m o, line )ha s a constant speed so that losses increase similarly to the steps in straw density and BETA. Themachin e speedwa s lower than in other cases,henc e feed rate and the losswer e lower.Th e simulation timewa s the same for the various controls with the result that the travelled roadwa s shorter atmanua l control.

WLkg.s- 1 0.12

0-10-

-i 1 r 60 70 80 distancem Figure 5.5.1. Simulated responses ofwalke r loss (WL) to two step functions for the various control systems as a function of traversed distance._At t=0 (distance=0) the straw density increases from 0.6 to 0.75 kg's 'an d 20 s later the value of BETA decreases from 1.76 to 1.61.Th e simulation time is the same for each system, indicated by n ... 4. See text. 130 In the response of the loss control system (system 1,lin e )a delay of 10.5 s canb e recognized after both steps.Th e speed decreases after each step (with some resonance) resulting in a decrease in feed rate and loss. The feed rate-loss control system (system 2, line )react s more quickly to the straw density step than system 1bu t doesno t react to the BETA step.Thi s isbecaus e the loss isno tmeasure d in the simulation,bu t thevalue s of theparameter s in the loss to feed rate relationship are estimated in advance. In the simulations for cost calculation, BETA and saidparameter s undergo a similar change. In a control system on a combine harvester the estimation can,o f course only be done after the lossoccurs , but over shorter travelled distances than 178.5m .Whe n a and b then change, the speed changes accordingly. The same facts apply also to thenex tcontrol , but in this case the threshing speed reacts to feed rate,s o that loss is lower for the loss feed rate threshing speed control (system 3, line ). The loss feed rate separation control system (system 4, line ) adapts the threshing speed feed rate relation to the threshing separation efficiency. After the BETA step the separation decreased below the desired level so that threshing speed continuously increases after the delay of 10s .Losse s thus decrease accordingly. The effect of these control actions on cost,wil lb e discussed in the next chapter.

131 6. Simulations

6.1 . METHOD

6.1.1.. Introduction

Inth eforegoin gchapter sth eproces san dcontrol-syste mmodel shav ebee n shownseparately .I nth epresen tchapte rthe ywil lb epresente dlinke d togetheri nth esimulatio nprogram .Th esimulatio nproces swil lb eexplai ­ nedi n6. 1 and6.2 ,i nparticula ro ndiscussio no fth einput .Th estage s inth esimulatio nprogram ,th eparamete restimatio nan dfinall yth ecom ­ parisono fsimulatio nresult swit hexperimenta lresult sar eexplaine di n 6.2.Th eresult so fth esimulation sar edeal twit hi n6. 3 onth ebasi s ofth eresearche dvariable so fou rproble man dth econclusion sa st oth e costso fth eharves twil lb egive ni nsectio n4 o fchapte r6 .

6.1.2. Simulation program CSMP

Thesimulatio nha sbee ncarrie dou to nth edigita lcompute rDEC1 0o fth e AgriculturalUniversity ,usin gth eContinuou sSyste mModellin gProgra m CSMPII Io fth eIB MCorporation .Thi sprogra mi sthough tt ob esuitabl e forou rpurposes .Onl ya shor tdescriptio no fth eprogra mwil lb egive n inth eappendi xa sth edetail so fth elanguag eca nb efoun di nth eProgra m ReferenceManua l (Anonymus1975 ). Th eCSM PFunctio nBlock suse di nou r programan dth eadde done swil lals ob egive ni nth eappendix .

Theaccurac yo fth esimulation sdepend so nth ecalculatio ntim e step, theintegratio n methodan dinterpolatio ntechnique so fth efunctio n generatorschosen . Forth etim este pth evalu eo f0. 1 swa suse dbecaus eth esmalles ttim e constanti nth eproces si s0. 3s .Thi sals owa steste db ycomparin gth e resultso fa smal lnumbe ro frun swit htim este pvalue so f0. 1 and0.0 5s .

133 thé results showing aver y slightdifferenc e (seeals o 6.3.3.14). The chosen integration method was the fixed step,firs t order Euler rectangular method because with thismetho d and thechose n time step no stability problemswer e encountered thatdemande d more sophisticated me­ thods. The function generators willb e discussed when they are introduced in the nextchapters .Fig .6.1.2. 1 shows themai n elements of the simulation program.

INPUT PROGRÄM OUTPUT

STORAGEO FARRAY S DEFINITIONO FADDITIONA L FUNCTIONBLOCK S (MACROS)

interactive: chosenparameter s PARAMETERDECLARATION S =5» PARAMETERSDEPENDEN TO N SITUATIONS LOADINGO FINPU TDAT AB Y Datafile s FUNCTIONGENERATOR S CALCULATIONO FINITIA LVALUE S

DYNAMIC

PROCESSCOMBIN EHARVESTE R speeds, force s, accelerations, losses, COSTCALCULATIO N costs of grain loss MODELSO FCONTROLLER S and machine (in data files or plots) MODELO F TRANSMISSION CALLFO RFILTER S CALLFO ROUTPU T

TERMINAL

FINISHCONDITION S SUBROUTINESFO R - INPUT - FILTERS - OUTPUT

Figure 6.1.2.1. The main elements, inputs and outputs of the program

134 6.1.3. Simulation input

Theinpu tca nb espli tu pint othre ecategories . -Dat ao nth evariatio no fth ecro ppropertie s; -dat ao nth echoic eo fcontro lsyste man dvariable so fth econtroller s; -dat aspecifyin gth eparameter si nth ecos tcriterion .

6.1.3.1. Data concerning crop properties

Thestra wdensit yinpu ti ssimulate db yconnectin gth edat ao f8 differen t datafile so f"apparen tstra wdensity "together .Eac hdat afil ecomprise s datatha trepresen tth estra wdensit yvalues ,average dove r0.2 5m o ftra ­ verseddistanc ean da cuttin gwidt ho f5. 9m ,calculate d fromfiel dtes t dataa sexplaine d inA 4.2 .Th edat arepresen ta tota ldistanc eo f 187.5m thatw ewil lcal la swath .Th estra wdensit ydat aar estore di na functio n generatora sa functio no fdistance .Th eread-ou tdat aar ecalculate db y linearinterpolation ,becaus ehighe rorde rinterpolatio nca ngiv eris et o negative,thu sunrealistic ,value si fstore dstra wdensit ydat aar eclos e tozero . These8 swath stogethe rrepresen ta sampl eo fth evariatio ntha ta combineharveste ri sface dwit hwhe noperatin ga tth eFlevopolder si n Holland.Th emea nstra wdensit ydiffer sfro mon eswat ht oth eothe r (see table4.2.1) .

Asecon dclas so finpu tdat aar eth ecro ppropertie saffectin gth egrai n separationi nth eprocess .I nth esimulatio nthe yar econstan twithi neac h swath,bu tca ndiffe rfro mon eswat ht oth eother ,resultin gi ndifferen t steadystat econdition si nth eprocess . Thesepropertie sare :- threshin gcoefficien t BETA - walkerefficienc yparamete r WEP - grain-to-strawrati o GS - meangrai nyiel d YIELD

Thesevalue sar eals ostore di nfunctio ngenerator sa sa functio no fdis ­ tancean dar erea dou tb ylinea rinterpolation .Th evalue suse di nth e simulationhav et ob eregarde d asa sampl eo fth ewid evariatio no fmea n valuesencountere d inth efield .Thei rvalue sar egive ni ntabl eA 4.1.2.3 .

135 In the field,however ,th e values ofthes e parameterswil l also vary within the swath but thisvariatio n is smallcompare d to the differences between the swaths. Inrealit y thesemea n levels usually remain nearly constant even for aperio d longer than theduratio n of the harvesting of a swath in the simulation.Thu s theharvestin g of a swath in the simulation could be repeated several times,bu t isnot ,i n order toreduc e the cal­ culation time of the computer.

When another swath is started in the simulation the crop properties are really changed as they are taken tob e affectedb y other cropcondi ­ tions in the field,suc h asweathe r or cropvariety . The control systems are expected to react tothi s sudden change. Since controller 1react s slowly and the effect of this controller is intended tob e compared fairly with the others,thi s controller is offered the swath data three times in successsion before thenex t swath enters the simulation. Thisprocedur e in the simulation is assumed tob e close to the reality in the field,sinc e the various control systems follow the small and slow changes in croppropertie s in the same way,bu twil l react differently to the fast and large variations in cropproperties .Suc h changes inproper ­ ties are due todifference s in soil conditions and to the start of another crop.

6.1.3.2. Data concerning control systems

Formanuall y controlled runs (system 0) themachin e speed ispu t in from the swath data,henc e each swath has its own constant machine speed equal to that measured in practice. For manual controlled runs aswel l asthos e of control systems 1 (loss control system) and 2 (loss-feed rate control system) the speed ofth e threshing cylinder is adjusted at amea n value of 30.0m' s by setting the position of thevariato r (DV) to0.03 2m (see 2.3.3). In thiswa y the threshing cylinder speed varies dynamically with variation of straw feed as in reality. Forcontro l systems 3 and 4 the threshing cylinder speed is automatically controlled.

For the loss-feed rate control system (system 2) values areneede d for the parameters in the loss-feed rate equation for the optimum machine speed calculation as isexplaine d in 5.2.1 and 5.4.2.Th e parameter values are calculated foreac h swathbase d on data of the field tests as explained

136 in4. 6an dA 4.2.1 .I nth esimulatio nthes evalue sar eals ostore di n functiongenerator slik eth ecro pproperties .Whe nthe yar erea dou to f thefunctio ngenerator ,th eoutpu ti sfirs ttreate db ya firs torde rlow - passfilte rwit htim econstan tT = 1 0s fo rth efollowin greason .Use d inpractic eth eparamete rvalue so fth econtro lsyste mar e assumed tob e estimatedb ysuc ha metho dtha tlos san dfee drat edat aar eaverage dove r about5 0s (seeals o5.4. 2 and6.2.4.1) .I naddition ,th elos si sdelaye d by 11s ,s oi ttake sabou t6 0s until lth echang ei ncro ppropert yi s completelyincorporate di nth eparamete rvalues .Thi sbehaviou rca nb e approximated bya first-orde rlow-pas sfilte rwit ha tim econstan to f roughly3 0s .Sinc eth econtro lsyste mcanno tadjus tth emachin espee d atth eoptimu mleve la slon ga sth eparameter sar eno tcorrectl yestimated , thecost sar eals osuboptima lfo rtha ttime .I fth eparamete rvalue si n thesimulatio ndiffe rfo rtw osucceedin gswaths ,th ecost sar esuboptima l forth eperio dth eparamete rvalue schang ei nth efirs tpar to fth esecon d swath.Thi sperio dwoul db eabou t6 0s wit h T_= 3 0s ,a relativel ylon g periodcompare dt oth esimulatio nperio do f187. 5s ,whe nth emachin e speedi s1 m* s .Sinc eeac hswat hi ssimulate dthre etime si nsuccessio n forcontro lsyste m1 an donc efo rcontro lsystem s2 ,3 an d4 ,contro lsys ­ tem1 coul db eahea da sregard scosts .Fo rthi sreaso nth esuboptimu mperio d ofcontro lsystem s2 ,3 an d4 wa sdecrease db ya facto ro f3 .T wa sthere ­ foretake na s1 0s .I nth ecos tminimisatio ncriterio no fth econtro lsys ­ tems,th eparamete r YIELD, thati sth egrai nyiel dalso ,ha st ob econsi ­ dereda sa nestimate dparamete rs otha tth ecos to ftimelines slos sca n becalculate d correctly.However ,th etimelines slos sfractio ni scalcu ­ latedan duse di nth ecalculatio na sa nexpectatio no fth emea nlos sfrac ­ tionove ra certai nnumbe ro fyears ,s otha tthi slos swil lno toccu ri n thesam ewa yfo rth especifi charves tsituatio ni npractice . Inpractic e wed ono tkno wth erea ltimelines slos seither .A valu e for YIELDtha ti s anexpectatio no fth emea ngrai nyield ,i stherefor eaccurat eenough .Th e meanyiel do fth etw owhea tvarieties ,tha twer euse dfo rth einpu tdat a measuredi nth efield ,wa suse dan dals otreate di nth esimulatio na sa cropproperty .Th etim econstant so fth eintegratin gactio nan dth ebreak ­ pointfrequenc yo fth efilter s (see6.2 ) ofth econtroller sar eals oinpu t parametersconcernin gth econtro lsystems .Th eeffect so fth evalue so f theseparameter swil lb estudie di n6.3 .

137 6.1.3.3. Data concerning cost calculation situations

Thecost so fwhea tcombin eharvestin gusin gth edifferen tcontrol swil l becalculate d for6 differen tsituation si nwhic hth econtrolle ri sused . Thesesituation sar echaracterize db yvariou scost-determinin gvariables , affectingno tonl yth ecos tcalculatio nbu tals oth ecos tminimisatio n algorithmo fth econtro lsyste mbecaus ethe yinfluenc eth emachin espee d forminimu mcost . Forth ecos tsituation s 1...4 (seetabl e6.1.3.3.1 )differen ttimeli ­ nesslos sfractio nline sar euse d (seefig .1.4.1.3) .Thes edifferen t linesar epu tint oth esimulatio nb yfunctio ngenerator sloade dfro mdat a filescontainin gth efraction so ftimelines slos spe rvalu eó f VW,tha t isth eharveste darea ,increasin gpe r0. 1 m -s from0 t o1 0m #s .I n thecos tminimisatio ncriterio nth efirs tdérivâte so fthes eline sar e used,s otha tfunctio ngenerator sar eloade dfro mothe rdat afile scon ­ tainingth eslop evalue spe r0. 1m 2,s l.Th evalue suse di nth esimulatio n arecalculate db ylinea rinterpolation st oth eactua lvalu eo f VW. Forsituation s5 an d6 ,constan tvalue so ftimelines slos spercentage s areuse dbecaus ei nthes esituation sth emachin ecos tline sdetermin eth e costminimisation .Th ecost-determinin gvariable sar eliste di ntabl e 6.1.3.3.1.Fo rexplanatio nse e2. 2an dA 2.2 .

Table6.1.3.3.1 .Cost-determinin g factorsi nth evariou scos tsituation s

Costsituatio n 1 2 3 4 5 6 User Farmer IJ.D.A. Farmer IJ.D.A. Contractor IJ.D.A. Timeliness lossris k% 25 25 162/ 3 162/ 3 25 25

Timeliness loss% f(VW) f(VW) f(W) f{VW) 0.057 1.65 AAN ha 100 175 100 175 100 175 NE h'ha-1 0.20 0.27 0.20 0.27 0.20• 0.27 L0 fl'ti-1 20.00 40.00 20.00 40.00 32.60 40.00 MVCfl'ha -1 54.00 58.00 54.00 58.00 66.00 58.00 VMNm-s -1 - - - - 1.0 0.9 AFC fl'yr-1 35280.00 20387.50 35280.00 20387.50 36350.0 0 20387.50 Vi fl'kg"1 0.534 0.505 0.534 0.505 0.534 0.505

138 6.1.4. Simulation output

The aimo f the study was to calculate the expected financialbenefit s of the various control systems,henc e the calculated costs of combineharves ­ ting are stored in output files.Besides ,i ti s informative to follow the simulated processes so losses, speeds, accelerations and forces are also stored in output files.Th e totalcost s of the various control systems have tob e calculated in awa y thatenable s them tob e compared.Th e unit fl'ha is the most informative forth e farmer aswel l as forth e contrac­ torbecaus e the totalcost s are then clear,give n theknow n area tob e harvested. In the simulation the calculations are done per time interval, so that costs alsowil l be computed per time intervalbu t in fact refer toth e areaharveste d in that time interval.Th e costs ofeac h interval are added until the total area (8swaths ) isharvested . This is the case when the traversed distance is8*187. 5 = 1500m or three times as much in the case of control system 1.

Maohine costs

The calculation of machine costs is done asexplaine d in 2.2.The sum of the calculated costs in fl*ha per time interval is thenmultiplie d by the areaharveste d intha t interval,tha t is VWi nha* s ',s o thatw e know the costs of that time interval in fl*s l. These costs then are integrated.

Costs of machine losses

The cost ofmachin e losses is foundb y integrating the valuespe r time interval of the sum of the costs ofbreakag e loss,walke r loss, threshing loss and sieve loss calculated asexplaine d in 2.3 by the model of the process.

Costs of timeliness loss

The costs of timeliness loss are in reality notknow n until the harvest is completed and the totalharves t period isknown . Inou r simulation we can only calculate thecost s for our sample of 8 swaths.W e therefore calculate the "expected" timeliness loss ofeac h time interval on the

139 basis of the loss thatwoul d occur,wer e thewhoi e harvest done at the machine speed of thatparticula r interval and atth e same grain yield of the swath thenharvested . We could have used themea n machine speed of our 8 swaths togetherbu t since the timeliness loss curve,a s a function of machine speed (or VW)i sno t linear,th e resultwoul db e too optimistic in the caseo fmea n lowmachin e speeds.Thi s isbecaus e the timeliness losses occur mainly at the end of the season and are therefore considerable when theharves t season is long owing tolo wmachin e speeds. In this way the risk ofhig h timeliness lossha sbecom e part of the cost calculation results.Th e timeliness loss is calculated from the integrated product of the grain feed rate (FGTD), th e timeliness loss fraction (TILF) and the

value of the grain (77).Th evalu e of TILF is found from the function generator as explained in 6.1.3.3.

Costs of wear of threshing ayUnder V-belts

The costso f thewea r of theV-belt s driving the threshing cylinder are calculated asexplaine d in 2.2,pe r time interval and then integrated.

Total costs

The above-mentioned cost factors are added together and then, depending on the desired dimension, divided either by the harvested area or harvest duration giving output data in fl'ha or fl*s

6.2. SIMULATION MODEL

Here themodel s dealtwit h in chapter 2,wil l be discussed as to the adaption toth e simulation. In addition in some cases the sensitivity of various parameters willb e analysed and the comparison with experimental data willb e made.Th e parameter estimation technique forsom e important parameters will alsob e discussed.

6.2.1. Threshing and separation

Fig.6.2.1. 1show s theprocesse s of threshing and separation in abloc k diagram. The inputparameter s of the models,enclose d in a circle are variable and originate from function generators or controls.Th e other 140 Delay 1 VE=2.64

LA-O.9

0.6

pST ~LT=1.561t b

T FGZ,(=TOTAL GRAIN PLOW)

Delay 5 Delay 4 >« Delay 4 jFGi 10 '•P&VVnr

CRL=*0.k ICRL-CRS-FSJl) ) TAVV=0.B CRS-0.05 1+E4W-S

AFSW WW FGW-expl-LWj^l SW=1.56|-

8.2

Delay 6 (_|8. : D .001-AFSWD-FGTD 0.025-TNSED- FGTD

MEASURED STRAW SIEVE LOSS WALKER LOSS THRESHING BREAKAGE FEED RATE FLOW LOSS LOSS

Figure6.2.1.1 .Flo wchar to fth esimulate dproces so fthreshin gan d separation inputparameter sar eindicate da tthei rdefaul tvalues .

Thesensitivit yo fth evariou sparameter saffectin gth ewalke rlos swil l bestudie dfirst .Thes eparameter sare :threshin gcoefficien t (BETA) , walkerseparatio nparamete r (WEP), an drotar yseparato rparamete r (CRL). Figures6.2.1. 2.. .6.2.1. 4sho who wth evariou svalue so fthes eparameter s influenceth ewalke rloss-to-fee drat erelation . Theseplot ssho wresult so fexperiment sa swel la so fsimulation ss o thatcompariso ni sals opossible .Th epoint sindicate db y( a) i nthes e plotsrepresen tth evalue sfro mfiel dexperiment sa sexplaine dbelow . Thesear eth e2 3mea nvalue so fwalke rlos san dstra wfee drat e calculatedfo r 141 Figure6.2.1.2 .Dat ao ffiel dmeasurement san dsimulatio no fstra wfee d rate (FS) andwalke rlos s (WL),average dove r8 m traverse ddistance . Measureddat ao ffiel dtes t3 1 (a)an dleas tsquar ebest-fi tcurv eo f form WL= amexp{b'FS) onthes edat a ( ).Simulate ddat afo r BETA =1. 4 (x),1. 6 (0)an d 1.8 (•) (WEP= 1.8 , CRL= 0.55) .Wher eth e simulateddat aar eto oclos et oeac hothe rfo ra clea rplot,the yar e notplotte dbu tshow nb yth eenclosin glin e

0,05

Figure 6.2.1.3. Same asfo r figure Figure 6.2.1.4. Same asfo r figure 6.2.1.2bu tsimulate d datafo r 6.2.1.2bu tsimulate d datafo r WEP= 1.4 (*), 1.8 (0),2. 2 (•) CRL =0.3 5 (x),0.5 5 (0)an d0.7 5 (BETA =1.8 , CRL= 0.55 ) (•) (BETA = 1.8, WEP =1.8 )

142 consecutivestretche so f8 m traverse db ya combin eharvester .Th e"appa ­ rent"stra wdensit yo fth esam efiel dtes twa scalculate dpe r0.2 5m an d storedi na dat afil ei nth ewa ya sdescribe di nA 4.2.I.e .Thi sdat afile , representingdat ao fa tota ldistanc eo f187. 5m ,wa suse da sinpu to f thesimulatio napplyin gth eproces sparamete rvalue sa sgive ni nth eplots . Themachin espee dwa sth esam ei nth esimulatio nan dth efiel dtes t andth esimulate dlos san dfee drat ewer eals oaverage dpe r8 m simulate d traverseddistance .Thes evalue sar erepresente di nth efigur eb y (x), (o)an d (•). Thepoint sar eofte ns oclos etogethe rthat ,fo rth esak eo fclarity ,i t wasdecide dt oenclos eth eare ao fgreates tdensity .Finall yth eplo tals o showsa line ,representin gth eleas tsquare ,bes tfi tcurv eo fshap e y= a exp(b-x )o nth edat a( •) o fth efiel dexperiment . Eachfigur eshow sth esam epoint san dlin eo fth edat ao fth efiel d experimentan ddifferen tsimulate dpoints .I neac hfigur ejus ton epara ­ meteri svaried ,whil eth eother sar eretaine da tth edefaul tvalues .

Figure6.2.1. 2show stha tth emode li sver ysensitiv et o BETAan dfigure s 6.2.1.3an d6.2.1. 4demonstrat etha tth esam eeffec to nlos sca nb eobtai ­ nedb ybot h WEPan d CRL. Itwa stherefor edecide dt okee p CRLa ta constan t levelo f0. 6 forth esimulation san dt oestimat eth evalue sfo r BETAan d WEPfo reac hswat hb ystandar dparamete restimatio ntechniques ,suc htha t thewalke rlos si nbot hsimulatio nan dexperiment sar esimilar .

Apackag eo fparamete restimatio ntechnique swa suse dcontainin gvariou s optimisationroutine sdescribe db yHimmelbla u (1972).Th eerro rcriterio n ofth eroutine swa s: J =/{(measure d loss)- (calculatedloss) } Theteste droutine swer e (Dongen,1981 ): -DFP ,usin gth eDavido n- Fletche r- Powel lalgorith m -POWEL ,usin gth ePowe lalgorith mwithou tdérivâte s -SIMPLX ,usin gth esimple xalgorith mö fNeide ran dMead . Asca nb esee ni nfigur e6.2.1. 5i twa sfoun ddurin gth eoptimisatio ntha t therear esometime sa numbe ro fcombination so f WEPan d BETAwit hth esam e lowerro rcriterion .Th elowes tvalue sar ealway sfoun d ina noblon gare a Fig.6.2.1.6 ,fo ra nothe rfiel dtest ,i sa nexampl eo fthis .Th eroutine s DFPan dPOWE Ld ono talway sfin dth eabsolut eminimu mo f J becausethe y

143 WEP m-i.kg.s-1 2.5 A "5 "

2.0

1.5

1.0

—i— 1.3 1.4 1.5 1.6 1.7 1.8 BETAh) Figure 6.2.1.5. Lines of constant values of the error criterion J = ƒ {(measured loss) - (calculated loss)}2 of the SIMPLX parameter estimation algorithm for the threshing coefficient (BETA) and walker efficiency parameter {WEP) fordat a of field test 55 use hill-climbing methods,wherea s SIMPLX is adirec t search method with restart algorithms,s o also optimum combinations of BETA and WEPar e found that aremor e close to the expected values.Value s of BETA and WEPar e calculated in thiswa y for each "swath"wit h the SIMPLX method. These values are listed in tableA 4.2.1.3i n the colums BETA 1 and WEP.

The meanwalke r loss,a s aresul t of simulations with these values,devia ­ ted from the mean lossesmeasure d in the experiments owing to the quadratic error criterion.Thi s is undesirable because the simulated losses of the runs at the same speed as inpractic e will be used as the loss level of themanuall y controlled practical situation,henc e these simulated losses have tob e atth e same level as in practice.Ne w values of BETA have therefore been foundb y ahand-operate d optimisation calculation until the simulated loss deviated from themeasure d oneb y less than0.1% . These values are given intabl eA 4.2.1.3i ncolum n BETA 2. Theparamete r WEP 144 W£P m-1.kg.s-i 4.0H " 3" 36

1.8 1.9 BETA (-) Figure6.2.1.6 . Samea sfigur e6.2.1. 5bu ti nthi scas efo rdat ao f fieldtes t31 ,tha tals owa suse dfo rfigur e6.2.1. 2.. .6.2.1. 4

waskep tunchanged .

Thedynami cbehaviou ro fth esimulate dwalke rlos sca nb estudie dan d comparedt oth elos smeasure di nth efiel dexperiment si nfigur e6.2.1.7 . Thedotte dlin ei nth efigur eshow sth elos si nth esimulatio ni nwhic h theapparen tstra wdensit yinpu to fnearl ya complet eswat h (nr.12 )wa s used.Th elin econnect sth elos svalue saverage dove r0.2 5m .Th eful l lineconnect sth elos svalue saverage dove r0.2 5m a sthe ywer emeasure d inth efiel db ymean so fa nacousti csensor . Atfirs tsigh tth eline sar eno tto oclos et oon eanother .I nparti ­ cularth epeak sar eno ta tth esam eplace .Thi sca nb eexplaine db yth e variationi nth edela yo fth elos si nth erea lmachin ecause db yth e irregularstra waccumulatio na tth ebaffl ecurtai nan db ygrai naccumu ­ lationi nfron to fth ethreshin gcylinder .I nth esimulatio nthi svariatio n doesno texis ta sn orando mirregularitie sar eintroduce dint oth esimu ­ lationmodel . 145 Figure6.2.1.7 .Simulate d ( )an dmeasure d (- -)value so fwalke r losso fth edat ao ffiel dtes t ("swath")1 2

146 Theaverag elos slevel showeve rsho wa goo dconformit ya sca nb ere ­ cognisedi ntw oways .First ,th elos speak so fmeasure dlos sar ealway s accompaniedb yrelativel ylo wlevel si nth eimmediat eneighbourhood . Second,a tth etota ltes tlengt hdifferen tmeasure dmea nlos slevel sca n berecognised :firs ta stretc ho f4 0m lo wloss ,the nu pt o11 0m a n increasedleve lan dth elas tstretc hshow sth ehighes tloss ,includin g highpeaks .Th esimulate dlos sshow sth esam epattern . Thedynami cbehaviou ro fth esimulate dlos sshow sroughl ywha tcoul d beexpecte dan di si nconformit ywit hwha ti sneede dfo rou rsimulatio n sinceth elos si sheavil yfiltere dwhe nuse da sinpu tsigna lfo ra contro l system.Th eslo wvariatio ni nth eleve li ssimulate dcorrectly .

6.2.2. Machine speed

Themachin espee di nou rsimulatio ni scontrolle dmanuall yb yth emachin e speedcontro lconsidere di nchapte r5.3.1 .I nth econtro lschem esom e timeconstant saffectin gth ebehaviou ro fth ehydrauli cdriv eha dt ob e estimated.Th esimulatio nwa sdon ewit hth eparamete rvalue sgive ni nfig . 2.4.2.1.Th esimulate dbehaviou ro fthi scontro lcoul dno tb ecompare d withrealit ybecaus en osuc hcontro lsyste mha sbee nteste di npractic e onmachin eB (seeA 1.1) . However,a torqu econtro lsyste mwa steste do nmachin eA (Loo,1977 ) usingi nprincipl esimila rdrivin gpart sa smachin eB ,thu sallowin gth e assumptionso fth emode lt ob etested .I nparticula rth eintegratin g actionan dth efirst-orde rtransfe rfunctio no fth emachin etransmissio n canb econsidered .

Fig.6.2.2. 1show sth ebloc kdiagra mo fth etorqu efeedbac kcontro lsys ­ temwit hth eparamete rvalue stha tar euse di nth esimulatio nprogra m (Reumkens,1983) .Se eals o2.3. 1 and2.4.1 .A tfiel dtest swit hth e torquefeedbac kcontro lsyste mth eactua lmachin espee dan dauge rtorqu e weremeasure dan drecorded .Th eapparen tstra wdensit ywa sthe ncalculate d fromthes emeasurement san daverage dpe r0. 2m traverse ddistanc ean d storedi ndat afiles .Thes edat awer euse da sinpu tfo rth esimulatio no f thetorqu efeedbac kcontro lsystem .Th evalue sfo rth emachin espeed , machineacceleratio nan dauge rtorqu eaverage dpe r0. 2m ,outpu to fsimu ­ lationar eplotte di nfig .6.2.2.2 .Thi si sals odon ewit hth evalue so f

147 CONTROLLER AND VARIATOR MOWING PROCESS 83. 46 rad-s l SD kg-rn"2 +

SVTA+ E LIMITER 0.9686 VM FSC Delay 0.329 + 0.00587 SD'CL-VM FSAC^ s + CORRECTOR 1+0.3's t,I . 0.3 s ; • l l -, mV mm 0 - 113 nun rad-s ' m*s kg*s

MVTA MV kg-s '

TOROUETRANSDUCE R

Figure6.2.2.1 .Simulatio nmode lo fauge rtorqu efeedbac kcontro lsyste m ofmachin eA workin gi nfirs tgea r SVTA =se tvalu eauge rtorqu e (300-400mV) . MVTA =measure dvalu eauge rtorqu e thesam evariable smeasure ddurin gth efiel dtests .Th edimensio no fauge r torquewa scalculate di nterm so fmeasure d feedrat e (FSM).

Theplot ssho wthat ,fo rth e P valueo f0.7 0i nth econtro lsystem , the behaviouro fth esimulate dmachin edoe sno tdeviat eessentiall yfro mtha t obtainedwit hth efield-tes tsystem ,s otha tth eassumption so fth e time constantsuse di nth esimulatio nar ecorrect .Specia lattentio nwa spai d toth ecalculate dan dmeasure dacceleration so fth eforwar dmachin espee d becauseth eintegratin gactio no fth etorqu efeedbac kcontro lsyste mha s beenadjuste ddurin gth efiel dtest si nsuc ha wa ytha tth emaximu m acceleration anddeceleratio nvalue swer edecrease dunti lthe ywer e comfortablefo rth eoperator .I nfig .6.2.2. 2ca nb esee nthat ,i ngeneral , thevalu eo f0. 4m's -2wa sno texceede di nsuc hadjustment ,s otha tfo r themachin espee dcontro lo fmachin eB thi sleve lwa sals ouse da sth e maximumtolerabl elevel .

6.2.3. Threshing speed

Thethreshin gspee di nth esimulatio ni sth eresul to fth einteractio no f theoutpu to fth espee dcontro lsyste mgive nb y DVan dth estra wfee drat e atth ethreshin gcylinde r FST,a si sexplaine di n2.3. 3an dreviewe di n fig.2.3.3.7 .Th edat agive ni nthi sfigur ear eals ouse ddurin gth e simulation.I nth eabsenc eo fa rea lsyste mther ei snothin gt ocompar e thesimulatio nwit ha syet .However ,th eresult so fsom esimulate dvalue s ofth etensio ni nth eV-bel t (FOB)show sgoo dagreemen t withwha twa s tob eexpected .I ntabl e6.2.3. 1a compariso ni sgive no fth eFOB value s

148 o o b o c o

1 01 3 B (0 dl id S +J o V 0) S oi Ol S >i >O "0 o) 1- •0

Table6.2.3.1 .Mea nvalue so ftensio ni nth eV-bel tdrivin gth ethreshin g cylinder {F0BAV)i nth evariou scontro lsystem si ncos tsituatio n2 an d SVTS =80 %

Control system 0 12 3 4

F0BAV (N) 1246 1377 1430 1455 1500

149 ofth evariou scontro lsystems .

6.2.4. Control systems

Inthi ssectio nth esimulatio no fth econtro lsystem swil lb ediscussed . Someparamete rvalue swil lb eexplaine dhere .Wher esuc ha valu ei scalle d adefaul tvalu ethi smean stha tothe rvalue sar eals oinvestigate di n6.3 . In6.2.4. 8plot sar eshow ncomparin gth ebehaviou ro fth edifferen tcontro l systems.

6.2.4.1. Filtering and sample interval subroutine

Thecontro lsystem sdescribe di nchapte r5 ar es ocomple xtha ti twil lb e usefult oprogra mthe mi na micro-processor .I nconsequence ,th emeasure d valueso flosse san dspeed swil lb esample dan daverage dove ra certai n sampleinterva l (TD).Thi ssamplin goperatio ni nou rsimulatio ni scarrie d outb ymean so fth esubroutin e "MECEF"i nwhic hi sinclude da digita lfil ­ teractio nt oobtai nth edesire dbehaviou ro fth espee doptimisatio ncal ­ culation.A discret esmoothin gfilte ri suse d (Verbruggen,1975 )tha twork s asa first-orde rlow-pas sfilte rwit ha breakpoin tfrequenc yo fƒ ,= 1/T« . When MEANINi sth evalu eo fth einpu taverage dove rth esampl einterva l (.TD)the nth eoutpu to fth efilte ri scalculate da s MEANOUT.I nFortran : MEANOUT= {( 1- GF)'MEANOUT }+ GF"MEANI N Thevalue so f GFan d TDdetermin eƒ .a sfollow s Jb 4-l n {Y^F >/ W

Thesubroutin e "MECEF"als ogenerate sinitia lvalue sfo ra correc tstar t ofth eprogram .Th edefaul tlengt ho fth esampl einterva l (TD) is0. 5s whichi sconsidere dt ob ea reasonabl evalu econsiderin gth emicroproces ­ sorsno wavailable .Th edefaul tvalue so fth efilte rbreakpoin tfrequencie s areexplaine di nth efollowin gsections .Th esubroutin eMECE F isgive n inth eappendix .

6.2.4.2. Control systems inputs

Thevariable sgive nbelo war einpu tfo rth econtro lsystems .

150 Machine speed

Themachin espeed ,calculate db yth eproces ssimulatio npasse sth eMECE F subroutinewithou tbein gfiltere d (GF = 1),bu ti shel ddurin gth esampl e interval.N onois ei sadded .

Threshing cylinder speed

Thecalculate dthreshin gcylinde rspee d isdirec tinput ,withou tadde d noise,filte ractio nan dvalu eretentio ndurin gth esampl einterval .

Straw feed rate

Thefee drat emeasuremen ti srepresente db yth emeasuremen to feithe rth e augertorqu eo rth edisplacemen to fth eelevato rchai na sexplaine di n 3.1.Th evariabl et ob euse dca nb eselecte db ya switch .The nmeasuremen t noisei sadde da sdescribe d in4.2 .Th esu mo fth emeasure dvariabl ean d thenois ethe npasse sth eMECE Fsubroutin et ob efiltere dan dhel ddurin g thesampl einterval .Th edimensio no ffee drat eremain skg* s 1 sotha t noconversio ni sneede danywher ei nth ecalculation .I nfig .6.2.4.2. 1 themeasure dvariabl ei nth estra wfee drat edimensio ni sshow nwit ha s wella swithou tnois etogethe rwit hth eoutpu to fth eMECE Fsubroutine . Inthi scas eth esampl einterva lwa s0. 5 sbu tn oadditiona lfilterin g wasdone .I nthi sfigur ew eca nge ta nimpressio no fth enois ean dth e effecto fnois eo nth esample ddata .No tmuc hvariatio ncause db yth e noiseremain san dth edela ycause db yth esampl einterva lca nb erecog ­ nised.

Threshing separation efficiency

Thethreshin gseparatio nefficienc ycalculate dwit hth emode lis ,a s explainedi n3.4 ,multiplie db y 100,delaye dfo r9. 0 san dadde dt onois e atth edefaul tvalu eo fmaximall y± 3 %absolute .Th etota li sthe nhel d forth esampl einterva lbu ti sno tfiltered .

Walker loss

Noise,wit ha defaul tamplitud eo fmaximall y0. 4time sth elos sleve lo f

151 FSA FSMD

i r 50 60 traverseddistanc em

Figure6.2.4.2.1 .Stra wfee drat e {FS) takena tdifferen tplace so fth e simulationmodel :lin e 1i s FSA, thecalculate d feedrat ea tth eauger ; line2 i s FSAwit hadde dnois e (butplotte d3 kg's" 1higher ) FSM,lin e 3i sth esample d FSMvalu e FSMD

0.007kg" s 'i sadde dt oth ewalke rloss ,calculate db yth emode lo fth e process.The ni tpasse sth esubroutin eMECE Ft ob efiltere dan dhel d duringth esampl einterval .

6.2.4.3. Manual control (system o)

Thespee do fth emachin ei sse ta tth evalu etha twa smeasure di nth e field.Th echang ei nspee da tth een do fa swat ht oth espee do fth eothe r swathi ssimulate db ya first-orde rtransfe rfunctio nwit ha tim econstan t of2 s a sthi si sa roughl yth epatter ni nwhic hth eoperato rdoe sit . Toresearc hth eeffec to fothe rspeed so nth ecosts ,thes espeed swer e raisedan dlowere db y10 %an d20% .

152 6.2.4.4.Los s control system (system 1)

Asexplaine di nchapte r5 ,th evalu e qo fth eequatio n WL= cexp(q'VW) hast ob eestimated .Thi si sdon eb ydelayin gth evalu eo f VWfo r10. 5s andfilterin gbot h WLan d VW withth eMBCE Fsubroutin ean dth ebreakpoin t frequency (equalfo rboth) ,an dthe ncalculatin g q. Thismean stha tfo r eachsampl einterva lanothe rvalu eo f q isfound ,s otha tth esetpoin t valuefo rth emachin espee dcontro li sals oconstan tdurin gth esampl e interval. Thiscalculatio no fth eoptimu mspee di sdon ei na CSM Pimplici tfunctio n thatcalculate sb yiteratio nuntil ,i nou rcase ,th edifferenc ebetwee n thelas tan dth esecond-las toutpu ti sles stha n2% .A valu eo f 1%wa s toosmal li nou rsimulation sbecaus eth elimi to f 100iteration swa sno t reachedi nsom ecases ,resultin gi na nundesire dsto po fth esimulations . Therespons eo fdifferen tvariable so fth econtro lsyste mt oa simulate d stepfunctio ni nstra wdensit yha salread ybee nshow ni nfigur e5.4.1.2 . Thebehaviou ro fth esyste mwhe napparen tstra wdensit yi sth einpu to f thesimulatio ni sdemonstrate d infig .6.2.4.4.1 .Th ebreakpoin tfrequenc y ofth esmoothin gfilte rwa s0.1 7 rad-s inthi scase .Th erespons eo f q isthe nto ofast .I nsom eexplorator ysimulation sbette rresult swer e founda tbreakpoin tfrequencie snea r0.01 4rad' s 1 sotha tthi svalu ewa s chosenfo rth edefault .Th esyste mthe ncontrol sth eslo wvariation so f lossalone .I nfigur e6.2,4.8. 1ca nb esee nho wth emachin espee dvarie s overth eteste dswaths .On eha st orealis etha tth eapparen tstra wdensit y inputo feac hswat hwa suse dthre etime si nsuccessio nfo rthi scontro l system.T ocompar eth ebehaviou ro fth edifferen tcontro lsystem smor e easily,th etraverse ddistanc eo fcontro lsyste m1 i nth eplo twa sdivide d by3 .

153 70 80 times Figure6.2.4.4.1 .Th ebehaviou ro fvariable si nth elos scontro lsyste m asa respons et oth einpu to fapparen tstra wdensity ,lin e1 i sth e simulatedmeasure dfee drat eincludin gmeasuremen tnoise ,lin e2 isth emachin espeed ,lin e3 i sth evalu eo f q inth ecalculatio nan d line4 i sth ewalke rlos s

6.2.4.5. Loss feed rate control system (system 2)

Theoptimu mspee dcalculatio nfo rthi ssystem ,givin gth eset-poin tvalu e forth emachin espee dcontrol ,i sals oobtaine db ymean so fth e CSMPimpli ­ citfunction .Th elos sfee drat eequatio nuse dhere ,i sa two-paramete r equationo fth efor mI n WL=D0+D1'FSa sexplaine di n5.4.2 .I fthi scontro l systemi st ob euse di npractice ,thes etw oparameter shav et ob eestima ­ ted "online"' .Paramete restimatio nfo rthi ssystem ,however ,stil lrequi ­ ressom efurthe rresearch .I nth epresen tstud yw ehav ebee noblige dt o simplifyth eestimatio nb ydoin gi t"of fline" .Th eresults ,however ,wil l beentere da snea r"o nline "a spossible .Ho wi twil lb edon ei sexplaine d below.

A4.2.1. Cexplain sho wth e DOan d Dl valuesar ecalculate do nth eexperi ­ mentaldat ao ffee drat e (F5)an dwalke rlos s {WL)o fth euncontrolle d runso feac hswath,o fwhic hals oth eapparen tstra wdensit ydatafile sar e madean d BETAan d WEPar eestimate d forth esimulation .I nfig .6.2.4.5. 1

154 5 6 FSkg.s- 1 Figure6.2.4.5.1 .Curve so fwalke rlos s {WL)relate dt ostra wfee drat e FSo f4 swaths ,lik ethe yar ea resul to fth esimulatio no fth eproces s when FSi sincrease dslowl y (indicatedb yth esligh tline san dadditiona l E)an dthe yar eth eresul to fth eequation : WL= DO + Dl'FS usedi nth e optimumspee dcalculatio n (indicatedb yth ethic kline san djus tth e swathnumbers ) curvesar eshow no fth eabove-mentione dequatio nan dcalculate d DOan d Dl valuesfo rfou ro fth eeigh tswath s (arbitrarilychose nou to fth e8 a s examples).The yar eindicate db yth ethic kline san dswat hnumbers . Thesecurve sca nb ecompare d toth ecurve so fth erelatio nbetwee n lossesan dfee drate ,found ,usin gth esimulatio nmode lo fth eproces swit h BETAan d WEPvalue scalculate da sexplaine d in6.2.1 .Thes elines ,indicate d byth ethi nline san dswat hnumber sincludin ga n "E",represen tth ewalke r losslevel sa tth evariou sstra wfee drat e levels,whe nth esimulate dpro ­ cessi si nstead ystat ea tthos elevels .Th emea nleve lo fwalke rlos s andfee drat etha toccurre da tth e fieldtest ,i sindicate di nth eplo t by(x) . Thecurve so fth esimulatio nmode lan dthos eo fth eequatio nwit hcal ­ culated DOan d Dl arefairl y similara ttha tpoin ti nth eplot .I nterm s ofth econtro lsyste msimulatio nthi smean stha tth eloss-to-fee drat e relation,use dt ocalculat eth ese tvalu eo fth emachin espee dcontrol , accordsreasonabl ywel lwit hth erelatio nsimulate di nth eprocess ,bu t therelation sar eno texactl ysimilar .

155 Thiswil lals ob eth ecas ei fsuc ha syste mi sapplie di npractice . Thedifferenc earise sowin gt odisturbance si nth eproces sand/o rth e differencei nfor mo fth esimplifie dequatio nan do fth erea lseparatio n processequation .Thi si sho wth edifferenc ei sinclude di nou rsimulation . Ifth econtro lsyste mwer et ob euse di npractic ean dth emea nleve lo f feedrat eshifte ddu et oanothe roptimu mmachin espeed ,th eestimate d valueso f DOan d Dl mightchange . Thisi sno tpossibl ei nou rsimulatio na sth e DOan d Dl areestimate d "offline" .Figur e6.2.4.5. 1show stha tth etw ocurve so fswat h5 2a s wella sthos eo fswat h5 7deviat ean dd os oth emore ,th emor eth emea n feedrat ediffer sfro mth efee drat eleve li nth ecalculatio no f DO and Dl (thelevel so f (x)). Thiswil lresul ti na greate rdeviatio no fth e calculatedoptimu mspee d fromth eoptimu mspee dobtaine dwhe nth elos s feedrat erelatio no fth esimulate dproces si sused . Thesimulatio nresult sar einfluence db ythi simperfection ,an dar e soth emore ,s omor eth eautomaticall ycontrolle dspeed sdeviat efro mth e manuallycontrolled ,speeds ,sinc eth elevel sindicate db y (x)ar eals o themanua lcontro llevels .Th etota lcost so fthi scontro lsyste mar eraise d bythi simperfection . Toinvestigat eth eeffec to fthi simperfectio ncontinue dfiel dresearc h andsimulation swit h"o nline "paramete restimatio nar eneeded .

Theoptimu mspee dcalculatio no fthi scontro lsyste mals oneed sa valu e forth ecalculate dstra wdensit y (SDM)a sexplaine di n5.2.1 .I nth e simulationthi svalu ei scalculate db ydividin gth emeasure dfee drat e variableincludin gnois e (FSM)b yth eharveste dare a {VW). Th equotien t isthe nfiltere da sexplaine di n5.1.2. 2b ymean so fth eMECE Fsubroutine . Thedefaul tvalu eo fth ebreakpoin tfrequenc yo fth efilte rwa sse ta t 0.4rad- s' base dupo nth evalu echose ni n5.4. 2 andsom einitia lsimula ­ tionsshowin gth eexpecte dbehaviour .I nfig .6.2.4.5. 1th ecalculate d strawdensit yan dth eoutpu to fth efilte rar eshow nt ogiv ea nimpressio n ofth emeasuremen tnoise ,filterin gan dsamplin gi nth esimulation .Th e inputint oth esimulatio nwa sa constan tapparen tstra wdensit yleve lo f 0.6kg'm" 2an da ste po f25 %a tt=2 0i nadditio nt otha tlevel .Th estra w feedrat ewa smeasure db yth eauge rtorqu ean ddefaul tnois ewa sadded .

156 SDM kgm-î 1.0J

Figure6.2.4.5.2 .Stra wdensit yi nth esimulation .Lin e 1represent s thestra wdensit ya si ti scalculate db ydividin gth emeasure dfee drat e (thusincludin gth emeasuremen tnoise )b yth emeasure dmachin espeed . Line2 represent sth esample dan dfiltere dsigna lo fth estra wdensit y oflin e 1(th ebreakpoin tfrequenc yo fth efirs torde rlo wpas sfilte r was0. 4 rad^s ).Th einpu twa sth eapparen tstra wdensit ya ta leve l of0. 6kg* m2 until t =2 0s an dthereafte r0.7 5kg'm -2

6.2.4.6. Loss-feed rate-threshing speed control system (system 3)

Themachin espee dcontro lo fthi ssyste mi ssimila rt othos eo fsyste m2 . Thethreshin gcylinde rspee do fthi ssyste mi scontrolle db yth ethreshin g speedcontro lwhos einput ,th eoptimu mthreshin gspee d VT , isgive nb y

VTQ=24.0+2.4'AFS accordingt o5.2.3 .I nth esimulatio nth evalu efo r AFS isfoun db ydividin gth e FSMvalue ,a sexplaine d in6.2.4.2 ,b yth ewidt h ofth ethreshin gcylinder .

157 6.2.4.7. Loss-feed rate-threshing separation control system (system 4)

Themachin espee dcontro lo fthi ssyste mi sals osimila rt othos eo fsys ­ tem2 .Th ethreshin gcylinde rspee di scontrolle db yth emeasure dfee d rate (FSM)(se e6.2.4.2 )an dth edifferenc ebetwee nth ese tvalu eo fth e threshingseparatio nefficienc y (SVTS) andth emeasure dthreshin gsepa ­ rationefficienc y (TSEM)a sexplaine di n5.2. 4 and5.4.4 .

Thedefaul tleve lo f SVTSwa schose nt ob e90 %a swa s thought to be a reasonable value,becaus eth ethreshin gseparatio nefficienc yshoul db e largeenoug hfo rlo wwalke rloss ,s otha tth ethreshin gspee dwoul dthu s becomehig henoug ht ogiv elo wthreshin glos sbu tno tto ohig ht oresul t ins omuc hstra wbreakag etha tsiev elos swoul dbecom ehigh . Ifsuc ha syste mi suse di npractice ,thes eargument swil lb eused ,too . Theoperato ri sabl et oinspec tth eexten tt owhic hther ei sbroke ngrai n andthreshin glos san dwil lthe nchoos eth evalu eo f SVTSan dth econcav e adjustment.Th eothe rargumen tabou tstra wbreakag eaffectin gsiev elos s andeve nwalke rlos swil lals ob econsidere dan dacte do ni nth efield . Thesefactor shav eno tbee nbrough tint oth esimulatio nmode ls ocanno t affectou rchoic eo f SVTS, whenonl yth ecalculate dcost sar etake nint o consideration.However ,thes eargument swer enevertheles suse db yu st o chooseth eleve lo f90 %i nth esimulation,althoug hminimu mcost swer e obtainedwhe nhighe rvalue so f SVTSwer euse d (see6.3.3.8) .

Thedefaul tvalu eo f2 vtha taffect sth espee do fadaptio no f VFSCi nth e relationbetwee noptimu mthreshin gspee dan dfee drat ewa s2.5«1 03 a s explainedi n5.4.4 .T osho who wfas tth eadaptio noccurs ,fig .6.2.4.7. 1 demonstratesth erespons eo fth evalu eo f VFSC,th ethreshin gspee d (VT) andth ethreshin gseparatio nefficienc y (TSE) toa sudde nchang ei ncro p propertiesresultin gi na decreas ei nthreshin gseparatio nefficiency . Thischang ewa scause db ya ste pfunctio ni n BETAchangin gth evalu efro m 1.75t o1.6 0a tt=1 0i na preparator ysimulation . Asca nb esee ni nth eplot ,th eproces swa sstil lmovin gt ostead ystat e startingfro mth einitia lconditions .Th estra wdensit yinpu tint oth e simulationmode lha sa constan tvalue .A sa resul to fth edeal yi nth e measuremento fth ethreshin gseparatio nefficienc y (see3.4) ,th ethreshin g speed (VT) and,a sa resul to fthat ,th ethreshin gseparatio nefficienc y

158 VT VFSC 'TSE

£_^r 10 20 30 40 50 60 times Figure6.2.4.7.1 .Th erespons eo f VFSC(lin e 2), theparamete ri nth e threshingspee dt othreshin gseparatio nefficienc yadaption , VT (line3 ) and TSE (line1 )a ta simulate ddecreas eo f BETAa tt = 1 0a sca nb esee n inth esudde ndecreas eo f TSEa ttha tmomen t

(TSE) startt oincreas efaste ra t£=2 0tha nthe ydi dbefore . Atabou t£=4 0 VTreache sit slimit ,bu t VFSCstil lincreases,becaus e TSEdi dno treac hth evalu eo f SVTS. Thisi sbecaus e VTha st odecreas e inth eeven ttha t TSEdrop sbelo w SVTS. Hence,a ssoo na s VTreache sit s maximum (orminimum ) VFSCmus tremai na tit slas tlevel .Thi swa sincor ­ porated intoth esimulatio nb yth ecorrecto rstructur estatemen tdescribe d inA 6.1.2 .

6.2.4.8. Comparison of control systems in simulation

Therespons eo fwalke rlos so fth econtro lsystem st oa ste pdisturbanc e inth evalue so f BETAan dstra wdensit yi sshow ni nfig .5.5.1 .Th ebeha ­ viouro fth esystem sdurin gth esimulatio nrun swil lb eshow ni nth e figureswhic hfollow .

Themachin espee di sshow ni nfig .6.2.4.8. 1a sa functio no ftraverse d distance.Sinc eth espee dals ovarie si na relativel yshor tdistance ,th e lineswil lcros seac hothe rto omuch .I norde rt oobtai na clea rplo tth e speedoutpu twa spu tthroug ha first-orde rlow-pas sfilte rwit ha break ­ pointfrequenc yo f0. 2rad- s 1. Althoughth etraverse ddistanc eo fth e losscontro l (system1 )i sthre etime sa slon ga sthos eo fth eothers ,

159 200 400 600 800 1000 1200 U00 traversed distance m Figure6.2.4.8.1 .Machin espee d (VM)durin gth esimulation so fth e8 consecutiveswath sa tcos tsituatio n2 ,fo rth emanua lcontro l (line1) , controlsyste m 1(lin e2 )an dcontro lsystem s2,3, 4 (line3 )

thetraverse ddistanc ei nth eplo thav ebee nmad eequa li norde rt o compareth ereaction so fth esystem st oth eswat hdata .Thi smean stha t withinth etraverse ddistanc eo feac hswath ,syste m 1ha sbee noffere d threetime sth estra wdensit ydat ao fthi sswath . Thefigur eshow sth espeed so fsystem s0 ,1 an d2 i ncos tsituatio n2 forth egive ndefaul tvalue so fparameters .Th emachin espeed so fsystem s 3an d4 ar eequa lt othos eo fsyste m2 .

Thethreshin gcylinde rspee di sshow ni nfig .6.2.4.8. 2(als ofiltere da s explainedabov efo rmachin espeed )fo rsystem s2 ,3 an d4 .Thi sspee di s givenfo rcos tsituatio n2 an dth edefaul tvalue so fth eparameters .Fo r controlsyste m4 tw oline swer eplotted ,th ese tvalue so fthreshin g separationefficiency , SVTS, beingadjuste da t9 0an d80% ,respectively . Inth elatte rcas e (80%)th ethreshin gspee ddoe sno treac hit suppe r limita sa t90% .Thi sclearl yshow sth enee do fextr acriteri afo rth e threshingspee dcontro lo fsyste m4 ,fo rinstanc eth egrai nan dstra w breakagea sindicate d in6.2.4.7 .Furthe rresearc hha st ob edon eo n thisaspect .

160 200 400 600 800 1000 1200 .K0 0 traverseddistanc em

Figure6.2.4.8.2 .Threshin gcylinde rspee d (VT) duringth esimulation so f the8 consecutiv eswath sfo rcos tsituatio n2 an dcontro lsystem s0, 1an d 2 (line 1),contro lsyste m3 (line 2), controlsyste m4 a tdesire dthreshin g separationefficienc y90 %(lin e3 )an d80 %(lin e4 )

Theresult so ntota lcost so fth evariou scontro lsystem sar eplotte di n fig.6.2.4.8. 3fo ra shor tdistanc ean di nfig .6.2.4.8. 4fo rth etota l simulationo f8 swaths .Th eline sha dt ob eshifte dt oobtai na clea r plot. Forth esam ereaso ni nfig .6.2.4.8.4 ,th eoutpu twa spu tthroug h alow-pas sfilte rwit ha breakpoin tfrequenc yo f0. 1rad* s . Iti sinterestin gt ose eho w thecos tline so fcontro lsyste m 1sho w largerpeak stha nth eothe rsystem scause db ya novershoo tdu et oth e delayi nth eprocess .Contro lsyste m4 show scompare dt osyste m3 highe r costsi nth efirs t60 0metres ,bu tmuc hlowe rcost safte rthat .

161 TOC fl-ha-1 300-J

200

100

i r- 30 40 traversed distance m Figure6.2.4.8.3 .Tota lcost s {TOC)calculate dfo rth esimulatio no fa shortpar to fth efirs tswat hfo rth evariou scontro lsystems ;lin e1_ = TOCo fmanua lcontrol ,lin e2 = (TOC o fcontro lsyste m 1)-50.0 0f lh a , line3 =(T0Ccontro lsyste m 2)- 100.00fl-ha" 1,lin e4 =(T0Co fcontro l system 3)- 150.00fl-ha" 1,lin e5 ={T0Co fcontro lsyste m 4)- 200.00fl-h a

T0C fl- ha-1 500 -,

400

300

200-

100

200 400 1000 1200 1400 traversed distance m

Figure6.2.4.8.4 .Tota lcost s (TOC)calculate dfo rth esimulatio no fth e 8consecutiv eswath si ncos tsituatio n2 ,fo rth evariou scontro lsys ­ temsa sindicate di nfigur e6.2.4.8. 3

162 6.3.SIMULATIO NRESULT SAN DDISCUSSIO N

6.3.1. Introduction

Thefirs tsimulatio nrun swer eexecute dwit hdat ao ftw oswath st otr y outth echose nparamete rvalues .The nrun swer edon efo rfina lparamete r adjustmentusin gdat ao fal l8 selecte dswaths ,wit hfairl ydifferen t resultsi nsom ecases . Whenon eparamete ri svarie di nth erun sdiscusse d inthi schapter , allth eother sar ese ta tth edefaul tvalue smentione di n6.2 .I nmos t casesth ecalculation swer eonl ydon efo rth eIJ.D.A .cos tsituation s 2an d6 (se etabl e6.1.3.3.1 )t oreduc ecalculatio ntime .I ngenera lonl y totalcost sar ecompared ,bu tsometime sth eseparat ecos tfactor so r speedswil lb estudied ,too .

6.3.2. Manual control

Thecondition srecorde ddurin gth efiel dtest swit hth ecombin eharveste r ofth eIJsselmeerpolder sDevelopmen tAuthorit ylarge-scal egrai nfar mwer e defineda sth estandar d ofth emanua lcontro lfo rou rresearch .Th e operatorsa tthi sfar mar ewel ltraine dan dhav ewid eexperience .I n additionthe yar einforme dregularl yabou tth elosse soccurrin gwit h theirmachine sb yaspecia lqualit yinspectio nteam .Th emachin eopera ­ torsar einstructe dt odriv ea tsuc ha spee dtha ttota lmachin elosse s willb eabou t0.5% ,thi sbein gth eoptimu mleve lcalculate dwit ha nope ­ rationalresearc hoptimisatio nmode lfo rth ecerea lharves t (Kampen, 1969;Hagting ,1976 ;Fokkens ,1981) .Fo rthi sreaso nth espeed sselecte d byth ecombin eoperator so fthi sfar mwil li n generalb eneare rth eopti ­ mumtha nthos eelsewhere .T oinvestigat eth eeffec to fothe rmachin espeed s oncosts ,th ecalculation swer eals odon ewit hmachin espeed stha twer e increasedo rdecrease db y20 %(a swel la s10 %fo rth ecos tsituation s2 and 6). Table6.3.2. 1show sth eresult sfo ral lsituation san dspee d deviations.

Theseresult sdemonstrat eth edifferenc ei ntota lcost sfo rth evariou s costsituations .Th ecost st o thefarme ran dcontracto rfo rth etimelines s losscalculatio nfo r25 %weathe rris k (situations1 an d5 )ar eclos te o thosecalculate db yothe rauthors .Th etimelines slos sris kpercentag oe f

163 Table 6.3.2.1. Costs of combineharvestin g with manual control at machine speeds measured at the IJ.D.A. grain farm calculated for various costsituation s explained in table 6.1.3.3.1 and various speed deviation factors (allcost s in fl*ha 1). TOC= total costs, CM =machin e costs, CLO= machin e losscosts , CTI = total timeliness loss costs, CW =cost s ofwea r ofV-bel t T0C Situ­ Meanmachin es peed Machine speed deviation factor ation TOC CM CLO CTT CVW 0.8 0.9 1.1 1.2 1 478.95 420.57 55.78 2.45 0.16 468.45 505.61 2 299.21 204.85 52.73 41.47 0.16 341.17 311.31 297.49 302.74 3 1052.99 420.57 55.76 576.50 0.16 1469.40 786.25 4 461.85 204.85 52.73 204.12 0.16 778.75 386.22 5 519.56 461.65 52.76 1.9 9 0.16 568.44 502.55 6 306.77 199.74 52.73 54.13 0.16 309.41 305.87 311.60 319.73

16 -/%%(situatio n 3)introduce s large timeliness loss costs thatar e not realistic.The y indicate the reasonwh y farmers in theNetherland s restrict the area tob e harvested to 100h a per combine per year. The costs for the large scale grain farm of the IJsselmeerpolders Development Authority (IJ.D.A.) aremuc h lower (situation 2), even forth e timeliness loss risk of 16 2/3% (situation 4). A reason is the fact that the IJ.D.A.wil l alsoharves t at grainmoistur e conditions above 23%.Cos t situation6 ,wher e harvest time is fixed,bu t thenumbe r ofmachine s is variable,manifest s costs very close to those in situation 2.Thi s indica­ tes thatth e areape rmachin e (175 ha) isnea r the optimum in relation to the timeliness loss curve used for situation 2.I tca nb e concluded there­ fore thatthi s timeliness loss curve and themachin e cost assumptions used in this studywit h results similar tothos e ofth e operations research model of the IJ.D.A.cerea l harvest.

Whenw e consider the cost figures of the other speedcalculations ,the n it isclea r that the selected speeds are fairly near theoptimu m for situa­ tions 2an d6 .Fo r cost situation 2,minimu m costs are found at 1.1 times the selected machine speeds,bu t for cost situation 6 theminimu m costs are found at 0.9 times the selected machine speeds.I tindicate s that the selected speeds are indeed close toth e optimum at the IJ.D.A. farm. The far-t thata slower speed isoptimu m for situation 6 and ahighe r speed 164 forcos tsituatio n2 ,indicates ,moreover ,tha tth etimelines slos si s animportan tcos tfactor . Considerationo fcos tsituatio n4 show stha teve n 1.2time sth emachin e speedgive slowe rcosts .Th eautomaticall ycontrolle dsystem ssho woptimu m speedstha tar e 1.5time sth ehand-controlle dmea nspeed .

Iti sinterestin gt ostud yth eeffec to fth etimelines slos sris ko nfar ­ mers'costs . Incos tsituatio n 1th eoptimu mspee di sles stha n0. 8 timesth eselec ­ tedspeeds ,bu ti ncos tsituatio n3 th espeed shav et ob ei nexces so f speeddeviatio n factor1.2 .Thi si sdu et oth egrai nmoistur elimitation s of23 %chose nfo rth ecos tsituatio no fth efarmer ,givin gles sworkabl e time,henc erapi dincreas eo ftimelines slosses .Thi sshow sth eimportan t roleo fth echose ntimelines slos scurv ean dth enee dfo rth ecurv et o bechange di na contro lsyste mwhe nth etimelines slos sexpectatio nchange s becauseo fpas tweathe ran dweathe rexpectations .I ti sth esam emechanis m thata farme ruse sintuitivel ywhe nh eincrease shi smea nmachin espee d whenharves tcondition sthreate nt odeteriorate . Costsituatio n5 ,i nwhic hth eare at ob eharveste di svariable ,als o demonstratesa highe rmachin espee dt ob emor eadvantageous . Theautomati ccontro lsystem sgiv einformatio na st oth eoptimu mmachin e speeds (table6.3.3.2) .Thes ecanno tb edirectl ycompare dt oth emea nspee d thati sfoun dt ob eoptimu m formanua lcontrol,becaus eth elas tname di s calculatedb ychangin gth espeed sfo ral lswath sb yth esam erati owhereas , inautomati ccontrol ,th espee do feac hindividua lswat hi soptimall yad ­ justed.

Whenspeed sar eadjuste db yautomati ccontrol,th etota lcost sar einflu ­ enced.Th edifference si ncost scompare dt omanua lcontro lar eno tonl y interestingwhe ncalculatin gth einvestment swort hmakin gfo rautomati c control,bu tthe yals ohav et ob ecompare dwit hth eeffect san dcost so f otherimprovement st oth ecombin eharvester . Thedat ao fth ehand-controlle dsituatio nmak ei tpossibl et oa certai n extentt ocalculat eth ebenefit so fa theoretica limprovemen ti nharves ­ tingcapacity .I naddition ,i ti sinterestin gt ocompar eth eresult so f thesesimulation swit hthos esimulate do nth esam ehypothesi sfo rth etota l harvestingoptimisatio nmode lo fth eIJsselmeerpolder sDevelopmen tAutho ­ rity (IJ.D.A.).

165 TheDepartmen to f OperationsResearc ho fth eIJ.D.A .wa sfo rthi s reasonaske dt ocalculat eth efinancia lbenefit ,i fmachines ^wer euse d witha harvestin gcapacit y 10%greate rtha nthos ei nactua lfase .Th e machinelosse swoul dremai nth esam ebu tth eothe rcos t factorswoul d decreasethen,becaus eo fth e 10%increase dmachin espee d (see2.2) .Th e timelinesslosse sar eals oinclude di nthi scalculatio ns otha tth eresult s can becompare dwit hou rcos tsituatio n2 .I nth eIJ.D.A .simulation seac h machineals oharvest s 175h ao fwinte rwheat .Th ecalculate dbenefi to f totalharvestin gcost sprove dt ob e34.5 0fl'h a l. Thesecost sinclud e transport,dryin gan dstorag ei nadditio nt oth ecos tfactor suse di nthi s study.

Inou rsimulatio nth ebenefi twa scalculate da sdemonstrate di ntabl e 6.3.2.2. Themachin ecost s (CM)an dtimelines slos scost s (CTI) weretake nfro m theincrease dspee dcalculatio nwhil eth emachin elos scost s (CLO)wer e takenfro mth enorma lspeed .Th ecost so fwea ro fthreshin gV-bel twer e alsotake nfro mth enorma lspee dbecaus ethe yar eno ttake nint oconside ­ rationi nth eIJ.D.A .calculation seither . Thecalculation swer eals odon efo rth espee dincrease sfro m 1.1t o1.2 , 0.8t o0. 9an d0. 9 to1.0 .Th ebenefi ti sdependen to nth echose nnorma l speedleve lan di sgreater ,th elowe rth enorma lmachin espeed .Th ebenefi t ofou rsimulatio ndoe sno tinclud eth econtributio no fth ecost so ftrans ­ port,dryin gan dstorage ,becaus ethe yar e assumed tob eindependen to f capacityvariation st oth eexten ttha tthe yvar yi nou rsimulations .Th e roleo fthes efactor si nth eIJ.D.A .simulatio ni spresen tbu twa sno t recordedan dthei rcontributio ni sthu sunknown .Knowin gtha tth enorma l speeda tth eIJ.D.A .i s0.9 0m' s l andth erecorde dspee do fou rhand - controlledsituatio ni s0.96 3m' s' mean stha tw ema ycompar eth ebenefi t of34.5 0fl'ha" 1o fth eIJ.D.A .leve lt oth e23.1 3fl'ha -1o ftabl e6.3.2.2 .

Thedependenc eo fth ebenefi tfro mspee dleve lca nonl yb eexplaine db y therelativel ylarg eincreas eo ftimelines slos sa tlowe rspeeds ,whe n thesam ecalculation sar emad efo rothe rcos tsituation s (for20 %increase ) thenth edat ao ftabl e6.3.2. 3ar efound . Forcos tsituatio n 1.. .4 th etimelines slos scost smak eth elarges t contributiont oth ecos tdecrease ,wherea si ti sth emachin ecos ti nsi -

166 Table6.3.2.2 .Cos treductio nthank st oincrease dmachin ecapacit ya t differentmachin espeed srelate dt omeasure dspee d

CM CLO CTI CVW TOCfl-h a capacity increase fl-ha' fl-ha' fl-ha' fl-h increasednorma l difference from to capacity capacity 1.0 1.1 203.02 52.73 28.46 0.16 284.37 299.21 14.84 1.1 1.2 201.54 65.75 20.10 0.26 287.65 297.49 9.84 0.9 1.0 204.85 41.78 41.47 0.08 288.15 311.31 23.13 0.8 0.9 206.97 32.69 62.48 0.03 302.17 341.17 39.00

Table6.3.2.3 .Decreas ei ntota lcost sthank st oincreas ei nmachin e capacityb y20 %i ndifferen tcos tsituations .A i nfl-h ax andB i n percentageso fcost so fth elo wspee d (so0. 8o r 1.0)

Afl-h a CostSituation s compared tomeasure d speed 1 2 3 4 5 6 0.8 - 1.0 10.83 62.13 437.73 337.06 70.20 22.82 1.0 - 1.2 3.12 24.68 296.51 103.80 46.78 15.20

B% 0.8 - 1.0 2.3 18.2 30.0 43.3 12.3 7.4 1.0 - 1.2 0.7 8.2 28.2 22.5 9.0 5.0

tuations5 an d6 .Thi sconfirm sth egenera limpressio ntha ta larg ecapa ­ cityi sadvantageou st odecreasin gi nmachin ecost san dtimelines slos s risk.

6.3.3. Automatic o ontrol

6.3.3.1. Control systems

Theeffect so fcontro lsystem so ncost san dspeed sar eshow ni ntabl e 6.3.3.1.1fo rsituatio n2 an di ntabl e6.3.3.1. 2fo rth eothe rsituations .

167 Table 6.3.3.1.1. Costsan dspeed so fth e different control systemsi n costsituatio n2 (IJ.D.A.,1 62/3% ) TOC= tota l costs, VMAV= mea n machine speed (rn's-1), ACAV= mea no fabsolut e valueso facceleratio no fmachin e (rn's-2), VTAV =mea n threshing cylinder speed (m's"1), CM= machin e costs, CLO =machin e loss costs, CTI =timelines s losscosts , CVW = costs of wear of V-belt (all costs in fl'ha-1) *) indicates speed deviationt omeasure d speeda than d control

Control system TOC VMAV ACAV VTAV CM CLO CTI CVW

fl'ha"1 m's"1 m's"1 m's"1 fl'ha-1 fl'ha-1 fl'ha"1 fl'ha"1 0 299.21 0.963 0 30.51 204.85 52.73 41.47 0.16 1 293.53 1.077 0.001 30.50 202.74 62.64 27.86 0.29 2 299.18 1.123 0.023 30.49 202.01 71.31 25.50 0.36 3 301.93 1.123 0.022 29.39 202.02 74.01 25.50 0.39 4 289.62 1.123 0.022 33.97 202.06 60.82 25.50 1.27 0 (1.2) 302.69 1.156 0 30.49 201.54 80.70 20.10 0.36 0 (0.8*341.12 0.771 0 30.54 209.69 32.69 98.71 0.03

Table 6.3.3.1.2. Costso fcontro l system4 i nth e various cost situations for defaultadjustmen to fthreshin g speed controlan d threshing speed controlledb yadditiona l filteringo fth emeasure d straw feed rate input (breakpoint frequencyo ffilte ri s0.01 4 rad*s )

Total costs fl'ha Cost situation 12 3 4 5 6 Default 468.24 289.62 670.80 365.31 486.30 301.82 Filtered 468.33 290.16 673.30 365.85 487.66 302.40

Machine loss costs fl'ha Default 41.86 60.82 119.33 84.03 85.81 54.12 Filtered 41.90 61.35 121.84 84.56 87.14 54.64

168 Theresult so fhan dcontrol ,includin g 1.2an d0. 8 timesth ehand-control ­ ledspee dar eals ogive nt osho wth ebenefit so fcontro lsystem si fothe r speedswer echose ni nhan dcontrol . Itca nb econclude dtha tth edifference sar ever ysmall.Firs tthe y willb ediscusse dfo rsituatio n2 an dcompare dt othos eencountere d manualcontrol .

Thetota lcost so fcontro lsyste m1 ar e 1.9%lower ,mainl ydu et oth e decreasei ntimelines sloss . Controlsyste m2 show sth esam ecosts ,sinc eth eincrease dmea nmachin e speedcause so nincreas ei nmachin elos sequa lt oth edecreas ei ntime ­ linessloss . Costso fsyste m3 ar eslightl yincrease dbecaus eo fincrease dmachin e lossesdu et oa les stha noptimu mthreshin gspeed . Asthreshin gspee di sincrease di nsyste m4 ,thi sbring sth eminimu m costst o3.2 %les stha ni sth ecas ei nmanua lcontrol .I fthes ecost s are comparedt othos eo fmanua lcontro la tspeed stha tar e 1.2time sth e measuredones ,th ecost sar e4.5 %les sand ,i fcompare dt o0. 8time sth e measuredspeed sthe yar e 17.8%less .

Thegenera lconclusio nfo rthi scos tsituatio ni stha ta sligh tincreas e inmachin espeed ,brough tabou tb ycontro lsyste m1 ,cause sa smalle r increasei nmachin elosse s (CLC)tha nth edecreas eo ftimelines slos s (CTI) . Alarge rincreas ei nmachin espeed ,realise db ysyste m2 o ra bette rchose n manuallycontrolle dspee do f1. 2time sth eorigina lspeed sgive sequa l increasean ddecreas eo fmachin elosse san dtimelines slosses ,respectively . Itseem sfro mthi sresul ttha ti ncontro lsyste m1 th ecalculate dse t value forth espee dcontro lwa smor eclos et oth e optimumtha ni ncontro l system2 .Thi s indicatestha tth esimplification si nth ecalculatio no f DOan d Dlwer emor ebadl ytha nt oth eadvantage so fa fas tfee drat e control.S oth econclusio nwil lb edraw ntha ta simple ,bu tgoo destimatio n of theloss-fee drat erelatio ni smor ebeneficia ltha ncontro lo ffas t feedrat evariations . Whensystem s3 an d4 ar ecompared ,i tca nb econclude dtha tth eadaptio n ofmea nthreshin gspee dt oth ethreshin gseparatio nefficienc y insyste m4 ismor ebeneficia ltha ntha to fthreshin gspee dt oth efas tvariation si n feedrat ei nsyste m3 .

169 A real comparison of these effects, however, cannot be made with precision by comparison of system 3 with system 4,because the mean level of threshing speed is not the same. For this reason control system 4 was simulated with heavily filtered measured feed rate input. The breakpoint frequency of the first order low-pass filter was 0.014 rad's , so that the speed of the threshing cylinder just changed slowly. In table 6.3.3.1.2 the results are shown for both the default and filtered case in all cost situations. The differences are very small,so it can be concluded that it is only the adjustment of the mean threshing speed that is important.

Table 6.3.3.1.2. Costs of control system 4 in the' various cost situations for default adjustment of threshing speed control and threshing speed controlled by additional filtering of the measured straw feed rate input (breakpoint frequency of filter is 0.014 rad's )

Total costs fl*ha Cost situation 12 3 4 5 6 Default 468.24 289.62 670.80 365.31 486.30 301.82 Filtered 468.33 290.16 673.30 365.85 487.66 302.40

Default 41.86 60.82 119.33 84.03 85.81 54.12 Filtered 41.90 61.35 121.84 84.56 87.14 54.64

170 Ifth edifference sarisin gi nth evariou scontro lsystem sar eals ostudie d inth eothe rcos tsituation sb ymean so fth eresult so ftabl e6.3.3.1.3 ,

Table6.3.3.1.3 .Tota lcost san dmea nspeed so fth econtro lsystem si n thedifferen tcos tsituation s

Costsituation: 12 3 4 5 6 Controlsyste m 0 478.95 299.21 1052.99 461.85 519.56 306.77 1 468.62 293.53 678.98 374.96 495.20 302.04 2 470.46 299.18 704.85 384.71 506.26 309.01 3 476.67 301.93 692.02 382.05 502.97 312.43 4 468.24 289.62 670.80 365.31 486.30 301.82

Meanmachin espee dm' s 0 0.963 0.963 0.963 0.963 0.963 0.963 1 0.893 1.077 1.439 1.262 1.190 0.985 *) 0.93 1.12 1.50 1.31 1.24 1.02

2,3,4 0.915 1.123 1.449 1.294 1.230 1.051 *) 0.95 1.17 1.51 1.34 1.30 1.09

) speed relative to the hand controlled speed

we can conclude as follows. The results in cost situation 6 are comparable to those in cost situa­ tion 2, described above. Differences are greater for situation 4 (U.D.A., 16 /3%) where the benefits of control systems 1 ... 4 compared to manual control are respec­ tively 18.8%, 16.7%, 17.3% and 20.9%. This result is the outcome of the speed difference compared to manual control (factor 1.3). Thedifference si ncos tsituatio n1 ar eslight ,jus ta si ncos tsitua ­ tion2 ,tha ti s2.1% ,1.7% ,0.5 %an d2.2% ,respectively . Theoptimu mmachin espee di ncos tsituatio n3 i- s1. 5time sth espee d atmanua lcontro ls otha tth eth ecos tdifferenc ebetwee ni tan dmanua l controli sals ogreat .Compare dt oeac hothe rth eeffec to fth eautomati c

171 control systems is smaller.Compare d to system 1th e differences are +3.8%, +1.9%an d -1.2%fo rsystem s 2, 3an d 4 respectively. Thedat ao f cost situation 5demonstrat e the same tendencies as in situation 6,althoughth edifferenc e tomanua l control isgreater , that is 4.7%.Compare d to control system 1system s 2, 3 and 4 give a costdif ­ ference of +2.2%, +1.6%an d -1.7%, respectively. The general conclusions tob edraw n from these results are: 1.Th e manually controlled machine speeds and the optimum machine speeds calculated and adjusted by the control systems for cost situations 1,2 an d 6 are very much the same.Ther e canb e two reasons for this: First:Assumin g that the cost values and timeliness loss curve chosen for the simulation are correct,th e operator of the IJ.D.A. machine selected machine speeds very close to the optimum. Second:Assumin g that thehand-chose n machine speeds are indeed optimum speeds,th e chosen timeliness losscurv e of the 25%weathe r risk is realistically related toweathe r and lossdat ause d by the IJ.D.A. in their simulation of the grainharvest .

Itshoul db e noted here that themachin e losses inou r simulation are higher than those of the optimum level of 0.50% calculated by IJ.D.A. Thewalke r loss and thebreakag e losswer e 0.98% each,th e threshing losswa s 0.50% and sieve loss 0.21%, together 2.7%average d for all the manually controlled runs. It can thus alsob e concluded that the manually controlled speedswer e toohig h compared to the standard loss level ofth e IJ.D.A. so that itwa s purely fortuitous thati twa s soclos e toth e optimum.

2.Contro l system 1give s lower total costs than control system 2 for all the cost situations.Thi s means that a simple lossmode l and slowcon ­ trolo f the mean levels and low-frequency variation in thecro ppara ­ meter values and feed rate,give s abette r contribution tocos t mini­ misation than fastfee d ratecontrol .Th e simplification,needed for our simulations of the parameter estimation of control system 2,can be one reason,bu t the results clearly:,demonstrat e that fast feed rate control is less important than control of slowvaryin g crop properties including mean straw density.

172 3.Th eresult so fcontro lsyste m3 an d4 als odemonstrat ethat ,fo rth e threshingspee dcontrol ,adaptio nt ocro pparamete rvariatio ni smor e beneficialtha nfas tcontro lo fthreshin gspeed .Th edifference scom ­ paredt ocontro lsystem s1 an d2 ,however ,ar eslight ,s otha ta n expensivethreshin gseparatio nmeasuremen tsyste mi sno tquickl y recovered.

6.3.3.2. The time constant of the integrating action of the machine speed control The default value of the factor P that determines the integrating action of the speed control was 25.0. The effect of other values has been studied and is shown in tables 6.3.3.2.1 and 6.3.3.2.2.

Table 6.3.3.2.1. Effects of time constant of machine speed control integration P in control system 2 TOC= total costs, VMAV = mean machine speed, ACAV= mean machine acceleration, WLAV = mean walker loss, CLO= machine loss costs, CM = machine costs

p TOC VMAV ACAV WLAV CLO CM fl'ha-1 m*s 1 m-s 2 kg-s"1 fl'ha" 1 fl'ha-1 15 299.34 1.123 0.015 0.0611 71.51 202.07 20 299.02 1.122 0.019 0.0606 71.11 202.08 25 299.37 1.124 0.022 0.0610 71.45 202.06 30 299.02 1.122 0.025 0.0605 71.02 202.08 35 299.19 1.123 0.029 0.0607 71.17 202.07 40 299.28 1.123 0.033 0.0607 71.22 202.07 45 299.16 1.123 0.038 0.0605 71.04 202.07

It was concluded from these data that there is no effect on loss and speed, and thus on costs. Thus the chosen value based on the agreements of 5.3.1 was correct. A faster reaction of the speed control to the set point, calculated by the slower-acting cost minimisation calculation, merely introduces higher accelerations but not lower costs.

173 Table6.3.3.2.2 .Percentage so fcalculatio nstep si nwhic hth eabsolut e valueo fth emachin eacceleratio n (AC)exceed sth egive nleve l

p te­ m*s 2 c p rn's "2 > 0.1 >0. 2 > 0.3 >0. 4 a 15 1.07 0.13 0.0 0.0 20 1.68 0.34 0.0 0.0 25 2.40 0.69 0.12 0.067 30 3.02 0.91 0.32 0.17 35 3.59 0.99 0.32 0.12 40 4.10 1.13 0.42 0.19 45 5.46 1.50 0.56 0.29

6.3.3.3. Thefilter action of control system 1

The breakpoint frequency of the low-pass filter in the loss feedback loop of control system 1 affects the mean machine speed and the machine losses. Table 6.3.3.3.1 shows the data from which can be concluded that the default breakpoint frequency ƒ of 0.014 rad*s " results in minimum costs in cost situations 2 and 6. It is also demonstrated that the low-cost area is wide. The minimum machine loss is found at f=0.030 rad's-1, which b meanstha tth econtro lsyste mma yb ever yslo wi nacting ,i nfac tmuc h slowertha ni sneede dfo rstability ,fo rinstanc eƒ = 0.16 rad's"1a si s given in5.4.1 . 6.3.3.4. Thechosen value of c in the parameterestimation procedure in control system 1

Thelos smode lo fcontro lsyste m1 wa si n5.2. 2define da s WL=c-exp(q'VW) . Theparamete r qi sestimate d"o n line"i nth esimulation .Th evalu eo f parameter cwa sno t"o nline "estimated,bu tse ta tavalu e3.4*1 0" *base d onth emea nmeasure di nfiel dexperimen to nth e8 swath sconsidered .T o investigateth esensitivit yo fthi schoice ,othe rvalue swer eals oteste d andth eresult sgive ni ntabl e6.3.3.4.1 .Th elowe rth evalu eo fc, th e steeperth elos scurv ean dth egreate rth edecreas ei nspeed .Th eeffec t ontota lcost sis ,however ,smal lwhe n ci sno tgive nto ohig ha value . Thechose ndefaul tvalu elead st ominimu mcost si ncos tsituatio n2 . If

174 Table 6.3.3.3.1. Effects of the breakpoint frequency F of the low-pass filter in the measured walker loss of control system 1 for cost situation 2 and 6. TOC =tota l costs, VMAV= mea nmachin e speed, CM= machin e costs, CLO= machin e loss costs, CTI = timeliness loss costs, CVW =cost s of wear ofV-belt .

situation 2

4 T0C VMAV CM CLO CTI CVW rad • s l fl'ha-1 m*s ' fl-ha-1 fl-ha-1 fl'ha-1 fl'ha-1 0.0030 294.50 1.099 202.39 66.34 25.46 0.31 0.0064 293.81 1.085 202.61 63.93 26.97 0.30 0.014 293.53 1.077 202.74 62.64 27.86 0.29 0.030 293.54 1.075 202.76 62.32 28.17 0.29 0.064 293.84 1.077 202.73 62.55 28.28 0.29 0.16 299.32 1.124 202.01 71.45 25.50 0.36 0.33 297.84 1.096 202.44 67.49 27.60 0.31 0.4 300.14 1.100 202.37 70.01 27.44 0.32

situation 6 0.0030 303.17 1.016 194.97 53.78 54.17 0.24 0.0064 302.32 0.996 196.78 51.13 54.18 0.23 0.014 302.04 0.985 197.73 49.90 54.18 0.23 0.030 302.06 0.982 197.98 49.67 54.18 0.23 0.064 302.55 0.985 197.73 50.41 54.18 0.24 0.16 309.00 1.052 192.06 62.32 54.32 0.30 0.33 314.68 1.018 194.80 65.40 54.17 0.31 0.4 318.54 1.025 194.29 69.76 54.17 0.33

thevalu e a is toohig h and the loss fallsbelo w that level,negativ e values of q willb e calculated. This results in an equation that cannot besolved and the simulation stops.Thi s in factoccure d for o =6.7-1 0 . Aver y strange thingoccurre d for c=2.5-10 3 incos t situation 6. The speeds became very low in the first swath and were atmaximu m in the others. No explanation was found for this phenomenon.

175 Table 6.3.3.4.1.Effect s of thevalu e c in theparamete r estimation procedure WL= cexp(q"W) of control system 1fo r cost situation 2 and 6. TOC =tota l costs, VMAV= meanmachin e speed, CLO= machine loss costs

situation 2 situation 6 In c C TOC VMAV CLO T0C _ VMAV CLO fl'ha l m's 1 fl'ha' fl'ha l rn-s"1 fl'ha l - 5.0 6.7.10"3 — 0.0*) — 321.05 1.179 83.21 - 6.0 2.5.10-3 299.09 1.156 76.01 **. - 8.0 3.4.10-'* 293.53 1.077 62.64 302.04 0.985 49.90 -11.0 1.7.10"5 293.64 1.006 53.08 300.90 0.886 38.85

*) The simulation stopped after 22seconds . **)Th e first swathwa s harvested ata ver y lowspee d of 0.093m- s and theother s atmaximu m machine speed.

6.3.3.5. The filter action of control system 2

The default value of thebreakpoin t frequency of the low-pass filter (ƒ') in the calculation of strawdensit ywa s chosen as 0.4 rad-s 1 inaccor ­ dancewit h 5.4.2.Th e results of table 6.3.3.5.1 showminimu m total costs

Table6.3.3.5.1 .Effect s of thebreakpoin t frequency ƒ of the low pass filter of calculated strawdensit y ofcontro l system 2fo r cost situation 2 and 6. TOC =tota lcosts , VMAV =mea n machine speed, CM= machin ecosts , CLO= machin e losscosts , CTI = timeliness losscosts , CVW= cost s of wear ofV-belt .

Costsiti îation 6 2

TOC TOC VMAV CM CLO CTI CVW 4 l 1 1 fl'ha ' fl'ha ' m*s fl'ha fl'ha fl'ha fl'ha 1 rad"s ' 0.05 308.99 299.25 1.117 202.11 71.60 25.17 0.37 0.1 308.43 298.73 1.117 202.11 70.92 25.34 0.36 0.2 308.39 298.67 1.118 202.10 70.65 25.58 0.35 0.4 309.00 299.18 1.123 202.01 71.31 25.50 0.36 0.5 309.43 299.29 1.125 201 .98 71.63 25.33 0.36 0.6 311.30 299.69 1.134 201.86 72.77 24.71 0.36

176 at f = 0.2 rad-s l for cost situations 2 and 6 mainly because of the minimum machine loss. The differences are very slight so the adjustment of f was correct. The machine speed control for system 4 is the same as for system 2, hence the effect of breakpoint frequency in this system was also studied and the results are to be found in table 6.3.3.5.2. Minimum cost is found in this case for 0.1 rad's for both situations 2 and 6,also thanks to minimum loss costs.

Table 6.3.3.5.2. Effects of the breakpoint frequency ƒ of control system 4 (see text table 6.3.3.5.1.).

Cost situation 2 6 TOC T0C VMAV CM CL0 CTI cvw 4 l -1 -1 rad*s ~ fl-ha fl'ha m«s* fl-ha"1 fl'ha-1 fl-ha-1 fl-ha-1 0.05 288.92 301.23 1.049 192.32 53.23 54.34 1.34 0.1 288.79 300.97 1.048 192.40 52.89 54.33 1.35 0.2 288.91 301.10 1.049 192.32 53.11 54.32 1.35 0.4 289.40 301.6 4 1.052 192.07 53.90 54.32 1.34 0.5 289.29 302.10 1.054 191.92 54.51 54.32 1.35 0.6 290.60 303.15 1.058 191.54 55.95 54.32 1.34

In fig. 5.4.2.2 it can be seen that for ƒ = 0.4 rad's the response to a step in the straw density input shows no overshoot so that in the cost optimisation the value for ƒ may be much smaller than is necessary for stability. Quiet behaviour and following the low-frequency and mean level variations of the disturbances of the process is found to offer better cost minimisation results than trying to follow the high-frequency varia­ tions .

6.3.3.6. The integrating action of the threshing speed control

The default value of the factor PCTC, that adjusts the integrating action of the threshing speed control,was set at 0.10 in accordance with 5.3.2 Other values were tested for control system 4 and cost situation 2. The results are given in table 6.3.3.6.1 and show minimum costs for PCTC^IO.IO "* but the difference in costs compared to the default value is very slight. It can be concluded therefore that the value chosen for control theory

177 Table6.3.3.6.1 .Effect so fth etim econstan to fth eintegratin gactio n ofth ethreshin gspee dcontro l PCTC,i n PCTC/s, forcontro lsyste m4 andcos tsituatio n2 . TOC=tota lcosts , VTAV=mea nthreshin gcylinde rspeed , CLO= machin elos scosts , CVW= cost so fwea ro fV-belt , FOBAV= mea ntensio ni nV-belt , TSEAV=mea nthreshin gseparatio n efficiency, WLAV =mea nwalke rloss .

PCTC TOC VTAV CLO CVW FOBAV TSEAV WLAV -1 l -1 -1 x lO-1* fl'ha m*s~ fl'ha fl'ha N % kg*s ' 4 289.99 34.01 61.15 1.24 1394.42 82.55 0.0522 6 289.73 33.99 60.92 1.24 1395.77 82.53 0.0519 8 289.62 33.97 60.82 1.24 1396.99 82.50 0.0518 10 289.41 33.96 60.60 1.23 1397.86 82.50 0.0515 12 289.50 33.95 60.70 1.23 1399.93 82.47 0.0516

reasonsi sals oa goo don efo rcos tminimisatio nreasons .

6.3.3.7. Theintegrating action in the adaption of threshing speed-to-feed rate relation in control system4

Thedefaul tvalu eo fth eproportiona l factor 2vi ncontro lsyste m4 i s 2.5'103 (see5.2. 3 and5.4.4) .Th eeffec to fothe rvalue swa sals oinves ­ tigatedan dshow stha tvalue sbelo wth edefaul tvalu ear eto olow .Th e totalcost sar eno tminimu mbu tth eimportan tthin gi st orealis etha t thethreshin gspee dadapt sto oslowly ,remainin ga tth evalu eo fth elate r swathto olon g .A sfo rth einpu to fcro ppropertie sint oou rsimulation , theoptimu mwoul dhav ebee na valu eo f5*10~ 3. (seetabl e6.3.3.7.1 ) Theoptimu mvalu eo fthi sfacto rdepend sver ymuc ho nth econditions , sotha tmor eresearc hi nactua lpractic ei s required.

6.3.3.8. Theset value of threshing separation efficiency of control system4

Theoptimu mthreshin gspee di sinfluence db yth ese tvalu eo fth ethreshin g separationefficienc y (SVTS) .Th eeffect sar edemonstrate di ntable s 6.3.3.8.1an d6.3.3.8.2 .I tbecome sclea rtha tincreasin g SVTSvalue sgiv e riset oincreasin gvalue so fth ethreshin gspee dand ,a saresult ,t o increasingthreshin gseparatio nefficienc yan ddecreasin glos scost san d totalcosts .

17b Table 6.3.3.7.1. Effects of the value of the proportlnal factor 2V in the integrating action of calculation of VFSCo f control system 4 for cost situation 2. TOC= total costs, CLO = machine loss costs, VTAV = mean threshing speed, TSEAV = mean threshing separation efficiency, WLAV = mean walker loss, FOBAV = mean V-belt tension, CVW = costs of wear of V-belt.

2V TOC VTAV CLO TSEAV WLAV FOBAV CVW x 10"3 fl'ha"1 m's fl-ha % leg's-1 N fl'ha" 0.1 308.32 28.25 80.23 73.58 0.0687 1497.87 0.53 1 291.30 33.12 62.75 81.19 0.0532 1411.07 1.06 2.5 289.62 33.97 60.82 82.50 0.0518 1396.99 1.24 5 289.22 34.18 60.38 82.88 0.0515 1394.03 1.28 10 289.98 34.18 61.13 82.96 0.0525 1395.52 1.28 20 294.71 34.61 65.77 82.21 0.0576 1403.90 1.37 40 305.74 34.43 76.65 79.95 0.0691 1445.91 1.53

Table 6.3.3.8.1. Effects of the set value for the threshing separation efficiency (SVTS) of control system 4 for cost situation 2. TSE = threshing separation efficiency, VTAV = mean threshing speed, T0C = total costs, CLO= machine loss costs, CBLE = costs of extra breakage loss under adverse conditions, TLAV = mean threshing loss, SLAV = mean breakage loss, WLAV = mean walker loss, BLEAV = mean extra breakage loss under adverse conditions

SVTS TSE VTAV TOC CLO CBLE TLAV BLAV WLAV BLEAV % % m-s-1 fl>ha_1 fl-ha-1 fl>ha_1 kg-s_1 kg-s-1 kg-s-1 kg-s_1 80 76.46 30.61 314.06 85.43 2.29 0.0249 0.0411 0.0771 0.2056 85 79.86 32.44 300.54 71.79 2.67 0.0210 0.0460 0.0632 0.2299 90 82.50 33.97 289.62 60.82 3.04 0.0180 0.0500 0.0518 0.2499 95 84.71 35.64 279.91 51.10 4.30 0.0154 0.0546 0.0416 0.2730

179 Table 6.3.3.8.2. Effect on total costs (TOC in fl-ha-1) of the set value for the threshing separation efficiency (SVTS) of control system 4 for cost situation 1 ... 6.

cost situation 12 3 4 5 6 SVTS 80 486.68 314.06 704.31 393.93 515.52 325.29 85 476.76 300.54 686.05 377.93 499.19 311.90 90 468.24 289.62 670.80 365.31 486.30 301.82 95 460.97 279.91 656.20 353.51 473.98 292.67

The increase of the costs of grain breakage loss under adverse condi­ tions (CBLE) is less than the decrease in machine cost for the parameter values chosen in our simulation (see 2.3.2), even for the last step in SVTS from 90% to 95%. It could therefore be concluded that SVTS might be increased to above 95%,bu t it must be realised that no straw breakage is included in the model, so that the negative effect of increased threshing speed on walker loss and especially sieve loss is unknown. The threshing speed reaches its maximum in swath 5 — 8 when SVTS=90%. When SVTS=85* it does so most of the time as can be concluded from table 6.3.3.8.3 and figure 6.2.4.8.2. These aspects of threshing speed make it clear that the effect of straw breakage on walker and sieve losses should be included in the simulation model as well as in the control system. However, much more research into these aspects is required,before this can be done.

The results in the tables of this section also demonstrate the importance of the threshing separation efficiency. Manufacturers of combine harvesters are aware of this,as can be concluded from the newly designed combine har­ vesters having extra rotating grain separation elements.

6.3.3.9. The strati feed rate monitor

The straw feed rate can be measured by either the auger torque or the dis­ placement of the elevator chain. Auger torque was taken as the default case. Table 6.3.3.9.1 shows the total costs for both. The positive effect of auger torque measurement is very slight especially for control systems

180 Table 6.3.3.8.3. Effects of twodifferen t setvalue s of the threshing separation efficiency {SVTS) for the individual swathso f the simulation. The swaths are indicated by these sequence number (Sw)an d the field test number (Tn). TSE =threshin g separation efficiency, VTAV= mea n threshing speed, CLO= machin e losscosts , TOC - totalcosts , CBLE= cost s of extra grainbreakag e under adverse conditions, TLAV =mea n threshing loss, BLAV =mea nbreakag e loss, SLAV =mea n sieve loss, WLAV =mea nwalke r loss, BLEAV =mea nbreakag e loss under adverse conditions TSE ÎW CLÖ TOC CBLÊ % m-s-1 fl'ha-1 fl'ha-1 fl'ha-1 SVTS %:85 90 85 90 85 90 85 90 85 90 Sw Tn 1 61 84.589. 4 24.2 26.7 78.81 57.41 294.08 272.58 0.00 0.33 2 3985. 3 90.3 24.5 27.1 75.10 53.10 299.41 277.24 0.01 0.40 3 1284. 9 89.9 25.0 27.7 93.98 68.51 317.57 291.450.0 0 0.98 4 5568. 2 71.7 32.0 34.058.9 8 52.53 296.28 290.26 2.01 2.44 5 57 81.7 82.3 38.1 38.5 43.23 41.35 291.94 290.10 4.44 4.49 6 52 93.7 94.8 37.5 38.8 37.94 34.83 255.74 252.79 7.16 7.53 7 37 64.1 66.0 37.1 38.4 94.66 89.47 313.20 308.21 3.53 3.91 8 3378. 9 79.1 38.4 38.6 90.47 90.30 334.95 334.80 4.21 4.24

TLAV BLAV SLAV WLAV BLEAV -l -l -l -l x 10-" kg-s'- 1 kg*s kg*s kg's kg's SVTS % :85 90 85 90 85 90 85 90 85 90 SwT n 1 61 219 151 313 380 129 129 847 590 1564 1901 2 39 169 112 271 332 120 120 721 482 1353 1658 3 12 184 126 301 376 140 144 966 682 1507 1880 4 55 289 256 371 418 63 63 353 308 1853 2080 5 57 180 173 548 557 64 63 248 232 2741 2785 6 52 94 84 777 813 133 133 334 298 3886 4065 7 37 332 311 527 571 89 89 895 843 2633 2855 8 33 208 207 556 559 86 86 770 769 2779 2794

181 Table6.3.3.9.1 .Tota lcost s {TOC)an dwalke rlos s (WL)affecte db yth e choiceo fstra wfee drat emonitor .

Costsituatio n2 Costsituatio n6 controlsyste m TOCfl'ha -1 augertorqu e 293.53 299.18 301.93 289.62 302.04 309.00 312.44 301.8! displacement 293.51 299.39 303.06 289.68 302.05 309.76 313.68 302.41

WL kg's-1 auger torque 0.0485 0.0609 0.0627 0.0518 0.0316 0.0473 0.0494 0.041: displacement 0.0486 0.0607 0.0638 0.0527 0.0316 0.0481 0.0507 0.042'

3 and 4 because of the decrease in walker loss caused by an increase in threshing separation efficiency. These results from the threshing speed control which, thanks to the longer delay, has ample time to bring the speed to the optimum. The other cost components do not differ, because machine speed is not affected.

6.3.3.10. The level of the simulated measurement noise

The added noise was set at zero, at twice the default levels and at half those levels (see 6.2.4.2) to check the sensitivity on costs. The results are given in table 6.3.3.10.1.

Table 6.3.3.10.1. Effects of noise levels related to the default level; for cost situation 2 and the control systems referred to. TOC = total costs, CL0 = machine loss costs, VMAV = mean machine speed

Control system factor to default T0C CL0 VMAV TOC CL0 VMAV T0C CLO VMJ 1 1 1 1 noise level fl'ha 1 fl'ha 1 m-s ' fl'ha 1 f 1' ha" m-s" fl'ha" fl'ha" m-s 0 293.52 62.69 1.078 298.95 70.99 1.121 289.36 60.46 1.1 1.5 293.52 62.69 1.078 298.92 70.94 1.121 289.40 60.47 1.1 1 293.53 62.64 1.077 299.18 71.31 1.123 289.62 60.82 1.1 2 293.51 62.64 1.077 299.27 71.67 1.126 289.69 61.19 1.1

182 Forcontro lsyste m1 onl yth enois ei nwalke rlos smeasuremen tha sa n effecto ncosts .Th eeffec ti snegligible,becaus eo fth elo wbreakpoin t frequencyo fth efilte ri nth econtrol ,s otha talmos tal lnois ewa s filteredout .I npractic ethi sha sals ot ob edone . Incontro lsyste m2 i ti sjus tth enois ei nth estra wfee drat emeasure ­ mentwhic hha sa neffect .Th eeffec to ncost sremain sslight,becaus eals o hereth efilte rha sdon eit swork . Incas eo fcontro lsyste m4 th ethreshin gseparatio nefficienc y \(TSE)wa s measuredwit hadde dnoise .Thi snois ei sals oheavil yfiltere dbecaus e ofth esmal lproportiona lfacto ri nth ecalculatio no f VFSC(se e6.3.3.7) .

Thenois ewa scoloure db ymean so fhigh-pas sfilter .Th ebreakpoin tfre ­ quencyo fthi sfilte rwa sals ovaried .Th edefaul tvalu ewa s0. 1rad* s Table6.3.3.10. 2show sresult sfo rbreakpoin tfrequencie so f 1,0.1 ,0.01 ,

Table6.3.3.10.2 .Effect so fth ebreakpoin tfrequenc yo fth ehig hpas s filterso fth enois egenerator sfo rcos tsituatio n2 an dcontro lsyste m 1an d4 . T0C =tota lcosts , VMAV =mea nmachin espeed , WLAV= mea nwalke rloss .

Control system 1 4 4 TOC VMAV WLAV TOC VMAV WLAV 1 _1 _1 rad" s l f1 ' ha_1 m'S l kg*s fl«ha m*s kg-s 1.0 293.52 1.078 0.0486 289.07 1.123 0.0516 0.1 293.53 1.077 0.0485 289.62 1.124 0.0518 0.01 293.52 1.077 0.0485 290.03 1.132 0.0534 0.001 293.60 1.079 0.0488 291.00 1.199 0.0654

Theeffect sar eagai nnegligibl ysmall .A tth esmalles tbreakpoin t frequencya relativel ylarg evariatio ni nth elo wfrequencie sremain si n thesignal ,thu sbring sabou tth ehighes tdeviatio ncompare dt oth erea l value,resultin gi nextr acosts .Th eeffect so nmea nmachin espee di n controlsyste m4 i nthi ssituatio nwa sremarkabl ean dwa sprobabl ycause d byth enegativ enois evalue stha twer efortuitousl yi nth emajority , makingth esimulatio noutpu tstochasti ct oa certai nexten tan dprovidin g thereaso nwh yth ehigh-pas sfilte ri nth enois egenerato rwa sintroduced .

183 Theeffec to fnois eo nstra wfee drat e (FS) andthreshin gseparatio nef ­ ficiency (TSE) wasinvestigate dseparatel ya tdoubl eth enois elevel .I n table6.3.3.10. 3th eeffec to fnois eo n FSca nb esee nt ob eth eprincipa l reasonfo rincrease dcost smainl yi nth efor mo fth eincrease dlos scosts .

Table6.3.3.10.3 .Effec to fnois esuperpose do nth emeasuremen to ffee d rate (FS) andthreshin gseparatio nefficienc y (TSE),i nturn,i ncontro l system4 an dcos tsituation s2 an d6 .Th enois elevel sar etwic eth e defaultlevels . TOC= tota lcosts , CLO= cos to fmachin eloss , VMAV =mea nmachin espee d

Costsituatio n TOC CLO WAV TOC CLO VMAV fl'ha"1 fl'ha-1 m-s 1 fl-ha-1 fl-ha"1 m*s ' nonois e 289.36 60.46 1.122 301.62 53.88 1.051 justnois eo n FS 289.4289.41 1 61.02 1.127 301.96 54.34 1.053 justnois eo n TSE289.4 289.47 7 60.61 1.123 301.75 54.01 1.051 noiseo n FSan d TSE 289.69 61.19 1.126 302.19 54.58 1.053

6.3.3.11. The sequenoe of simulated swaths

Thecontro lsystem sreac tt oth evariatio ni ncro pparameter si nthei r ownspecifi cway .I nthi ssimulatio nth ecro pparamete rvalue sdiffe ri n asequenc e determinedb yth eswat hsequence .Th eslowe rth eadaptio nt o> cropparameter san dth emor eth esuccessiv eparamete rvalue sdiffer ,th e longerth etim etha tth esyste mwork sbelo woptimu mlevel .Thu sth echose n swathsequenc ei nfac taffect sth eresults . Thisca nb einvestigate db ychangin gth eswat hsequenc ei nth esimula ­ tion.Th esequenc ei nwhic hth eswat hdat awer erecorde ddurin gth efiel d measurementswa schose na sth ealternative,whic hcorrespond st oth eincreas e inth etria lnumbers ,tha ti s12 ,33 ,3 7 ...instea do f61 ,39 ,1 2.. .o f thedefaul tsequence ,selecte dt omak eth edifference sgreater . Table6.3.3.11. 1show sth ecos tdat afo reac hcontro lsyste man dfo r costsituatio n6 .Th edifference sar esligh t (maximum1.5 %fo rcontro l system4 )s otha ti tca nb econclude dtha tth esequenc eha sno tmuc himpact .

184 Table6.3.3.11.1 .Effec to ntota lcost so fth esequenc eo fth eswath s duringth esimulatio nfo rcos tsituatio n6 (costsi nfl'ha" 1)

Control system 0 1 2 3 4 Swath TOC CLO TOC CLO TOC CLO TOC CLO TOC CLO sequence Default 306.7752.7 3302.0 449.9 0309.0 062.3 1 312.4465.6 8301.8 254.1 2 Tests 307.4653.5 5302.1 849.2 1308.7 962.4 0312.3 465.9 1297.3 449.9 1

Thedifferenc ei nth ehand-controlle dsituatio ni sremarkabl y Large,fo r whichreaso nth eorigi no fthi sphenomeno nwa sstudie di nth ecos tdat a oneac hindividua lswath .Th edefaul tsequenc eo fth eswat hi sgive ni n table6.3.3.11.2 .Th edifference sar emerel yi nth eorigi no fth elosse s andar ecause db yth edifference si nfee drat ea tth ebeginnin go feac h swathowin gt oth eadaptio no fmachin espee dtha ttake sabou t4. 0seconds . Incontro lsyste m4 th ereaso ni sth etim erequire dfo rth eadaptio no f threshingspeed .

Table6.3.3.11.2 .Effec to ncost san dlos so fth eindividua lswath sdepen ­ dingo nth eswat hsequenc edurin gth esimulatio no fhan dcontrolle drun s andcos tsituatio n2 .Th edefaul t (Def.)sequenc ei sgive ni nth etabl e whileth etest s (Test)sequenc ei sth eincreasin gnumbe rsequenc e(12,33 , 37, ...).

Machinelos s Timeliness Meanwalke r Totalcost s costs losscost s loss Swathtes t fl'ha-1 fl'ha -1 fl'ha-1 -1 kg's "l number Def. Test Def. Test Def. Test Def. Test 61 273.66 276.56 15.77 18.96 58.10 57.89 0.0071 0 .0094 39 278.17 283.41 17.33 22.87 54.56 54.29 79 120 12 283.92 283.22 27.55 27.10 57.55 57.28 173 169 55 298.32 298.15 45.92 45.82 50.06 50.04 195 193 57 314.12 314.07 58.49 58.46 54.34 54.33 315 315 52 298.69 295.00 42.13 38.73 61.51 61.15 280 255 37 320.79 326.59 77.89 84.02 44.94 44.58 517 576 33 386.60 382.78 136.79 132.43 52.05 52.58 1180 1146

185 6.3.3.12. Sample interval

The sample interval (DT) of the "digital" control causes a delay in the information transfer. This affects the optimum adjustment of speeds and hence the costs.. Table 6.3.3.12.1 shows the effect for the various control systems in cost situation 2. No real differences are found in control system 1 as this system is in itself slow. In control systems 2, 3 and 4 it is clear that the shortest interval is optimal,althoug h the differen­ ce between 0.1 s and 0.25 s is not of importance and that between 0.25 s and 0.5 s i sliaht. From 0.5 to 1 s the cost increase is about 10%, which is

Table 6.3.3.12.1. Effects of the sample interval {DT) of the control calculation. T0C = total costs, VMAV =mea n machine speed

Control system 1 2 3 4 TOC VMAV TOC VMAV TOC VMAV TOC VMAV DT fl*ha_1m'S~l fl'ha-1m-s-1 fl«ha-1m's-1 fl'ha-1m's-1 0.1 293.57 1.078 298.83 1.120 301.52 1.120 289.20 1.120 0.25 293.60 1.079 298.83 1.120 301.57 1.120 289.20 1.119 0.5 293.53 1.077 299.18 1.123 301.93 1.123 289.62 1.124 1.0 298.61 1.076 301.52 1.131 304.96 1.132 291.89 1.132

too large. It is caused by the increase in machine loss due to the increa­ sed machine speed.

6.3.3.13. Timeconstant in the first-order transfer of the walker separation model

The determination of the time constant in the first-order transfer, model­ ling the redistribution of straw on the straw walkers, was too vague as can be seen from 2.3.4. To investigate the importance of the effect of this parameter (TAUW) on the simulation results, it was varied. In addition to the default value of 0.8 s, 0.5 and 1,2 s were also tested. The effects in cost situation 2 are shown in table 6.3.3.13.1.

186 Table6.3.3.13.1 .Effect so fth evalu eo fth etim econstan t {TAUW) in theredistributio nproces so nth estra wwalkers .Th edifference sar e giveni npercentages . TOC= tota lcosts , WLAV= mea nwalke rloss , VMAV =mea nmachin espeed .

Controlsyste m 0 TOC WLAV TOC WLAV VMAV TOC WLAV TOC WLAV x 1 1 1 1 TAUW fl'ha kg' s fl-ha" .kg-s" m-s" fl'ha-1 kg-s"1 fl'ha"1kg's" 1 0.5 300.21 0.0358 294.68 0.0489 1.071 300.55 0.0626290.8 0 0.053 diff.% 0.35 3.4 0.39 0.8 0.6 0.5 2.7 0.8 299.16 0.0346 293.53 0.0485 1.077 299.18 0.0609289.6 2 0.0518 diff.% 0.23 2.0 0.23 0.4 0.4 0.3 1.6 1.2 298.47 0.0339 292.85 0.0483 1.081 298.43 0.0599288.9 6 0.050

Walkerlos sdecrease dwit hincreasin g TAUW. Thiscoul db eexpecte dbe ­ causeth estra wfee dvariation sar eflattere dthen .I ncombinatio nwit h thenon-linea rtransfe ro fwalke rlos st ofee drat ethi sresult si na lowe r meanlevel . Thehand-controlle dsituatio nshowe ddifference so f3 %an d2 %an dth e effectca nonl yb edescribe da sslight .Th ereduce dlos sbring sabou t anincreas ei nmachin espee di ncontro lsyste m 1,bu tsom edifferenc ere ­ mains (0.8%an d0.4%) .Difference si ncontro lsystem s2 an d4 ar eabou t thesam ea si nhan dcontro las ,i nou rsimulation ,ther ei sn ofeedbac k ofsimulate dlos st omachin espeed . Thedifference si ntota lcost sar eth esam efo ral lsystem sbecaus e thewalke rlos scos ti sjus ta smal lpar to fth etota lcosts .Thu s TAUW doesno tinfluenc eth esimulatio nresults .

6.3.3.14. Optimum parameter values for the simulation

Insom eo fth eprecedin gsection sth edefaul tparamete rvalue swer efoun d nott ob eth eoptimu malthoug hthe ywer eclose .T oinvestigat eth eeffec t ofthi sdeviation ,simulatio nrun swer edon ewit hth eoptimu mparamete r valuesi nsituatio n2 fo ral lcontro lsystems .Tabl e6.3.3.14. 1demonstrate s howthes erun sdiffe rfro mthos ewit hdefaul tvalues .Th edifference sar e verysligh t (lesstha n0.4% ) sotha tthe yd ono taffec tth econclusion s ofth eprecedin gsections .

187 Table6.3.3.14.1 .Cost scalculate di nsimulatio nrun swit hdefaul tvalue s ofparameter san drun swit hoptimu mvalues .Th ealtere dvalue swere : P =20.0 , PCTC= 10.0'lo"" , 2v =5.0-1 03 an dƒ .o fcontro lsyste m2 = c -i b 0.1 rad's 1 T0C - totalcosts , CLO= machin elos scost s

Control system: 1 2 3 4 TOC CL0 T0C CL0 T0C CLO T0C CLO fl'ha-1 fl'ha-1 fl'ha"1 fl'ha"1 fl'ha-1 fl'ha-1 fl'ha"1 fl'ha-1 Default 293.58 62.64 299.37 71.45 302.06 74.11 289.62 60.82 Optimal 293.58 62.64 298.82 70.79 301.63 73.53 288.94 59.98

Finally,th eeffec to fcalculatio nste p DELTwa schecke di ncontro lsys ­ tem4 an dcos tsituatio n6 (seetabl e6.3.3.14.2) .Th evalu e0.0 5 scom ­ paredt o0. 1 s,represente da cos tdecreas eo f 1.11 fl'ha ,du emainl yt o adecreas ei ncalculate dwea ro fth eV-belt ,a sth eforce si nth eV-bel t areproportiona lt oth edifference si nthreshin gcylinde rspee dbetwee n theconsecutiv ecalculatio nsteps ,an dth eshorte rth esteps ,th eslighte r thedifferences .Sinc eth ewea rcos tfacto ri sa nestimate don ebase do n simulationswit h DELT= 0.1 s,thi sfacto rma yonl yb euse dfo rtha t "DELT" value. Itwa sconclude d thereforetha tth echose ncalculatio ninterva lwa s shortenough .

Table6.3.3.14.2 .Cost scalculate d insimulatio nrun swit hth eusua lcal ­ culationtim einterva l DELT=0. 1 andth evalu e0.05 , TOC= tota lcosts , CLO= machin elos scosts , CVW =cost so fwea ro fV-belt , WLAV - meanwal ­ kerloss .

DELT TOC CLO CVW WLAV s fl'ha-1 fl'ha-1 fl'ha-1 kg's-1 0.10 301.82 54.12 1.30 0.0413 0.05 300.71 53.93 0.36 0.0411

188 6.4.CONCLUSION SFRO MSIMULATION S

Themai nconclusion sdraw nfro mconsideratio no fth esimulatio nresult s aregive nhere .Th egenera lconclusion swil lb epresente di nth enex t chapter.

Comparisono fsimulate dwit hmeasure ddat ademonstrate sa fai rdegre eo f harmony.Th eresult so fth esimulate dcontro lsystem scoul dno tb eteste d inth efiel da sth enecessar yhardwar ei sno tye tavailable ,bu tthei r behaviourwa sno tunexpected .Th eselecte dsyste mparamete rvalue sar e closet oth eoptimu mvalue sfo rsimulation .Th echose nparamete rvalue s forth ecos tfactor san dth etimelines slos scurv erelatin gt oa weathe r risko f25 %resul ti nrealisti ctota lcos tdata .

Theinpu to fth esimulation sha sbee ntake nfro mth ecro pan dweathe r conditionsrecorde d forth efield san dmachine so fth eIJsselmeerpolder s DevelopmentAuthorit ylarge-scal egrai nfar m (IJ.D.A.).Th espeed sthe n selectedb yth emachin eoperato rwer edefine da sstandar d forth emanuall y controlled situationassume di nthi sstudy . Thecos tdecreas eachieve dwit ha nassume dmachin ecapacit yincreas e of10 %thank st oa machin edesig nimprovemen twa sfoun dt ob e23.1 3fl*h a 1 (ss8% ) forou rsimulation so nth ebasi so fth ecos tsituatio no fth eIJ.D.A . Thisvalu eca nb ecompare dt oth edecreas ecalculate db yth eDepartmen t ForOperationa lResearc ho fIJ.D.A .itsel f as34.5 0fl"h a1 .A sthes evalue s aremuc hinfluence db yth emea nmachin espee dan dth eshap eo fth etime ­ linesslos scurv ethe yar ei nfac to fth esam eorder .Thi sallow sthe mt o beuse di ncomparin gth edifference sbetwee ncontro lsystems .Th ecos t decreasei smuc hhighe ri nth ecas eo fcos tsituation si nwhic hth e timelinesslos srisk sar elowe rtha n25% .

Thecalculate dtota lcost so fth evariou scos tsituation sconsidere d differa grea tdeal .Th etimelines slos sha sa grea tinfluenc eo nth e costs. Thetimelines slos scurv ebase do n 162/3 %weathe rris kresult si nhig h costsan dindicate sth eimportanc eo ftimelines slos si nharves tseason s withunfavourabl eweather .I na nattemp tt oescap ethes ehig hcost si n suchsituations ,farmer softe nprefe rt ous emachine swit ha larg eharves t

189 capacitycompare dt oth ecapacit ythe ynee dfo rth eare at ob eharvested . However,thi sresult si nhig hmachin ecosts . Thisals oindicate stha tth etimelines slos scurv et ob econsidere di n controlsystem sha st ob eadapte dt oth econditions /shoul dthe ychang e duringth eharves tseason .Th efarme rals oreact sintuitivel yb yharves ­ tingfaste ro rlonge rpe rda ywhe nth eweathe rbecome smor eunfavourable .

Whentimelines slosse sar econstan t (fixedharves tperiod )o rwhe nth e riskfacto ri s25 %(harves tperio dvariable) ,ther ei sa wid erang eo f optimumspeeds ,s otha tselecte dmachin espeed sma yvar y +^10 %withou t anyconsiderabl eeffec to ntota lcosts .

Theeffec to ncos tdecreas eb yth econtro lsystem sfo rth esimulate dIJ.D.A . costsituation s (2an d6 )i sver ysligh t (from3.2 %t o-0.1%) .Minimu m costsar efoun dfo rth eloss-fee drate-threshin gseparatio ncontro lsyste m (4),followe db yth elos scontro lsyste m (1)an dth eloss-fee drat econtro l system (2).Th ecost sfo rloss-fee drate-threshin gspee dcontro lsyste m (3)ar eeve nhighe rtha nthos eo fmanua loperation .Th emanuall yselecte d speedswer ever yclos et oth espeed stha twer eoptimall yadjuste db yth e controlsystems .I nsuc ha cas en ocontro lsyste mgive smuc hbenefit . Itha st ob erealised ,however ,tha tth emanuall yselecte dspeed suse d asa standar di nthi sstud yar esample stha tar eperhap sfortuitousl y correct.I naddition ,th emachin eoperator so fth eIJ.D.A .ar etraine d toselec tspeed stha twil lresul ti na tota lmachin elos sleve lo fabou t 0.5%.Thi sleve lwa scalculate da soptimu mb ymean so fa cerea lharves t optimisationmodel,man yo fwhos edat awer eals ouse di nth ecos tcalcula ­ tiono fou rsimulation .I nothe rcos tsituations ,suc ha s3 an d4 where , duet oothe rtimelines slos scurves ,highe rspeed sar echose nb yth econ ­ trolsystems ,th edifferenc efro mmanua loperatio ni sconsiderable ,bu t inthi scas eth eoperato rwoul dprobabl yals ohav eselecte dhighe rspeed s inmanua lcontro li fh ei sfamilia rwit hth ecos tbackground .

Controlo fmachin espeed ,whic hadapt sno tonl yt oslo wlos svariation s affectedb ycro pproperties ,bu twhic hals oadapt st oexpecte dtimelines s lossesowin gt oth eweathe rdurin gth ecours eo fth eharvest ,wil lbrin g savings.Contro lo fth ehig hfrequenc yvariation si nstra wdensity ,however , willbrin gn oworthwhil eextr asavings .

190 Machine speed canb e controlled by a simple loss control system assu­ ming the presence of an accurate grain loss measurement device.A manual control system, including regular inspection of loss and the awareness of the optimum loss levelwil l possibly give the same effect.

The control of threshing speed has tob e achieved by optimising themea n threshing speed, since reacting to thehigh-frequenc y feed rate variations brings nobenefit .

It iseviden t from the above-mentioned conclusions that other factors such as selection of the feed rate monitor,th e sample interval and the value of control parameters are not important in cost minimisation.

The optimisation of the threshing speed isbeneficia lbecaus e totalmachin e loss costs are very greatly influenced by the threshing speed.A control system isneede d that considers the threshing loss and grainbreakag e as well as the sieve and walker loss caused by straw length reduction.

Consideration of the simulation resultsbrough t insight into the effects of the assumptions and simplifications on simulation: Cost situations The results of thevariou s costsituation s clearly showed the sensitivity of the optimisation to the chosen costparamete r values.Th e effect on the optimum speeds is slightexcep t for the timeliness loss curve.Th e impor­ tance of this curve leads to the conclusion that the adaption of control to the change in timeliness loss expectations will be a very important tool for optimisation. High-frequency disturbances The importance of thehigh-frequenc y variations in feed rate was found tob e slight, so that the assumptions made on filtering, and controlb y a combination ofquas i steady state calculation ofoptimu m speeds and dynamic speed feedback arepermissible . Parameter estimation The decision toperfor m off-line parameter estimation in simulating the loss-feed rate control system (2)ha d an effect on theresults . Itar e the assumptions made in the simulation,an dno t the differences between the systems themselves,tha t caused a loss controlwit h lower

191 overall costs than obtained with loss-feed rate control, where there was no continuous feedback of loss in the simulation. The loss control system did have feedback so that one parameter value of the simple loss-to-feed rate equation used in the calculation of optimum machine speed was esti­ mated continuously, while the second parameter was adjusted at a fixed level roughly estimated on the basis of the knowledge of the loss-to-feed rate relation of the input used. In practice, this information does not exist, so that some kind of an estimation procedure is needed. This can best be done by a two-parameter estimating procedure, like that suggested for the loss-feed rate control system, but in that case "on line". In such a case it is more important to make a slowly adapting good estimate than a faster but less accurate one.

Sélection of control systems The selected control systems clearly showed the importance of each extra input signal used. Itha sbecom e clear that the threshing speed control requires additional information on grain breakage and the effects of straw breakage. If this isprovided , then theproble m of interactionbe ­ tween machine speed and threshing speed control is solved.

192 7. Final conclusions and recommendations

The cost savings of automatic machine and threshing speed control are small compared towell-planne d manually controlled adjustment. Well planned means thatunde r certain harvest conditions the optimum loss level is regularly calculated and inspected. In this case the cost savings of each of the tested control systems areno thighe r than what could havebee n achieved by machine design improvements,givin g ane t capacity increase of approximately 5%.

In theeven t thatn o suchwel lplanne d conditions occur,th e savings will be much greater.Thi smean s thatwhe nbot h the optimisation of theharves t operation and the lossmeasuremen t are included in the control system,one canb e sure that the chosen speeds are close to the optimum and that less experienced operators will alsowor k with minimum costs. A control system with measurement devices for several functions,also provides process information thatenable sbette r manual adjustments to bemade .

Automatic machine speed control isprofitabl e as the control system reacts to the mean level variations in croppropertie s and strawden ­ sity.Th e control system cannot react correctly to the crop property variations, including straw density,occurrin g over a shortdistance . This isbecaus e of the delay in theproces s and the considerablemea ­ surement noise.N oworthwhil e extra cost savings occur for thatreason . The automatic control system canb e a loss control,bu t knowledge of the correct shape of the loss-to-feed rate curve is very important, so that a good estimate of this curve isneede d toensur e that the system calculates the rightoptimu m speed. For this reason the loss- feed rate control system described in this study is recommended.

193 A lossmeasurin g device that ismor e accurate than the devices available nowadays is essential to the control. If awel l trained operatorknow s the optimum loss level and has an accurate lossmeasurin g device athi sdisposa lh ewil l also be able to select machine speeds that result in costs close to minimum harvest costs,as the optimum speed range is fairly wide (see also point 4i n this chapter).

3.Threshin g speed control is alsoprofitable ,a s the separation at the threshing cylinder affects machine loss very much. Such a control system justneed s toreac t to the mean level variations of cropproper ­ ties and feed rate. Iti sessentia l in such a system tooptimis e the threshing speedbase d on all effectso f threshing, thati s threshing loss, grain breakage, threshing separation efficiency and strawbrea ­ kage affectingwalke r and sieve loss. Obviously, the systemwil l be complicated and costly, and requires various measuring devices.Som e parameters like threshing loss and grain breakage which are difficult to establish with ameasuremen t device,ca nb epu t into the system by hand. A threshing speed control that reacts tohigh-frequenc y variations of straw feed rate givesn o extra costreductio n compared to control of low-frequency variations in feed rate and cropproperties .

4. The impacto f timeliness losso n the calculation ofoptimu m machine speed isgrea tbu t in general somewhatneglecte d as it is difficult to calculate properly. An automatic control system based on amicro ­ processor makes itpossibl e toinclud e such calculations in the control system. Then the change inweathe r conditions in the course of the harvestperio d can alsob e included. The machine operator will adjust the extento f the expected timeliness losses at the microprocessor and the control systemwil l compute the optimum speed. In such control systems the costminimisatio n is adapted to the conditions of the spe­ cificharves tseaso n and thebenefi to f the systemwil lprobabl y be greater than hasbee n calculated in this study,a s it also minimises

194 costs for aperio d longer thanon e season. Further research is needed into thewa y the timeliness loss curveha s tob e adjusted to the spe­ cificweathe r until then the immediate weather forecast,th e area still tob eharvested , the loss sensitivity of the crop tob eharveste d and other factors. Thequestio n then arises as to the role the farmer'spersona l com­ puter or accessible programs at large computers canpla y in this cal­ culation. In view of the important role of the timeliness loss and the wide range of speeds thatgiv e costs close to theoptimum , one can imagine thati f theoptimu m loss level canb e computed more precisely with the aid of anoff-lin e computer,an d the combine harvester is equipped with agoo d lossmeasurin g system, the costswil l alsob e close to the minimum level of the "on-line"contro l systemswit h fewer computation facilities.Combinatio n of the two systems isals o feasible.

The loss-measuring systems available nowadays only observe anoncon - stant fraction of the real loss. The fraction isunknown ,henc e the absolute loss level is also unknown. In this study (section 3.3.2) theprincipl e of a system isworke d out thatestimate s an absolute loss level.Fo r such a system amicroprocesso r isneede d for proper calculation. A microprocessor isneede d for automatic control ofmachin e speed buteve nmor e for automatic control of threshing speed,as theoptimi ­ sation of threshing speed, invie w of threshing loss,walke r loss, sieve loss, threshing separation efficiency and grain damage isa rather complex phenomenon. A microprocessor used on the combineharveste r couldhandl e a large number ofothe r useful tasks.Th e inspection of several functions in themachin e and theprocesse s in the machine,a swel l as the calcula­ tion ofmea n levels,capacitie s and costs.Th e last settings before an emergency stopo r end of a swath canb e stored and used again when restarting. Even ifn o automatic control is introduced, the use of amicropro ­ cessor on the machine will beworthwhil e for calculation of the optimum setting ofmanua l adjustments,includin g the settings for the concave, sieves and eventually the optimum frequency of thewalke r movements.

195 In future,mor e researchwil l beneede d in the areasmentione d below. a) Themai n general conclusion of this study is the great importance tob e attached to an accurate loss-measuringdevic e forbot h auto­ matic control and manual control.Th e commercial loss-measuring devices just give information as to change of loss levels.Ne wmea ­ suring deviceshav e tob e developed. Possibly such unitswil l be built into threshing and separation process inspection devices as indicated in chapter 3.3.2. Othermeasuremen tprinciple s too,suc h as radiation or reflection have tob e considered asonl y the mean levelo f lossha s tob eknow n so that long averaging periods may be incorporated in the calculation. b) "On-line"automati c machine speed control for optimum operation has tob e compared with "off-line" computer calculations,togethe r with manual loss control.Fo r such comparison, amode lha s first tob e developed inwhic h the relation between the timeliness loss curve and the factors affecting timeliness loss isworke d out.The n the harvestoptimisatio n mustb eworke d out andquantifie d by harvest strategy adaption to timeliness loss expectation. Finally, computer programs have tob e developed for the farmersper ­ sonal computer to calculate optimum strategies for combineharves ­ ting. Further research on low-frequency and mean levelvariatio n in crop properties affecting machine lossha s tob e included. c) The mean level variations in croppropertie s affecting losshav e to be analysed in more detail also in order todevelo p parameter-esti­ mation techniques for the loss-to-straw feed rate equations for machine speed control. d) A system for the calculation of theoptimu m threshing speed inclu­ ding the concave adjustmentha s tob e developed inwhic h threshing loss,breakag e of grain,walke r loss and sieve losshav e tob e in­ cluded. If this research is supported by computer simulation, the model must include the strawbreakag e and itseffec t onwalke r loss andsiev e loss. Estimation of the threshing coefficientmus t thenb e improved. Finally, the interaction of machine speed control and threshing speed control has tob e studied.

196 From the conclusions arrived ati n this study, some idea can be obtained of the systems,tha t canb e expected tob e developed in future. In arelativel y short time an "off-line"manua l control system based upon a computer calculation of optimum loss level and lossmea ­ surement on the combine harvester canb e developed. The optimum loss level canb e calculated weekly or after aperio d inwhic h thetime ­ liness lossexpectatio n has changed. The loss levelha s tob e controlled manually by means of an improved loss-measuring system orb y very regular (hourly) comparison of grain-loss monitor readings with real lossi n the field. On the longer term amicroprocessor-base d automatic control system canb e developed that includes the following qualifications given in the ordero f introduction: - automatic control ofmachin e speed by means of the loss-feed rate control systemworke d out in this study and including the adaption to changing timeliness lossexpectations ; - a threshing and separation inspection system thatgive s information about thewalke r loss, grain flow,threshin g cylinder separation efficiency andwalke r separation; - a continuous calculation of optimum threshing speed and concave ad­ justment using the information provided by the above-mentioned inspec­ tion system and the manual input,o n the extent of threshing loss, grainbreakag e and strawbreakage . The threshing speed thenha s tob e alteredb y handwhe n so indicated by the system output.

197 Appendix

A1.1.a . Harvesting cereals with the combine harvester The combine harvester There are combineharvester s inus e that are pulled and driven by atrac ­ tor,bu t it isquit e common for combineharvester s tob e self-propelled. Such amachin e is equipped with an engine and 4wheel s and canb e opera­ ted by one person.Th e following operations areperforme d by themachine : mowing,conveying , threshing,separatio n of grain and straw,cleaning , intermediate storage of the grain and unloading of thegrain .Figur e A 1.1.1 gives a sidevie w of such amachin e asuse d in this study and figure A 1.1.2 a cross section.A smaller machine with adifferen t set-up

Figure A 1.1.1. Side view of the combineharvester , considered in this study (see text)

199 FigureA 1.1.2.Cross-sectio no fcombin eharveste rB

(seefig .A 1.1.3 )wa suse da tth estar to fth estudy .Machin especifica ­ tionsar egive ni ntabl eA 1.1.1 . Atth efron ti sth eheade r (1)wher eth ecro pi scu tb ymean so fa cutterba r (2), thecro pbein gpositione dwit ha ree l (3)an dseparate d fromth eres to fth ecro pb ycro pdivider s (4).Th emowin gwidt hi s6. 0 m,whil eth ewidt ho fth eelevato ri s1.6 0m .Th emowe dcro pi sconveye d toth ecentr eo fth ecuttin gtabl eb ymean so fa nauge r (5)an dcarrie d overt oth eelevato r (6),whic hconvey si tt oth ethreshin gcylinde r(7) . Thebar so fth ethreshin gcylinde r (8)bea tth estra wan dth eear san d owingt oth espee do fabou t30. 0m -s theear sar eaccelerate ds oth e grainsar eloosene dfro mth eears .Th egrai nthe ni sseparate d fromth e strawvi ath econcav efo r70-99% .Th egrai nremainin gi nth eear si sknow n asthreshin glos san dleave sth emachin ei nth estraw .Th edamage dgrai n iscalle dbreakag eloss .Figur eA 1.1.4 showsa flo wdiagra mo fth egrai n andth estra wi nth emachine . Thegrai ntha ti sno tseparate db yth econcav ei stransported ,togethe r withth estraw ,t oa rotar yseparato r (10)wher eabou thal fo fth ere ­ maininggrai ni sseparate dvi aa grat e (11). Threshing loss,breakag e

FigureA 1.1.3.Cross-sectio no fcombin eharveste rA

200 TableA 1.1.1 .Specification so fth ecombin eharvester suse di nthi sstud y

Machine A Machine B Manufacturer: Sperry New Holland Ditto Type : M 140 8080 Maximumwidth ,,withou theade r m 3.04 3.53 Maximumlength ,withou tdivider s m 7.70 8.82 Maximumheight ,withou tcabi n m 3.12 3.78 Gatheringwidt ho fheade r m 4.5 5.90 Feeding-augerspee d s_1 3.2 3.2 Straw-elevatorspee d m"S l 2.23 2.63 Threshing-cylinderdiamete r m 0.60 0.6 width m 1.25 1.56 raspbar s number 8 8 Concavear clengt h m 0.609 0.609 bars number 14 14 Rotaryseparator ,diamete r m - 0.59 speed m*s l - 23.5 concavelengt h m - 0.63 Strawwalkers ,numbe r m 5 6 length m 3.80 3.30 speed s-1 3.67 3.67 stroke m 0.11 0.11 Weight kg 6000 8800 lossan dth econcav eseparatio ndepen do nth espee do fth ethreshin gcy ­ linderan dth ethroughpu to fstra wmass . Thenth estraw-grai nmixtur ei sprocesse db yth estra wwalker s(12) , consistingo f6 sid eb ysid efixe dnarro wsieve smounte do ncrankshafts . Theycarr you trotationa lmovement swit hshift so fphase ,s oth estra w isthrow nu pan dth egrai npasse sthroug hth estra wan dth esieves .Thi s treatmentseparate salmos tal lth eremainin ggrai nfro mth estraw ,th e strawbein gconveye dt oth erea ran ddroppe do nth eground .Th egrai n remaining (threshed)i nth estra wleavin gth estra wwalkers ,i scalle d thewalke rlos s (UL) (0.01%-5%). Theseparate dpar to fth egrai ni scollecte di na grai npa n (13)an d conveyedb ya shakin gactio nt oth esieve s (14).Tw oreciprocatin gsieve s separateth egrai nfro mth echaf fan dshor tstra wwit hth eai do fa n airstrea mgenerate db ya fan . Thecleane dgrai ni stransporte d intoth egrai ntan kfo rtemporar y storage.Th epartl ythreshe dloos eear sar econveye dt oa smal lthreshin g cylinderfo rfina lthreshing .Grai ndischarge d fromth emachin etogethe r withth estra wan dchaf ffro mth esieve si scalle dth esiev eloss . Thesiev ean dwalke rlos stogethe rar ecalle dseparatio nlosses . Threshingloss ,breakag elos san dseparatio nlosse sar ei nthi sstud y knowna smachin elosses .

201 s s s s — s V s -Pre harvest and cutterbar losses Total grain losses l'1 Figure A 1.1.4. Diagram of the flow of straw {FS. ). an d grain (.FG..) of machine B. Straw isequivalen t tomateria l other than grain (m.o.g)

Cereal harvest organization When the grain tank is filled or almost filled, the grain is discharged by aconveye r into agrai nwago n which is either driving alongside the combine harvester or parked at the end of the field.Th e wagon pulled by a tractor transports the grain to a storage place where the grain is weighed, cleaned and,i f necessary,dried . Forprope r coordination of the harvestingan d transportation,thewago n should wait for the combine or there shouldb e one ormor ewagon s waiting atth e field as intermediate storage forhaulin gb y a tractor.Sometime s iti s the combine harvester thatha s towait . Otherwaitin g periods arise outo fmachin e breakdowns,res tperiods , machine maintenance andweathe r conditions (showers). Much of the necessary maintenance canb e carried outwhe n one has towai t until a wetcro p hasdrie d in the field. Toodam p straw causesmachin e failures and malfunctioning of the threshing and separationparts .

The cereal harvest can only startwhe n the cropha s reached so-called combine ripeness.Fo rwhea t this is the case when the grain moisture contentha s once been 20%o r less. The IJsselmeerpolder DevelopmentAuthorit y (U.D.A.), where parto f the research was done,start sharvestin g wheat after the "combine-ripe" stage andwhe n thegrai nmoistur e content issmalle r than 28% (VanKampen , 1969; Hagting, 1976).Ther e isn onee d fordryin gwhe n the moisture content is smaller than 17%.S oon e could waitwit h harvesting until a moisture content of < 17%ha sbee n reached by thenatura l dryingprocess . InWester n Europe thisproces spossibl y takes too long,thu s giving a too small number ofworkabl e hours. Itals ocause s field losses after the crop reaches combine ripeness; these losses are called the timeliness

202 losses and comprise shatter loss, animal consumption,see d sprouting,dr y matter decrease and losses occurring at theheade r atmowing : cutting loss andheade r loss.

Consequently,harvestin g athighe r moisture contents results in an increase inth e number ofworkabl e hours and lower timeliness losses.Lowe r time­ liness losses anddryin g costs can alsob e achievedwit h amachin e of higher capacity.Th e same effect canb e obtained by increasing thedrivin g speed of the combine harvester,bu t thisbring s an increase inth e machine losses.

A1.1. b Control system terminology

In this section there is aver y brief explanation of control engineering and the terminology used in it.A detailed description canb e found in Jacobs (1974) and Cool (1979).

Aprimar y objective ofmos t control systems is tomak e some physical variable take on a desired value; forexampl e to give the speed of the machine a value that isoptima l in financial terms.Thi s is to be achieved by adjusting some mechanism forexample ,adjustin g the position of thepisto n of ahydrauli c cylinder that actuates the V-beltvariator . Thenon-instantaneou s nature of the response isaccounte d forb y re­ garding thephysica l controlling variable and the controlled variables as the input and output of a dynamic system,calle d the controlledprocess .

The effect of uncertainties, that isdisturbin g phenomena,ca nb e redu­ ced by using feedback as shown in fig.A 1.1.5,wher e a control element adjusts the controlling variable u depending upon the difference e between the desired value or setvalu e x and the fedback , actual Value y of the controlled variable, for instance the actual speed.Mea ­ suring instruments are needed in the feedback path tomeasur e the con­ trolled output.

Disturbances of theproces s Z Inputo f the outputo f the control controlled control = input of the process output Control Controlled desired actuating elements controlling process controlled value x signal e variable variable y (setvalue )

feedback signal Measurement device

Z =measuremen t disturbances m

Figure A 1.1.5. Scheme of a feedback control system

203 Undesiredvariatio ni ninpu tvariable swhic haffec tth evalu eo fth e output,occu ri nth eproces sa swel la si nth emeasuremen tinstrument s (calleddisturbances) . Disturbancesar eon eo fth emos tcommo nreason swh ya controlle d variablema ydepar tfro mit sdesire dvalu ean dwh yfeedbac kcontro li s necessary.Th edisturbance swil lb eregarde di nthi sstud ya scompose d ofvariation si nmea nlevel san di nth etim edomai na sslowl yan dquickl y varyinglevel stha tca nb espli tu pb yFourie ranalysi sint oharmoni c variations,o rfrequenc yfunction si nothe rwords . Thedisturbance si nth eproces so fthi sstud yar emainl ydu et onatu ­ ralvariatio ni ncro pproperties .Thes evariation sca nb emodelle da s colourednoise .A ver yimportan tpar to fth edisturbance sar eweather - affectedcro ppropertie stha tresul ti nvariation si nmea nlevel ,a si s thecas eals oi nvariatio ncause db ybree dan dvariet yo fth ecro punde r consideration.

Thecontrolle dproces sinclude spur etim edelays .Whe nth emeasure d controlledoutpu tdiffer sfro mth edesire dvalu ebecaus eo fa distur ­ bancei nth eproces sa contro lactio nwil lb etaken .Th eresul to f thisactio ni sonl yeviden ti nth econtrolle doutpu tafte rth edela y inth eprocess .Thi sresult si ndeviation sfro mth edesire dvalu ean d inadditio ni tca ncaus estabilit yproblems .Th econtrolle doutpu tca n showlarg eoscillation swhe nth econtro li sno tproperl yadjusted .Thi s canb efoun dou tb yobservin gth erespons eo fth econtrolle doutpu tt o aste pi nth einpu to fth econtro le .I fth etransien tshow ssufficient ­ lydampe dbehaviour ,th eadjustmen ti ssafe . Thestabilit yo fth econtro lsyste mca nals ob einvestigate dwit hth e helpo fth efrequenc yrespons et oharmoni cvariation sa tth einpu to fth e openloop ,tha tmean swithou tfeedback .Th egraphica lrepresentatio no f thetransfe rfunctio n G(s) = y(s)/x(s) evaluatedfo rth eimaginar yvalue s of s(= jw),i.s calleda Nyquis tplo t (Jacobs,1974) .Fro mth ecurv eo f thefigur eca nb ederive dwhethe rth eclose dloo psyste mi sstabl eo r not.

Whereth edisturbance sthemselve sca nb emeasure dthe yca nbecom e theinpu to fth econtrol .Th esyste mi sthe ncalle da fee dforwar d controlsyste man di sshow ni nfig .A 1.1.6.I nou rstud ysuc ha syste m isuse dfo rcontro lo fthreshin gspee do nth ebasi so fth estra wfee d ratevariation smeasure dbefor eth estra wenter sth ethreshin gcylinder .

Measuremenh, t Disturbances elements Z P ' Control Controlled elements controlling process controlled: variable variable

FigureA 1.1.6 .Schem eo fa fee dforwar dcontro lsyste m

204 Thedesire dvalu eo rse tvalu ex o fth econtro lsyste mi sderive dfro m anoptimu mspee dcalculatio ni nth ewa yshow ni nfig .A 1.1.7.Th e criterionfo rth eoptimisatio ni sminimu mharves tcost san dth einpu t forthi scalculatio ni sth evalu eo fon evariabl eo rmore ,measure di n theproces san dsom e"cos tfunctions .Th etas ko fth espee dcontro li s toadjus tth espee dt oth evalu ecalculate db yth eoptimisation .

+ Control Optimisation —*•Controlle d criterion desired'iP elements process Process ,i i , i value

cost Measurement parameters device

Optimisationinpu t Measurement device

FigureA 1.1.7 .Schem eo fa contro lsyste mincludin gcalculatio no f setpoin tb yoptimisatio n

A 1.2.LITERATUR E A1.2.1 . Introduction Inthi sappendi xth ereference so finteres tt othi sstud yar ereviewed . Thechronologica lan dsystemati csuccessio nar eshow nt ob eparallel . Theconclusio ndraw nfro mthi sstud yi sgive ni nchapte r1.2 .

A 1.2.2. Feed rate aontrol Theactua lstra wfee drat eo fth ecombin eharveste r (FS inkg* s l)i s derivedfro mth eproduc to fmachin espee d (I'Mi nm* s ),mowin gwidt h (CLi nm )an dstra wdensit yo nth efiel d (SDi nkg«m~ 2),s o FS- VM'CL'SD. Asth estra wdensit yvaries ,adjustmen to fth emachin espee dca nb eapplie d tocontro lth efee drate .I nsom ecase sfee drat econtrol sar ecalle ddri ­ ving-speedcontrols .Fo rthi sreaso nth edistributio no fcro pdensit yha s beenrecorde db yman yresearchers ,includin gKühn ,1969 ;Eimer ,1966 ; Feiffer,1964 ;Huisman ,197 4an di susuall ygive ni nterm so fa variatio n coefficient (seeals o4.2.2) .

Asearl ya s 1956th eRussia nresearche rDymnic h (1956)reporte do na tractor-drawncombin eharveste rwit ha fee drat econtrol .I nthi scas e thetorqu eo fth ethreshin gcylinde ri sutilize da sa ninpu tvariabl et o controlth ethroughput .Th etorqu ei smeasure dmechanicall yan dth etrac ­ torgoverno ri sadjuste db ya three-wa yswitc han da nelectromotor .Th e onlyresul th ereporte dwa sa variatio ncoefficien to fth efee drat eo f 3.38%a ta los sleve lo f1% . Nastenko (1959)report sa contro lsyste mo na self-propelle dcombin e harvesteri nwhic hth emechanicall ymeasure dtorqu eo fth ethreshin gdru m affectsth epositio no fth ehydrauli cvalv eo fth eV-bel tvariato ri nth e drivingmechanism .

205 Sincetha ttim eothe rRussia nwriter shav edescribe d throughput-control systemso nSK- 3combin eharvesters . Bogdanova (1960),i npresentin ga surve yo fcontro lsystems ,ha s referredt oth etorqu eo fth ethreshin gcylinder ,th ethicknes so fth e strawlaye runde rth eelevato ran dth ethicknes so fth estra wlaye ro n thewalke ra sfee drat esensors . Nakhamkin(1960 )describe svariou selectrical/hydraulica lsystem susin g theinput-variabl e thicknesso fth estra wlayer .Gulgae v (1960)present s anelectrical/mechanica lsyste mwit hth etorqu eo fth ethreshin gcylinder .

Itwa sno tunti l196 2tha tMichajlo vwen tint oth esubjec to fth eexpec ­ tedadvantages .H eascertaine dtha tth eyield so farea so f 150m 2an d even1 m havea Gaussia ndistributio nwit ha naverag evariatio ncoeffi ­ ciento f20% .Sinc ether ei sa nexponentia lrelatio nbetwee nth estra w feedrat ean dth elosses ,th eaverag e losseswil lb elowe rwhe nth evaria ­ tioncoefficien ti slowe r (see A 1.2.7). Hecalculate dthat ,a ta stra wfee drat eo f3 kg« s 1, adecreas ei n thecoefficien to fvariatio nfro m20 %o r30 %respectivel yt oa valu e of0 %wil lgiv e25 %o r33 %lowe rlosse srespectively .Takin ga los s levelo f 1.5%,the nth estra wfee drat eincreas ewil lb etheoreticall y10 % or 13%respectively .Consequentl yth eeffec tlargel ydepend so nth evalu eo f thecoefficien to fvariation ,bu tals oo nth eshap eo fth elos scurv ean d theadjuste dfee drat elevel .I nth earticl en oattentio ni spai dt oth e magnitudeo fth evariatio no fth efee drat ewhe nth emeasuremen testablishe d thelos scurve .I fth evariatio nha dbee nlower ,i twoul dhav eresulte d ina lowe ran dflatte rlos scurve ,wit hles seffect .Measuremen to na fieldo f8 hectare swit ha controlle dcombin eharveste rshowe da capacit y increaseo f11% .Ther ei sn oindicatio na st oho wequa llos slevel so f bothcontrolle dan dnon-controlle dmachine sar edeal twith .Thi si sth e greatestproble mdurin gfiel dmeasurement si nadditio nt otha to fth e quantificationo fth eoperator' sinfluenc eo nth econtrolle dan dnon - controlledmachines .

Feiffer (1964)fro mth eDD Rals oreport so na hig hvariatio ni nth estra w density ( 4.2.1)an dconclude sthat ,i norde rt omaintai nth efee drat e ata constan tlevel ,i tshoul db epossibl et ovar yth edrivin gspee d withina rang eo f 1-2metre sa ta rat eo f0. 1m' s Accordingt oFeiffer ,a nothe rbenefi to fa contro lsyste mi st oreduc e enginean dtransmissio noverload .I nvie wo fth efac ttha tther ei sa timela gbetwee nmowin gth ecro pan dmeasurin gth efee drat ea tth eele ­ vator,h epropose st ocarr you tmeasuremen ta tth eauge ro ra tth ecutte r bar.

Rumjantsev(1964 )report so na nelectric-hydrauli c feedrat econtro la t SK-3an dSK- 4combin eharvesters .Th estra wfee drat esenso rmeasure dth e thicknesso fth estra wlaye ri nth estra welevator .H estate stha tth e coefficiento fvariatio ndroppe db ya facto ro f1. 2t o2. 4a ta stra w feedrat eleve lo fabou t3 kg* s duet oapplicatio no fth econtrol .H e alsomentione da nincreas ei ncapacit yo f43% , butindicate dtha tthi s figurei srathe r highan dshoul db ere-investigated .

Gurarri (1964) was the first person to simulate the control system.H e compared the stability of a feed rate control, calculated by meanso f simulation with an analog computer, with field results, Thedesire dvalu eo rse tvalu ex o fth econtro lsyste mi sderive dfro m anoptimu mspee dcalculatio ni nth ewa yshow ni nfig .A 1.1.7.Th e criterionfo rth eoptimisatio ni sminimu mharves tcost san dth einpu t forthi scalculatio ni sth evalu eo fon evariabl eo rmore ,measure di n theproces san dsom e'cos tfunctions .Th etas ko fth espee dcontro li s toadjus tth espee dt oth evalu ecalculate db yth eoptimisation .

+ Control Optimisation —>Controlle d criterion desired"P elements process Process ,i 1 : i value

cost Measurement parameters device

Optimisationinpu t Measurement device

FigureA 1.1.7 .Schem eo fa contro lsyste mincludin gcalculatio no f setpoin tb yoptimisatio n

A 1.2.LITERATUR E

A1.2.1 . Introduction Inthi sappendi xth ereference so finteres tt othi sstud yar ereviewed . Thechronologica lan dsystemati csuccessio nar eshow nt ob eparallel . Theconclusio ndraw nfro mthi sstud yi sgive ni nchapte r1.2 .

A 1.2.2. Feed rate control Theactua lstra wfee drat eo fth ecombin eharveste r (FS inkg* s l)i s derivedfro mth eproduc to fmachin espee d (VUi nm"s_ 1),mowin gwidt h (CLi nm )an dstra wdensit yo nth efiel d (SDi nkg» m 2), so FS = VU-CL-SD. Asth estra wdensit yvaries ,adjustmen to fth emachin espee dca nb eapplie d tocontro lth efee drate .I nsom ecase sfee drat econtrol sar ecalle ddri ­ ving-speedcontrols .Fo rthi sreaso nth edistributio no fcro pdensit yha s beenrecorde db yman yresearchers ,includin gKühn ,1969 ;Eimer ,1966 ; Feiffer,1964 ;Huisman ,197 4an di susuall ygive ni nterm so fa variatio n coefficient (seeals o4.2.2) .

Asearl ya s195 6th eRussia nresearche rDymnic h (1956)reporte do na tractor-drawncombin eharveste rwit ha fee drat econtrol .I nthi scas e thetorqu eo fth ethreshin gcylinde ri sutilize da sa ninpu tvariabl et o controlth ethroughput .Th etorqu ei smeasure dmechanicall yan dth etrac ­ torgoverno ri sadjuste db ya three-wa yswitc han da nelectromotor .Th e onlyresul th ereporte dwa sa variatio ncoefficien to fth efee drat eo f 3.38%a ta los sleve lo f1% . Nastenko (1959)report sa contro lsyste mo na self-propelle dcombin e harvesteri nwhic hth emechanicall ymeasure dtorqu eo fth ethreshin gdru m affectsth epositio no fth ehydrauli cvalv eo fth eV-bel tvariato ri nth e drivingmechanism .

205 Sincetha ttim eothe rRussia nwriter shav edescribe dthroughput-contro l systemso nSK- 3combin eharvesters . Bogdanova (1960),i npresentin ga surve yo fcontro lsystems ,ha s referredt oth etorqu eo fth ethreshin gcylinder ,th ethicknes so fth e strawlaye runde rth eelevato ran dth ethicknes so fth estra wlaye ro n thewalke ra sfee drat esensors . Nakhamkin(1960 )describe svariou selectrical/hydraulica l systemsusin g theinput-variabl e thicknesso fth estra wlayer .Gulgae v (1960)present s anelectrical/mechanica lsyste mwit hth etorqu eo fth ethreshin gcylinder .

Itwa sno tunti l 1962tha tMichajlo vwen tint oth esubjec to fth eexpec ­ tedadvantages .H eascertaine dtha tth eyield so farea so f 150m 2an d even1 m havea Gaussia ndistributio nwit ha naverag evariatio ncoeffi ­ ciento f20% .Sinc ether ei sa nexponentia lrelatio nbetwee nth estra w feedrat ean dth elosses ,th eaverag elosse swil lb elowe rwhe nth evaria ­ tioncoefficien ti slowe r (see A 1.2.7). Hecalculate dthat ,a ta stra wfee drat eo f3 kg' s 1, adecreas ei n thecoefficien to fvariatio nfro m20 %o r30 %respectivel yt oa valu e of0 %wil lgiv e25 %o r33 %lowe rlosse srespectively .Takin ga los s levelo f 1.5%,the nth estra wfee drat eincreas ewil lb etheoreticall y10 % or 13%respectively .Consequentl yth eeffec tlargel ydepend so nth evalu eo f thecoefficien to fvariation ,bu tals oo nth eshap eo fth elos scurv ean d theadjuste dfee drat elevel .I nth earticl en oattentio ni spai dt oth e magnitudeo fth evariatio no fth efee drat ewhe nth emeasuremen testablishe d thelos scurve .I fth evariatio nha dbee nlower ,i twoul dhav eresulte d ina lowe ran dflatte rlos scurve ,wit hles seffect .Measuremen to na fieldo f8 hectare swit ha controlle dcombin eharveste rshowe da capacit y increaseo f11% .Ther ei sn oindicatio na st oho wequa llos slevel so f bothcontrolle dan dnon-controlle dmachine sar edeal twith .Thi si sth e greatestproble mdurin gfiel dmeasurement si nadditio nt otha to fth e quantificationo fth eoperator' sinfluenc eo nth econtrolle dan dnon - controlledmachines .

Feiffer (1964)fro mth eDD Rals oreport so na hig hvariatio ni nth estra w density ( 4.2.1)an dconclude sthat ,i norde rt omaintai nth efee drat e ata constan tlevel ,i tshoul db epossibl et ovar yth edrivin gspee d withina rang eo f1- 2metre sa ta rat eo f0. 1m* s Accordingt oFeiffer ,a nothe rbenefi to fa contro lsyste mi st oreduc e enginean dtransmissio noverload .I nvie wo fth efac ttha tther ei sa timela gbetwee nmowin gth ecro pan dmeasurin gth efee drat ea tth eele ­ vator,h epropose st ocarr you tmeasuremen ta tth eauge ro ra tth ecutte r bar.

Rumjantsev (1964)report so na nelectric-hydrauli c feedrat econtro la t SK-3an dSK- 4combin eharvesters .Th estra wfee drat esenso rmeasure dth e thicknesso fth estra wlaye ri nth estra welevator .H estate stha tth e coefficiento fvariatio ndroppe db ya facto ro f 1.2t o2. 4a ta stra w feedrat eleve lo fabou t3 kg* s l duet oapplicatio no fth econtrol .H e alsomentione da nincreas ei ncapacit yo f43% ,bu tindicate dtha tthi s figurei srathe rhig han dshoul db ere-investigated .

Gurarri (1964)wa sth efirs tperso nt osimulat eth econtro lsystem .H e comparedth estabilit yo fa fee drat econtrol ,calculate db ymean so f simulationwit ha nanalo gcomputer ,wit hfiel dresults .

206 Since 1965ther ehav ebee npublication so nfee drat econtro li nNort h Americaan dWester nEurop ea swell . Friesen (1965)reporte do na mechanical/hydraulica l feedrat econtro l systemwit hth etorqu emeasure da tth ethreshin gcylinder .I nth efiel d thissyste mwa sshow nt oreac tpositivel yt ocrop-densit ydifferences , butth eeffect so nlosse shav eno tbee nmeasured .I twa sexpecte dtha t theoperato rwoul db eles sfatigue dan dtha tthi swoul dlea dt olowe r lossesan dhighe rcapacity . Likewise,Gos s (1965)make sn omentio no fan ycapacit yeffect so fa feedrat econtro lsyste musin gth eabsolut eai rpressur ei nth eintak e manifoldo fth epetro lengin ea sinpu tvariable .Eime r (1966)expect sth e strawfee dt obecom emor eunifor man dja mth emachin eless .

Kalimullin (1966)describe sa mechanica lsyste mo fmovabl ecrop-holdin g pinsa tth efron to fth eauge rtha twil lsmoot hth estra wfeed .Dependin g onth evertica lpositio no fth ependin gauger ,th epin shol dth ecro p moreo rless ,an dtogethe rwit hth eactio no fth eauger ,a mor eunifor m feedt oth ethreshin gcylinde ri saffected . Comparedwit ha norma lfee da ta leve lo f2. 7kg' s hemeasure da decreasei nmea nthreshin gtorqu e (9.9• >8. 4kgm ), i nmaximu mthreshin g torque (36.2- *15. 5kgm) ,i nvariatio ncoefficien to fth ethreshin g torque (43.3-» • 39.9%),an di nseparatio nlosse s (2.4- *1.0%) .Thes eresult s clearlysho wth eadvantage so funifor mfeed .

Bogdanova (1967)suggest sa syste mi nwhic hsmal lfee drat evariation sar e controlledb yvaryin gth eelevato rspeed .N oothe rreport so hthi ssyste m havebee nfound ,presumabl ybecaus ei tcanno twork .Sinc eth eelevato r notonl ycarrie sou tth econveyanc et oth ethreshin gcylinde rbu tals o thetakeove rfro mth eauger ,thi styp eo fcontro lintroduce sne wirregu ­ laritiesi nth etakeover .

Nakonetschny (1967)state stha ta contro lsyste mwit hfee drat emeasure ­ menta tth eelevato rincrease sproductivit yb y 10%,bu tfail st osa yho w thisha sbee ncalculated .

Eimer (1970)mention sth enecessit yo fvaryin gth eree lspee di naccordanc e withth evariatio ni nmachin espeed .A shigh-frequen tfee drat evariation s cannotb esuppresse dsufficientl yb ya machin espee dcontrol ,becaus eo f theinerti ao fth econtro lsyste man dth emachine ,h epropose st osuppres s theeffec to fthos evariation sb ymean so fa threshin gcylinde rspee d controlan da concav eadjustmen tcontro l (see 1.3.4).Mentio ni sals o madeo fth enee dt omeasur elosses .

Brouër (1970)deal swit ha simulatio ni nCSM Pcompute rlanguag ean dtest - resultso fa contro lsyste m (continuingth elin eo fGoss ,1965 )base do n thevariation si nabsolut eai rpressur ei nth eintak emanifol do fth e petrolengin eo fth ecombin e (orth egoverno rstrok efro meithe ra petro l ora diese lengine) .Th edigita lcompute rsimulatio nwa sdon ei norde rt o obtainoptima lparamete rvalue sfo rth econtro lsystem .I tcoul dno tb e usedfo rcalculatin gth ebenefi to fth esystem .B ymean so fthi ssimulatio n itwa sfoun dtha tth erespons etim eo fth esyste mwa s5 second sa ta dela y of 1secon dbetwee nmowin gan dthreshing .Thi smean stha tonl ylong-ter m changesi nth edensit yo fth ecro pcoul db efollowed .Therefor ei tha s beensuggeste dt omeasur eth estra wfee drat ea tth efron to fth emachine .

207 Afluidi csenso rt osens eth eamoun to fcro pjus tbefor ei treache s thecombin ewa steste dbu tdi dno twork .A gamm aradiatio nsenso ri nth e feederconveyo rdi dno twor kproperl yeithe rbecaus ei tneede dto olon g anintegratio ninterval .

Anelectrical/hydraulica l strawfee drat econtro lsyste mbase do nth e torqueo fth eauge rha sbee ndevelope da spar to fth epresen twriter' s research (Huisman,1974a ,1974b) .Th eeffec to fthi scontro lwa sslight , duet oa nerro ri nth eadjustmen tan di nth esyste mitself . Animprove dsyste mha sbee npu tforwar db yNaaktgebore n (1976)an dVa n Loo (1977).Thi ssyste mi scapabl eo fsuppressin gvariation swit hfre ­ quenciesbelo w0.4 8rad' s'/bu tenlarge svariation sbetwee n0.4 8an d2. 8 rad*s 1.Abov e2. 8rad* s* th econtro lsyste mdoesn' thav ean yeffec ta t all.I tha sbee nshow ntha tthi ssyste mlower sth evariatio ncoefficien t ofth estra wfee drat efro m12.2 %t o4.1% .Th estra wfee drat edat a consistedo fvalue saverage dove r2 0s . Also,th edifferenc ei nlos sleve l (losseffect )o ri nfee drat eleve l ( feed rateeffect )o fa controlle dsituatio ncompare dwit ha non-control ­ ledsituatio nwer ecalculated .I ti sexpresse da sth edifferenc ei nleve l asa percentag eo fth enon-controlle dsituation .Thi scalculatio nwa s basedo nth etheor ytha twil lb ementione di nA 1.2. 7an do nth edecreas e inth ecoefficien to fvariatio n from12. 2t o4.1% .Whe nth elos seffec t iscalculated ,th efee drat eleve li skep tconstan tan dvic eversa .Th e resultsdepen do nth eloss-fee drat ecurve .The ywer ecalculate dfo ra specificsprin gan dwinte rwhea tsituation .Th efee drat eleve lan dth e losslevel ,als oaffec tth eresult .Tabl eA 1.2.2. 1show sth eresult so f thesecalculations .

TableA 1.2.2.1.Fee drat eeffec tan dlos seffec tinfluence db yth elos s levelan dstra wfee drat eleve l spring wheat winter wheat Lossleve li nkg» s 0.005 0.02 0.005 0.02 Feedrat eeffec ti n% 3.6 5.2 0.3 2.1

Feedrat eleve li nkg* s 1.3 5.3 1.3 5.3 Losseffec ti n% 1.6 28.1 0.14 2.3

Thisshow sth edependenc eo fth eresult so nth esituation .A scircumstance s arecontinuall ychanging ,th etota leffec tdurin gsom eharves tseason s cannotb epredicte dfro mthes edata .Moreover ,th eeffect sar eunderesti ­ matedbecaus eth evariatio nwa scalculate dfo rth eaverag evalue so ffee d ratea t2 0s interval .I nthi swa yonl yvariation si nfrequencie sles stha n about0.0 8rad* s1 ar etake nint oconsideration ,althoug hth econtrolle r cansuppres sfrequencie ssmalle rtha n0. 5rad* s

Besidesth efee drat econtro lsystems ,tha tar emean tt okee pth elosse s ata desire dlevel ,simila rsystems ,relatin gt oth epowe ro fth eengine , havebee nreporte don . Jofinov (1967)deal swit ha syste madaptin gth edrivin gspee dt oth e deliveredengin epowe rwher ea highe rdrivin gspee dcoul db etolerate d invie wo fth elosse sincurred .Th ethrottle dengin ecompressio nha sbee n takena sa ninpu tparamete ri nthi ssystem .I nth ecas eo fa nengin epowe r surplus,th edrivin gspee di scontrolle db yth ethreshing-cylinde rtorque .

208 Reichel (1969)refer st oa syste mcontrollin gth edrivin gspee do f self-propelled agriculturalmachine s (ingeneral )wit hth efue lconsumptio n asinpu tparameter .Th eadjuste dvalu eo fth efue lconsumptio no fa har ­ vesterca nb ederive d fromth ewalke rloss . Since 1972,Kawamur aha sbee npublishin go na small-head-feedin gtyp e ofric ecombin eharveste rwit ha stra wfee drat econtro lsyste m(Kawamura , 1972,1974 ,1975 ,1977) .B ymean so fsimulation san dfiel dmeasurements , acontro lsyste mha sbee ndevelope di nwhic hth edrivin gspee dha sbee n optimizedb ymeasuremen to fth ethicknes so fth estra wlaye ra tth eintak e andadaptatio no fth eengin espeed .Th eai mi sth eoptima lus eo fth eavai ­ lableengin epowe ran dth epreventio no fengin ejamming . Kruse (1982)report so na simila rsyste mi na rotar ycombin efo rcorn . Amicroprocessor-base dmachine-spee dcontro lha sbee ntested .Th econtro l purposei st outiliz eth eavailabl eengin epowe rcompletely ,circumstance s permitting.Th erotationa lspee do fth eengin ean dth efeede rtorqu ear e useda sinpu tparameters .Whe nth efeede rtorqu ereache sa certai nminimu m value,th epowe rcontro li sswitche don .I fth efeede rtorqu ereache sa certainmaximum ,the nth edrivin gspee di sslowe ddow nt opreven tjamming . Theeconomica ladvantage sarisin gou to fthes esystem sar eagai nno t calculated.

A1.2.3 . Loss controls Sinceth edevelopmen to fth eacousti cgrain-los ssenso r (Feiffer,1967 ; Reed,1968 )i tha sbee npropose dt ous ethi ssigna la sinpu tvariabl e forfeedbac kcontro lsystems .Ree d (1969)mention sthis ,bu tdoesn' t presentan yresult sobtaine dwit hsuc ha system . Kühn (1968)suggest sth ecombinatio no fa los scontro lwit ha fee drat e control.Th edesire dvalu eo fth efee drat econtro lca nb ederive da sa resulto fth elos smeasurement .Thi smetho dca nb euse dt osolv eth epro ­ blemo fth ebi gtim ela gbetwee ngeneratin gth efee drat ean dsensin gth e losscause db ythi sfee drate ,resultin gi na slo wcontrol .H eascertai ­ nedthat ,a ta simila rfee drate ,th elosse svar yb ya facto ro f1 0becaus e ofdifference si nth emoiëtur econten to fstraw ,th eripenes san dth e greenparts .Eime r (1970)an dHuisma n (1974b)stres sth enecessit yfo r this.Male r (1974)indicate sth epossibilit yo fhavin gth eoperato rcon ­ trollingth edrivin gspeed ,o nth ebasi so fth emeasure dlosses .

Abi gdisadvantag eo fthes eacousti cgrain-los ssensor si stha tth erati o betweenth eamoun to fregistere dgrai nan dth erea llos si sno tconstant , whichpreclude sthe mfro mus ea sabsolut eloss-measurin gdevices .There ­ forethe yshoul db eregularl ycalibrate dsevera ltime spe rhour ,bu tthi s isseldo mdon e (seeals oth eresult so fthi sstud yi n3.3.1 ). Nevertheless , someresearcher shav eteste dsimila rsystem si npractice .

Fekete (1981)publishe dth eresult so ftest si nHungar yo n5 machine s equippedwit hfee drate/los scontrols .A st othi ssystem ,al ltha tha s beenmad eclea ri stha tth eauge rtorqu esigna li suse da sa fee drat e parameteran dtha tth elosse sar emeasure db ya los smonito rhavin gacous ­ ticsensors . Theprobabilit ydistributio no fth eauge rtorqu esigna lo fth eautoma ­ ticallycontrolle dmachin eshow sth epea ka ta lowe rauger-torqu eleve l thani sth ecas ewit ha manuall ycontrolle dmachine .I nth epower-densit y spectrumles spowe rwa sfoun da tfrequencie sbelo w7. 5rad' s .A reductio n

209 in the power density of the corn head drive torque, has been noted in the frequency range of 0.63-3.14 rad's l. In tests with wheat and corn, where the losses have been kept equal at levels between 0.9 and 1.3%, it was found that the feed rates of the automatically controlled machine were from 9 to 20% higher than those of non-controlled machines. During the whole harvest season the net capacity in wheat and rape-seed was respectively 5.2% and 22% higher. Under the constraints of the circum­ stances the harvesting costs were 6-7% lower. These data have not been specified with regard to the harvested area, the circumstances and their variations. Therefore it is difficult to check their validity in other situations.

McGechan (1982) published results of a research project in Scotland, in which the influence of control systems on the decrease of the combined results of separation loss and timeliness losses has been researched analytically. Two not varied loss equations as a function of the feed rate, so-called loss-feed rate curves, from publications of Philips (1974) and Audsley (1974) have been used. The losses, according to not-calibrated grain-loss monitors and the driving speed were recorded from 3 machines, working under practical conditions. Assuming a crop yield of 5000 kg*ha 1 and a grain- straw ratio of 1, the variation of the realised loss was converted to variations of crop densities via both loss curves. Based on statistical assumptions this variation was converted into standard deviations of three sources : 01 = correlated in that it changed slowly through the crop 02 = uncorrelated and therefore totally unpredictable 03 = sampling variability introduced by the grain-loss monitor These data were later used to calculate analytically the total loss in given assumed situations : a)constant-spee doperatio n b)constant-los soperatio n c)optima lcontro lsyste mbase do na grain-los smonito r d)a tabl eauge rtorqu econtro lsyste m Inthi scalculatio nth etimelines slosse sar eincluded ,base do na 20 0h a cerealfarmin goperatio ni nScotland . Furthermorei twa spossibl et ocalculat eb ysimulation ,usin gth ere ­ cordedcro pdensit yprofiles ,th eeffect so fa contro lsyste mbase do na grain-lossmonito ran don ebase do na tabl eauge rtorque-contro lsystem . Theresult sshowe dtha tth ebenefit saccordin gt osimulation susin gth e loss-controlsyste mwer esmalle rtha nthos eobtaine dwit hth eanalytica l calculations.Fo rth emos tlikel ylos sequation si twa sanalyticall ycal ­ culated,tha tcompare dt oa constant-spee doperation ,a noptimu mcontro l systembase do na grain-los smonito ralone ,resulte di na smalle rlos so f amer e0. 4to n (i.e.£.40 ,— ),base do na tota lyiel do f100 0tons .I na croptha tshowe da maximu mbenefit,thi swa s0. 9ton .A syste mwit ha tabl e augercontro lsyste mincrease sthes estatistic sb y20% .Th econstan tlos s operation,whic hi sth etheoretica luppe rlimit ,presente dbenefit samoun ­ tingrespectivil y to1. 4an d2. 2tons .Th econclusio nwa stha tsuc ha n advantagei sto osmal lt ojustif yth edevelopmen to fa control-system .Th e evaluationsystem ,i fuse dfundamentally ,ca ngiv ecorrec tapproache st o reality,bu tsom eassumption swil lpossibl yaffec tth eresults .

1)A fixe dlos scurv eha sbee nused .Sinc egreatl ydifferin glos scurve s applyi nreality ,th evariatio ni nstra wdensit yi sincorrectl ycalcu -

210 FigureA 1.2.1.Effec to fshap eo floss-to-fee drat erelatio no ncalcu ­ latedfee drate .Whe nrelatio n (1)wa suse di nth estud yb yMcGecha n thecalculate dfee drat evariatio nwa sa'-b 'whil erea lvariatio nwa s a-bbecaus eo frea lrelatio n (2)

lated (seefig .A 1.2.1).Assum ecurv e 1wa sused .Whe nth elos svaria ­ tionsoccu rwithi nth eare aA- Ban di nrealit ylos scurv e2 applies , thenth estra wdensit yvariatio nwil lb ecalculate dbase do nfee drat e variationsa'-b 1whil ethe yar ea- bi nreality .Thi smistak eca nthe n nolonge rb ecorrecte ddurin gth ecalculations .Therefor eth eadvantag e ofa constan tsyste mi sunderestimate dwhe nth erea llos scurv ei s flatter,an doverestimate dwhe nth erea llos scurv ei ssteeper .More ­ over,th ebenefi to fa loss-contro lsyste madaptin gt oth eshiftin go f loss-feedrat ecurve scanno tb ecalculate di nthi sway . 2) Thegrain-los smonito ran dth etorqu emeasurement shav eno tbee ncali ­ bratedregularly .Sinc eth erati obetwee nth emonito routpu tan dth e reallosse svaries ,th emeasure d losscurv ewil lvar yi nsteepness , evenwhe nth erea llos scurv edoe sno tchange .Thi sresult si nth esam e effecta sha sbee nmentione da t 1). Sucha neffec tca nhav ea grea t dealo finfluenc ei nvie wo fth efac ttha tth echoic eo flos scurv e hasmuc hinfluenc eo nth ecalculate dresults .

Therea lbenefit shav et ob einvestigate db ymean so fsimulation si nwhic h therea llos scurve sar euse dan dcorrec tlos smeasuremen ti sinvolved .

A 1.2.4. Threshing speed control Thecro pflo wvarie sa tth ethreshin gcylinde rdu et oth evariatio ni n drivingspeed ,workin gwidt han dstra wdensit yi nfron to fth ecutte r baran ddu et oth eredistributio ni nth eauge ran da tth epoin to ftrans ­ fert oth eelevator .A fee drat econtro lsyste misn' tcapabl eo fsuppres ­ singth ehighl yfrequen tirregularitie si nth efee drate .A sth econcav e andwalke rseparatio nar e (negatively)relate dt oth efee drate ,th e walkerlos swil lvar ypositivel ywit hthes efee drat evariations .Sinc e therotationa lspee do fth ethreshin gcylinde ran dth econcav eadjustmen t canaffec tth econcav eseparatio nan ds owalke rloss ,i ti spossibl et o correctth evariation si nwalke rlos si nthi sway . Withthi si nmind ,Eime r (1973,1974 )develope d acontro lsyste mi n whichth emeasure dfee drat econtrol sth ethreshin gcylinde rspee da swel l asth emachin espeed .A nincreas ei nfee drat eresult sa tfirs ti na nin ­ creasei nthreshin gspeed .Th edecrease dconcav eseparatio ni scompensated .

211 toa certai nextent ,b yth ehighe rthreshin gspeed .Whe nth eincreas ei n feedrat econtinues ,th edrivin gspee dwil lals ob eslowe ddow ni naccordanc e withth efee drat econtro lsystem .Th eproble mo fthi ssyste mi stha tth e relationbetwee noptima lthreshin gspee dan dfee drat eha st ob eknown . Sincethi srelatio ngreatl ydepend so nth ecro pconditions,i tha st ob e adaptedaccordingly .Eime rha sinvestigate dth eeffec to fth econtro l systemo na nirregula rfee dfo ron especifi crelatio no fthreshin gspee d tostra wfee drate .Th eresults ;o ftest sa ta naverag efee drat eleve lo f 3kg» s l fora threshin gcylinde r 1m i nwidth ,a twhic h6 kg* s 1 straw ispu tthroug hfo r0. 8seconds ,followe db y0. 8second swithou tfeed ,ar e giveni nth etabl ebelow .

TableA 1.2.4.1.Result so ftest swit hthreshin gcylinde rcontro lo f Eimer (1974) crop: wheat rye Threshingcylinde rcontro l offdut y ondut y offdut y ondut y Concaveseparatio n % 88 92 78 86 Threshinglos s % 0.8 1.1 1.5 0.8 Breakagelos s % 0.1 0.1 0.15 0.3 Max.torqu ethreshin gcylinde r Nm: 230 120

Duringfiel dmeasurement si n196 9wit hwhea tan dry ei twa sestablishe d thata tsimila rlos slevel si nwhea tan drye ,respectivel y40 %an d25 % higherdrivin gspeeds ,compare dt owha ta traine doperato rca nperform , couldb erealised .A naverag eo f20 %wa sals omentioned .Ther ewa sn o mentiona st oho wthi sresearc hwa scarrie dout . Mailander (1979)an dBrizgi s (1980)reporte do na threshin gcylinde r speedcontro lsyste mwhic hadapt sth espee dt oth emoistur econten to f soybeanso rcorn .Mailande rapplie sa relatio nbetwee nth emoistur econ ­ tentan dth edesire dspeed ,base do nth elos sdu et odamage dbeans .Th e systemo fBrizgi swa steste db ysimulation swit hCSM PIII .Owin gt oth e slowcharacte ro fth esyste mi tcanno tb ecompare dt oth ethreshin gspee d -fee drat esystem .

A 1.2.5. Process models Themodel so fth eproces si nth ecombin eharveste rar eimportan tmainl y becausethe ymak ei tpossibl et oinvestigat ecoherenc eo fth edynamic s ofth eproces san dth econtro lsystem .Artne r (1971)claim stha tth ebene ­ fit ofcontro lsystem sdepend so nth edisturbance san dth edynamic so f thesystem .A nanalysi so fth eprocess ,tha ti so fth esignal san dth e system,i stherefor enecessary .Fo rth esigna lanalysi sth einpu tan d outputsignal shav et ob einvestigated .Fo rth esyste manalysis ,model s areneeded .A snonlinea rtransfer soccur ,th eus eo fanalo gcomputer s isdesirable .Artne rhimsel fdoe sno tpresen tan yresults .Nowaday stime - dependentsystem sca nb esimulate do ndigita lcomputers,fo rinstanc ewit h CSMP (ContinuousSyste mModellin gProgram ,develope db yIBM ). Kirk (1977)reporte do na simulatio nmode li nFortra no fa combin e harvesteran dcompare dth eresult swit hfiel dmeasurements .H eapplie s descriptivemodel spartiall ydescribe db yPickerin g (1974).H econclude d thatth epredictio no fth elos so fth ewalke ran dth esieve sb ymean so f thefee dauge rtorqu ea tit sonl yinput ,wa smoderatel yaccurate .Som e detailso fth emode lwil lb eanalyse di nchapte r2 .A sfa ra si sknown , themode lha sno tbee napplie di npractice .Model so fth ethreshin gan d walkerseparatio nar eavailable .Ther ear en odetaile dcalculation sknow n withmodel sinvestigatin gth eeffec to fcontro lsystems . 212 A 1.2.6. Cost models The research done by McGechan (1982) is discussed in A 1.2.3. He used a cereal harvest model to calculate the total harvest costs and calculated the optimum machine speed and used it to calculate the optimum loss level and the benefits of the control systems at that level. In this study just two loss curves were used and therefore the control systems could not react to the change of loss curves. This is also the constraint in the studies of Oving (1980) and Baumgartner (1969). In these studies even the speed of the machine is not variable. Their results therefore differ from those of Kampen (1969), Boyce (1972) , and Philips (1974), where the machine speed is one of the variables that can be optimised. They all agree that a high-capacity machine is worth­ while, because of the timeliness loss. Philips (1974) calculated that the total costs were minimal at a machine loss level of 13 kg per ha for British conditions. Kampen (1969) reports that the optimum total machine loss level for the situation at the large-scale grain farm of the IJsselmeerpolders Development Authority is 0.5%. The optimum loss level for conditions of Fed. German Rep. seems to be 1% (Eimer, 1966) and for the DDR 1.5% (Heinrich, 1968). In all these models however, no adaptation of the optimal loss level to the shape of the loss curve is included.

A 1.2.7. Effect of variation in feed, rate on the loss-feed rate relation Michaijlov (1962) already reported on the Gaussian distribution of the straw feed rate around an average value, as having an impact on the loss level when the loss-feed rate relation is nonlinear. This has been studied quantitatively (Huisman, 1977; Van Loo, 1977) to calculate the influence of a decrease in coefficient of variation {CV) on the feed rate and losses (see figure A 1.2.2) .

Assume a loss-feed rate relation according to WL= k'expia'FS) (the drawn line is from field measurements in oats; k = 2.2*10 z and a = 0.944, WL in %an d FS in kg«s l) and the feed rate distributed around an average value y_ (in the figure 4 kg*s ) is Gaussian. We will consider the manual- control situation where a. = 0.488, so that CV = 12.2% (line: ) and the situation with a feed rate control as it was measured in the field a = 0.164, so CV = 4.1% (lin e : ) . The values of a_ are calcu­ lated from mean values of the feed rate over periods of 20 s. For a Gaussian distribution this yields PW-x) =572?e*P(~(y)2 (a-l.D Multiplicationo fp b yth elos sfee drat erelatio nresult si na functio no f FS (inth efigur eline : ), sotha t

2 2 1 ix -u) , , , 1 , U -ü) i p(FS = x)'WL{FS = x) =a ^Tr exp(- 2o* )' & exp(ax) =^7 Fexp(a x -^—J - ~ " (a.1.2) This function can be transformed to

^^expfau + ha2q2 - -±r (x - (y_ + aa2))2 (a.1.3) whichshow stha tth eequatio ni ssymmetrica la tJ i+ ao2. Consequentlyth eaverag elos srefer st oa fee drat ewhic hi s aa higher thany_ .Thu sth eaverag elos si s

213 WL% 5 WL»pi.FS)

1 -

O -Ar 3 U FS Feedrate straw kg.s-1

0.5 1.0 plWL)

FigureA 1.2.2 .Effec to fa gaussia nsuppose dprobabilit ydensit yfunctio n ofstra wfee drat eo nth eloss-to-fee drat erelation .0 , standarddeviatio n offee drat e ( )= walke rlos s (WL) curvefo r Of 0 : WL= 0.02 2exp(0.944'F5 ); ( )= probabilit ydensit yfunctio no ffee drat e (p[FS)) ,fo r Oc= 0.48 8measure da tconstan tmachin espee dfo rperiod so f2 0s ; ( )= p(FS) for0 =0.16 4measure da tcontrolle dspee db ya fee d ratecontro lsystem ; ( -) productfunctio no f WL 'p(FS); ( )= theoretica lmea nlevel"o floss ,an dpertainin gcentr eo f productfunctio ni nth ecas eo f a. =0.48 8 (constantspeed) ; ( ) losscurv efo rO , 'I 488; ( )= probabilit ydensit yfunctio no flos s p(WL) forO f= 0 . 488

WL= k'exp(a' (\i + aa2)) (line (a.1.4) from which it appears that the "shift" of the loss curve compared to the original curve depends on a and o_. Note that the original curve refers to a hypothetical situation where o_ ~ 0. However, this example shows that if o_changes , for instance, because a manually controlled harvester is replaced by one with automatic control, there will be different loss levels for the same average feed rate. In this way the ratio can be calculated between the average feed rate levels for both these situations for a given loss level. When this is done for the previously mentioned loss-curve values k and a, 0, and 0 , then the following values are found for y /y, :

1.038 for WL = 0.5% 1.046 for WL = 1% 1.054 for WL = 2% The values for WL= 1% vary between 1.01 and 1.06 for a large number of loss curves. In the figure it can be seen (-..-..-) that, when the feed rate has a Gaussian distribution the loss will have a skew distribution.

214 A2.2 .COS TFACTOR S

Thecos tfactor swil lb econsidere d forth eIJsselmeerpolde rDevelopmen t Authoritylarge-scal egrai nfar m (U.D.A.),th econtracto ran dth egrai n farm.The yutilis eth ecombin eharveste ri nwhea tfo rrespectivel y175 , approximatel: y 100an d10 0h ape ryear .

A2.2.1 . Variable costs per hectare (MVC)

IJ.D.A. Accordingt oth einformatio no fFokken s (1983)th ecost sfo r198 2wer e formaintenanc e+ wea r 33.—fl'ha _ andfo rfue l 25.—fl'h a' Total 58.--fl'ha -1 Contractor: Accordingt oLang e (1972)combin eharvesters 'averag eoperationa l lifei s 5year swhe nthe yar euse db ycontractor san dthe nharves tapproximatel y 100h ape ryea rgivin ga tota lus eo f50 0hectares .Th esituatio ni s assumed tob eth esam ea tth epresen ttime .I nth etabl emad eou tb yLang e thetota lmaintenanc ecost sar efl.7500.— ,tha ti sfl.1500. —pe ryea r 40%o fwhic har elabou rcost san d60 %cost sfo rmaterials .Th epric eindexe s of198 1 (since1970 )fo rlabou ran dmaterial scost sar erespectivel y 3.2 and2. 0 (Anonymus,1981) ,thu sth epric einde xo fmaintenanc ecost sbecome s 2.5.A nextr a 10%fo r198 2give sa pric einde xo f2.75 .Thu sth emainte ­ nancecost spe ryea rar efl.4125. —which ,pe rhectare ,i sabou t41. —fl'ha _ Thecost sfo rfue lar e assumed tob eth esam ea sa tth eIJ.D.A. :25. —fl'h a Total 66.--fl'ha -1

Grain farm Asa rul e 1.5%o fth epurchas epric eo ff1.210.000.— ,whic hi sfl.31.5 0 per hectare,i sconsidere dt ob eth emaintenanc ecos tpe rhectare . Forth egrai nfar mth efue lcost sar e10 %les ssinc ether ei sles strans ­ portationove rlarg edistances ,s otha tw ehav e

fuelcost s 22.50fl'ha" 1 maintenancecost s Total 54.—fl'h a

A2.2.2 . Wages per hour (WA)

IJ.D.A. TheIJ.D.A .calculate sfo rthi sf'l.37.5 0pe rhou r (includingunworkabl e hours,trainin gan dtravellin gcosts )an da nallowanc eo f7.5 %fo rmanage ­ mentcost sgivin ga tota lo f40. —fl' hl .

Contractor Thewage sincludin gth ecost sfo runworkabl ehours ,travellin gan dmanage ­ mentar ei naccordanc ewit hth erate so fth eAssociatio no fContractor s 32.60fl' h 1.

Grain farm Theusua lwage so fabou t20. —fl' h 'ar e assumed. 215 A2.2.3 . Fixed aosts (AFC)

IJ.D.A. Thesecost shav ebee ncalculate dt ocove r25 0hour sincludin g roadtim ean dth etim euse dfo rth erape-see dharvest .Accountin gfo r winterwhea tpe rhectar e (namely1.2 1ha' h 1) thisgive s

depreciation 67.—fl'h a* interest 41.30fl'h a l together 108.30fl'h a includingmanagemen tallowanc e of7.5 %givin ga tota lo f 116.50fl-ha -1

Thetota lfixe dcost sfo r17 5hectar eo fwhea tar ethe nfl.20387.50 .

Grain farm In198 2th epurchas epric e (VATincluded )o fa ne wmachin ewa s]W=fl.21 0000. - and the residual value (RV) after 10 years of use is estimated as fl.30 000.— Then the fixed costs are depreciation (NV - RV) /10 = f1.1 8 000.— interest: 10% of (NV + RV) /2 = fl.12 000.— insurance costs 1^% of NV = fl. 3 150.— the total fixed costs f1.33 150;— for 100 hectare So the fixed costs per hectare are 331.50 fl'ha

Contractor He should bookth esam ecost sa sth ecerea lgrower ,an di naddition ,accor ­ dingt oth eBOVA L (Associationo fcontractors )standard s (Anonymus,1979 )th e sheltercost s (1.75%)an dth egenera lcost s (3%)w earriv ea ta tota lo f fl.9975.— . Thetota lcost sar ethu sfl.33150. —+ fl.9975. —= fl.43125. — • perhectare ,tha ti s431.2 5fl'h a 1.

Notei Whenth ecost sMV C+ HV C+ MF Car eadded ,the yamoun tf1.530. —pe r hectarea ta fiel dcapacit yo f1 ha' h 1...Compare dt oth etariff swhic hvarie d between 350.— fl'ha"1an d440. — fl'ha"1i n198 2i tbecome sapparen ttha t thecontracto ri sno treimburse dfo rhi sexpense sa t10 0ha'yea r^ .Sinc e theestimate sfo rfixe dcost sar elow ,th eamoun to f431.2 5fl'h a for thefixe dcost swil lb emaintaine di nou rstud yi nvie wo fth erathe rlon g operationallif eo f 10year stha twa sinclude di nth ecalculatio no ffixe d costs.

For theIJ.D.A .th evalu eo f AANi s assumed tob e 175ha ,whic hi sth e areao fwhea tpe rcombin eharveste rt ob eharveste di n1982 .I nth eyear s 1977.. .198 1th eaverag edrivin gspee dfo rmachin eB wa s0. 9m> s ,resul ­ tingi n VMN =0. 9m« s* .Fo rth econtractor , AANi s assumed tob e10 0ha , while VMNi s assumed tob e 1.0m.i sl ,becaus eth ecerea lfarme rwait sfo r morefavourabl econdition san dthe nth emachin espee dca nb ehigher .

A2.2.4 . Costs of the grain loss

Thesear ecalculate di nth emode lan daccoun tfo rth etradin gvalu eo f approximatelyf1.0.5 5kg" 1 (Schrier,1982 )minu sth etransportation ,clea ­ ningan ddryin gcosts .

216 1 Atth eIJ.D.A .th etransportatio ncost sar e100. —fl'h a f whichgive s 0.015 fl-kg 'a ta naverag eyiel do f688 5kg»h al in1982 .I n1982_th e processingan ddryin gcost swer efl.0.0 3kg -1,leavin g0.50 5fl-k g1 a s thecost so fgrai nloss . Forth ecerea lgrowe rth etransportatio ncost sar elower ;le tu s assurm theyar efl.0.0 1k g 1. Thedryin gcost sar eals olower ,becaus eth efarme r usesth emachin efo rfewe rhour san di si na positio nt owai tfo rmor e favourablemoistur econtent s (seeA 2.2.2.6) .Fo rinstance ,a tth eaverag e reductiono fgrai nmoistur econten tfro m21 %t o17% ,cost so fprocessin g included,yield sa tota lo f=0.016 5fl-kg -1.Thu sth evalu eo fth egrai n is0.53 4fl'k g .Th edecreas ei nvalu eo fdamage dgrai nis ,accordin gt o theEE Cinterventio nagreement ,0.0002 7fl'k g 1 per0.1 %exceedin g4% .I n thesimulatio nthi sleve lwil lonl yoccu ri nunfavourabl esituation si n closeconformit ywit hreality .

A2.2.5 . Costs of extra V-belt wear

Thelifetim eo fa V-bel tmainl ydepends ,accordin gt oIJ.D.A .dat a(Vos , 1982),o nth eexten tt owhic hth eoperato ri sabl et oavoi dth eformatio n ofwads .I fa noperato rdoesn' ttak eth enecessar ysteps ,a V-bel tca nb e wornou tafte r10 0hour so fuse .Normall yth eoperationa llif eo fa V-bel t is500-70 0hours ,th eaverag ebein g60 0hours .Th epric eo fa V-bel ti s ~'f1.350.— .Sinc eth eacceleratio nan ddeceleratio no fth ethreshin g cylinderarisin gou to fspee dcontro li scomparabl ewit hwad-formation , it seems to be reasonable to assume alifetim eo f5 0hour sfo ra V-bel t ata controlle d cylinder.Presumabl yth econstructio nwil lb eadapted ,s o thatlifetim ewil lincrease ,bu tthe nals oth ecost swil lb et oth eaccoun t ofth econtrol .Le tu s assume thatthe ywil lb ea sestimated ,tha ti s 350.—/50= 7. — fl«h-1 fora controlle dmachine .Thi si s0.0019 4fl' s* , whilepe runcontrolle dmachin ei ti s350.—/(600O600 )= 0.0001 6fl's -1. Bymean so fsimulations ,th eV-bel ttensio nha sbee nascertaine d tob e 1251N wit hmanua lcontro lan d 1866N wit hthreshing-spee dcontrol .W e willonl ytak eint oaccoun tth ecost so fwea rtha tar eabov ethos eo f manualcontrol ,s otha twhe n ¥3 isth ecos trat epe runi to fforce,_w e 2 cancalculat e V3 byth erelatio n (1866-1251)K 3= (0.194- 0.016)'1 0 . 6 1 Hence V3= 2.89*1 0 fl-s*« N . When FOBi sth ebel tforc eth ecost sar e {FOB- 1251)'7 3.I nthi scase , FOBvalue sles stha n125 1wil lgiv ea yiel ds ow eha dbette ronl ytak e the FOBvalue swhic har egreate rtha n1251 ,bu ti ntha tcas eth ecos t rate7 3wil lb eto olarge .O nstudyin gth edistributio no fvalue so f FOB, itwa sfoun dnecessar yt oreduc e V3t oabou t1.0*1 0 toge tth esam ecost s ofwear . Iti sno twort hwhil et ocalculat eth ecos trat emor eaccuratel ybecaus e therea lrelatio nbetwee nwea ran dbel tforce si sunknown .Th euse dcost s are0. 0fl- s l-N"1 if FOB« 1250an d {FOB- 1250W.0 10"6fl- s* 'N _1i f FOB> 1250 .

A2.2.6 . Costs of timeliness losses

Theheade ran dcuttin glosse s (front-end losses),occurrin gwhe na just - ripecro pi sharveste dar eno ttake nint oconsideration ,a ssuc hlosse s cannotb eharveste d atal lan dar e assumed tob eindependen to fth emachin e

217 speed. Based on an about 10year s ofresearch ,th e IJ.D.A.ha s established a model inwhic h the loss is calculated as a function ofweathe r factors likewind ,rain ,etc .B y simulating this model with the weather conditions of the past 40years ,th e function (1)o f figure A 2.2.6.1ca n be found (Fokkens, 1981). The standard deviation for thiscurv e has been indicated by the dotted lines.Thi smeans ,fo r instance,tha t if the harvest is brought in 24day s after ripeness,2 %o f the original yield cann o longer be collected.

FigureA 2.2.6.1. Functions of timeliness loss related to the number of days after combine ripeness (1)curv e calculated and usedb y the IJsselmeerpolders Development Authority (2)curv e used in this study based on (1)includin g the sprouting risk (3) front-end loss curve of Philips (1974) (4) front-end loss curve ofAudsl y (1974)

The sprouting losses are not included in this curve since they are sepa­ rately calculated as depending onothe r weather factors. In the event that sprouting occurs,th e loss, according to the above-mentioned curve,wil l bedouble d in the IJ.D.A.mode l because of ahighe r front-end loss and will be increased by 9% of thepercentage s soobtained .Th echanc e of sprouting increases rapidly from September 1st. Assuming thischanc e to be 50%o n September 15th and also that thecro p isworthles s on October 1st, thencurv e (2) in figureA 2.2.6.1doe s not seem unreasonable. The equation of this curve is 1.3*10 3(d - 8)3% for d >8 and 0 for d < 8 (d= the day of theharvest ). For comparison,th e following curves aredraw n inth e figure:th e total front-end loss curve of Philips (1974)(curve 3)an d the curve of Audsley (1974)(curve 4).Bot h curves are taken fromMcGecha n (1982).

218 Therea lcours eo fth eharves ti sdetermine db yth emachin espee dan dth e workablehour si nth epreviou speriod .Th edistributio no fth eworkabl e hoursvarie sstrongl yfro myea rt oyear ,s oa choic eha st ob emad efo r thedesire dcertainties .Thi swil lb eindicate db yth epercentage so fyear s inwhic hth ei ntabl eA 2.2.6. 1indicate dnumbe ro fhour stha tar euse d inth ecalculation,ar eno tavailabl ean dher ea choic eha sbee nmad efo r 25%an d 162/3% .Accordin gt oPortie k (1975),87 %o fth eworkabl ehour s ofa 24-hou rda yar ebetwee n06.4 0o'cloc kM.E.T .an d23.4 0o'cloc kM.E.T. . Thefigur eo f85 %o fth eavailable ,workabl ehour si n2 4hour shav ebee n takenfo rth egrai nfarm .N oreductio nha sbee napplie dfo rth eSunda y as,i nunfavourabl eyears ,thi sals owil lb ea workday . Forth eIJ.D.A .far mth eharves tseaso ni slong ,s oth ehire dworker s justwor kunti labou t21.0 0o'clock .Th eworkabl ehour si nth eperiod'fro m 09.40- 23.4 0o'cloc kM.E.T .includ eabou t7 %o fth etota lworkabl ehours , accordingt oPortiek ,s other eremai n80 %workabl ehour spe rday . Besides,a choic eals oha st ob emad efo rth emoistur econten to fth e grainabov ewhic hther ewil lb en oharvesting .Fo rth efarme ran dth e contractorthi svalu ei sassume dt ob e23 %an dfo rth eIJ.D.A .27% .A st o thestatistic so nth emoistur estandard s21 ,1 9an d 17%(se etabl eA 2.2.6.1 ) itca nb e assumed therear e about asman yworkabl ehour swhe nth eharves t takesplac ewhe nth emoistur econten ti sbetwee n2 1an d23 %a swhe ni t takesplac ea tbelo w21% .Fro mthi si ti s assumed thatth eaverag emoistur e contentdurin gth eharves tfo rth egrai nfar mwil lb eabou t21% .

TableA 2.2.6.1 .Th enumbe ro fth eworkabl ehours ,withou tstraw-moisture - contentlimit sdurin ga 24-hou rday ,base do ncalculate dgrai nmoistur e contentscoverin gth eperio d 1957.. .196 8

Thenumbe ro fyear si nwhic h lesstha nth eindicate dnumbe r ofhour sar eavailable : 25% 162/3 % Moistureconten tstandar d (%) <17<1 9<2 1<2 3<2 5<2 7 <17<1 9 <21 <23 <25<2 7 Period: August2 0 26 55 81 97 110 0 16 25 43 60 78 September1 0 0 24 36 58 73 0 0 5 12 32 64 September2 0 0 15 49 52 61_ 0 0 10 IL 32 36 Total24-hou rda y 166 244 76 178 Totalwor khour s: farmer 85%: 141 85%: 65 IJ.D.A. 80%29 5 80%14 2

Thewinte rwhea tharves tcoul dhav estarte da tth eIJ.D.A .grai nfar mi nth e years 1979 ...198 2i nAugus to nresp .17th ,23rd ,16th ,10t han d4th ,ac ­ cordingt oth estandar do fripenes sapplied .Thi sstandar di sdefine da s thedat eo nwhic hth egrai nmoistur econten tha sreache d20 %o ra lowe r level.A smea ndat a we chose the 15th,th estartin gdat eo fperio dAugus t2 fromtabl eA 2.2.6.1 .

Thecalculatio no fth etimelines slos si sthe na sfollows .Th e80 %o r85 % ofth eavailable ,workabl ehour sar eproportionall ydivide dove rth e1 5 dayso feac hperiod .Eac hday' sharveste d areai scalculate dfo ra rang eo f

219 machinespeed sfro m0. 0 ...1. 7m- s 1 andth eworkabl ehour so ftha tday . Thenth etimelines slosse so feac hda yar ecalculate dan dsumme du punti l thetota lare ai sharvested .Th epercentage sar erecorde d intabl eA 2.2.6. 2 whileth ecosts ,converte d intofl-h a' ar eshow ni nfigur e 1.4.1.3.Thes e costsar ebase do na yiel do f6 tons»h a andth egrai nvalue sgive ni n A2.2.4 .

TableA 2.2.6.2 .Timelines slos si n% o fth etota lcro p

VW (=VM'CL) 2 3 4 5 6 8 10 Farm Weatherris k Cerealfar m 25% 22.09 3.85 0.739 0.149 0.053 0.010 0.002 IJ.D.A. 25% 40.13 16.98 4.99 2.07 1.02 0.315 0.128 Cerealfar m 162/3 % 63.90 49.05 35.85 24.07 13.48 4.39 1.56 IJ.D.A. 162/3 % 55.58 38.45 23.66 10.83 5.00 1.96 1.04

A2.3.1 . Header and conveyer

Auger transfer Thetransfe ro fth emas stranspor tt oth edrivin gtorqu eo fth eauge rha s beenestimate db ystudyin gth erespons eo na ste pfunction .Thi sca nb e explaineda sfollows :Figur eA 2.3.1. 1show sa view ,fro mabove ,o fa headerwit hth edimension so fmachin eB an dbetwee nbracket sth edimension s ofmachin eA .

b i i i a /VAnv/XAZ i i l ~ 2.31(1.71) 1.275(1.075) 2.31(1.71) >t< ;—i i >!< B C D E F 5.9(4.5)

FigureA 2.3.1.1 .Dimension so fth eheade ro fmachin eB an d (between brackets)machin eA

Itca nb e assumed therei s0. 3 sbetwee nth emowin go fth ecro pan d thetransfe rt oth eauge rfo rmachin eA ,base do na machin espee do f1 m -s andth edimensions .Th epar to fmas sB Fo fth etota lmas si s1.07/(4. 5- 1.07) =0.31 andi sdirectl ytake nove rb yth eretractabl eauge r fingers.Th emas s ofA Ban dG Fi stransporte dt oB an dF a ta spee do f1.6 4m #s '.Thi sspee d iscalculate dfro mth eslop ean ddimension so fth eauge rwinding san dth e rotationalspeed .Afte r (4.5- 1.07)/1.6 4= 1.0 5second sal lth ecro pha s arriveda tB an dF .Th emateria lsuppl ycorrespond st oth edraw nline si n figureA 2.3.1.2 .Th emas sha st ob edivide dove rBF ,s otha tth eaverag e BCha st ob ecovered ,becaus eth eauge rwinding sals og ofurther .Thi s linewil lb emor efluent ,becaus eo finitia lprocesse san dskidding .

220 Initially thisproces s would be considered tob e asecond-orde r system in accordance with

1 (see the interrupted line), later a first-order process in (1 + 0.27'S)Z accordance with 1 +0.54' S has been used (see the line with long inter- ruptions). A similar reasoningha sbee n applied to theheade r of machine B,whic h has awidt h of 5.9 m.Fiel d measurements indicated a value of 2.0 - 2.4 s forth e real transportation time from the far to the take-overb y the auger fingers.Figur e A 2.3.1.3 shows the result.However , in this case,too , itseeme dmor e correct to approach itb y a first-order transfer, namely 1 1 1 + TS 1 +0.7. s Consequently the transfer depends on the working width {CD . This relation can be estimated by x = 0.12'CL.

-,x 1 Hi X y sZ^z~ ~~~~ x 0.8- ^ •^ 0.6- <7 0.4- 4f 0.2- lI*/ / / 0 i i i i i 1 1 -I— -1 • 1 1 1 1 1 1 1 1 r 02 0.4 0.6 0.8 1.0 1.2 U 1.6 1.8 0.20. 40. 60 8 1.01. 21. 41. 61. 82. 02. 22. 4 time s times

Figure A 2.3.1.2.Theoretica l respon­ Figure A 2.3.1.3. Same as figure A 2.3.1.2. seo f straw feed rate at the centre formachin e B of the auger on a step in strawden ­ ( )calculate d crop supply, sityparalle l to the cutterba r of ( )smoothe d calculated crop supply machine A and ( )calculate d crop supply, ( -) approximated supply according to ( )approximate d supply according first-order transfer 1/1+0.7»s. to first-order transfer and ( ) second-order supply.

Delays (see figure A 2.3.1.4) The quantity ofmateria l presented to theelevato r isth e same as delivered by the auger fingers.Henc e the transfer is linear.Nevertheles s there is adela y of 0.22 s,whic h canb e derived from the speedo f the cropan d thedimension s of themachine .Thi s delaywa smeasured ,too ,b y studying the peaks inplotte d signals of the auger torque and the elevatordisplace ­ ment ofmachin e A. The averagedela y of 174peak s was found tob e 0.65 s (Wevers, 1972). This value is ratherhig h compared to the theoretical value of0.2 2 san d canb e explained by the fact thatmainl yhig hpeak shav e been chosen.Th e peaks are those ofcro p accumulations occurringbefor e the arrival of thecro pa t the auger pins.

221 mean 1.0ms- 1 ^w ^\ \ '(1.0) \ VW ' N, i calculated delay tt41 10.33) 10.22 (0.22). 0.65(0.69 ) useddela y 0.410.3 ) '0- 3 (0.2)1 0-6 (0-7) I i

Figure A 2.3.1.4. Delays inheade r and conveyer,base d on dimensions (m) and speeds m-s l formachin e B and (between brackets) machine A

By determining cross-correlations betweenbot h signals,a n average delay of 0.43 sha sbee n found over 12test s (Theunissen, 1979). Eimer (1973) findsdelay s of0.2 5 -0.3 5 san d 0.6 - 0.7 s,dependin g on themachine . The inertia of themass-sprin g system of the elevator axle is also inclu­ ded in thisvalu e (forthi s see 3.1.2). Based on these observations and the imperfections expected at transfer, thevalu e used for thedela y is assumed tob e 0.3 s. Inth e simulation model thedisplacemen t of theelevatorchai n (DE) is taken into consideration separately,becaus e the auger torque (TA) as well as (DE) are used as ameasure d parameter for the straw feed rate (see 3.1).Th e delays to the threshing cylinder are calculated as 0.7 s formachin e A and 0.6 s formachin e B,whe n theelevato r speed and the length of the intake channel are taken into consideration.

A2.3.2. a Concave separation model From the formula for theconcav e separation or threshing separation efficiency TSE ofCasper s (1973) itca n be derived that BETA TSE 1- exp( - LA-NVRPS-(VT-VE)

This experimental model hasbee n arrived at fromresearc h with a rasp bar threshing cylinder ofdiamete r of 0.60 m,widt h of 0.98 m and concave length 0.68 m. The testshav e been performed with rye,sprin g wheat and sometimes winter wheat.Fo r our model thedat a ofwinte r wheat and springwhea t havebee n used.

222 Thethreshin gseparatio nefficienc y TSEi sdescribe db ythi smode l dependento nth ethreshin gspee d VTminu sth eintak espee d VE, thecro p property BETA, theconcav elength ,th econcav eadjustmen tan dth estra w feedrate .Thes efactor saffec tth evalue so f LA, NUan d RPS.

LAi sth econcav elengt hfacto rdetermine db yth elengt ho fth econcave , thefee drate ,th econcav eadjustmen tan dth ecrop .I ti sa rati orelatin g theseparatio no fa certai npar to fth econcav et oth etota lseparatio n inth ethreshin gcylinde ra suse db yCaspers .Th einfluenc eo fth efee d ratei ssmal lan dnegligibl efo rou rpurpose . Avalu eo f0. 9ca nb e assumed for LAbase do ndat ao fsprin gwhea tan d aconcav elengt ho f61 0m mfo rmachin eB (seefigur eA 2.3.2.1 ). Thi s valueapproximatel yaccount sfo rothe rcrop sto oan ddoesn' tdepen do n theadjustmen ta tthi slevel .

FigureA 2.3.2.1 .Concav elengt hfacto r (LA) relatedt oth elengt ho f theconcav e (L)for ,differen tconcav eadjustment s (COWA) indicatingth e gapa tth efron ti nmm/ga pa tth een di nm mo fth econcav ea sgive nb y Caspers (1973)fo rsprin gwhea t (MCS= 13% )

RPSi sth ereciproca lo fth eso-calle dcharg ecoefficient .Thi svalu eo f RPSdepend so nth estra wfee drate ,an di nfac tdecrease swit hincreasin g materialsupply .Se efigur eA 2.3.2. 2wit hdat ao fsprin gwheat . Onou rmachine sth eintak espee di sfixe d (machineA :2. 3m #s ',machin e B:2. 6m' s 1), resultingi n a more sirrple relation toth estra wfee drate . Thetabl ebelo wgive sth evalue sfe dt oa functio ngenerato rdurin gth e simulations.I nthi stabl eth especifi cfee drat ei sintroduced .Thi si s thestra wfee drat e FS, perm widt ho fth ethreshin gcylinde r LT, so FS/LT.

TableA 2.3.2.1 .Th euse dvalue so f RPSdependen to fth especifi cfee d rate AFSfo rbot hstudie dcombin eharvester s

Specificfee drat ei nkg« s -l 1 2 3 4 5 RPSmachin eA : («103 ) 10.2 8.5 7.0 5.7 4.8 RPSmachin eB :('10 _3) 10.5 8.8 7.3 6.0 5.0

223 RPS

2 AFSTkg.s- 1.m-

FigureA 2.3.2.2 .Reciproca lcharg ecoefficien t (RPS) relatedt oth ecro p supplyspee d (VE) fordifferen tspecifi cstra wfee drat elevel s [AFST) asgive nb yCasper s (1973)fo rsprin gwhea t (MCS= 13% ) ( )lin ecorrespondin gt oth eelevato rspee do fmachin eB

NUi sth erati obetwee n RPSa tth estandar dconcav eadjustmen t (20m ma t thefron tan d 10m ma tth eback )an d RPSa tth erea lconcav eadjustment . Thereforeth evalu eo f NUi sdetermine db yth econcav eadjustmen tan dth e strawfee drat eaccordin gt ofigur eA 2.3.2.3 .Fro mthes edat ath erela ­ tionbetwee n W andth efee drat eca nb ederived :se efigur eA 2.3.2.4 . Duringth esimulation sth evalue so fth e conoave adjustment 8/4 (8m m atth efron tan d i mma tth eback ) have been used throughout.

NU 1.5-1

1.3-

1.1- 0.5

1.0 0.9- 1.5 2.0' 0.7 2.5' 3.0' CMkg.m- 2 I 1 1 1 1 1 1 r 4 12 20 /2 8/4 A 16/8 /l0 2A/12 28/u CONA mm/m m Figure A 2.3.2.3 Compression factor (NU) related toth econcav e adjust- ment (CONA) fordifferen t crop mass levels onth econveye r (CM) ofth e test rigo f Caspers (1973) forsprin g wheat (MCS= 13% )

224 AFSTkg.s "

FigureA 2.3.2.4 .Compressio nfacto r (NU)relate dt ospecifi cstra wfee d rate (AFST) fordifferen tconcav eadjustments :x = 8/4 ,o = 12/6 , o =16/8 , 8 20/10mm/m ma sgive nb yCasper s (1973)fo rsprin gwhea t (MCS= 13% )

A2.3.2. b Laboratory research Theproces sa tth ethreshin gcylinde ran dth ewalker sha sbee nresearche d bymean so fa tes tri ga sshow ni nfigur eA 2.3.2.5 .Thi stes tri gcon ­ sistedo fa threshin gcylinde rwit ha diamete ro f0.4 5m ,a widt ho f 0.78m ,a concav elengt ho f0. 3m an d 10tray st ocollec tth eseparate d material. Thechose nvariable swer eth etyp eo fcrop ,th emoistur econten to f thestraw ,th estra wfee drat ean dth efee drat evariations .I nfigur e A2.3.2. 6th eresult sar egive no ftest swit hwinte rwhea t1 ,2 ,3 wit h moisturecontent so frespectivel y ~15% ,30 %an d45 %wit hstore dstraw , firstunmoistened ,the nslightl ymoistene dand ,last_o fall ,considerabl y moistened.Th efee drat ei si nk g (drymatter)» s l'm 1. Thepoint si nth e figurear eth eaverage so f5 tes teac hlastin g 12second s (Donkersgoed, 1980).Th ethreshin gcylinde rspee dwa s30. 6m' s* ; th econcav eadjustmen t was8/ 4m man dth eelevato rspee dwa s3. 5m' s

Apartfro mth eobservation sa tth elo wfee drate ,th emeasuremen tpoint s ofwhea t2 an d3 lin ku pwel lwit hth ecurv ewhic hca nb eobtaine dwit h theCasper smode li nwhic h BETA =1.55 .Se emodel s2 an d3 i nfigur e A2.3.2. 6 (LAi s0.5 3 atthi sconcav elength) .

225 FigureA 2.3.2.5.Tes t stand forth e laboratory testsconsistin g of conveyer belt, stationary small combineharvester ,reshake r and rethresher. M =measuremen to f the displacement of the elevator chain,A and Bacous ­ tic grain kernel sensors underneath the threshing cylinder,C ,D , E acoustic sensors underneath the strawwalke r placed as indicated by the dimensions, 1 10tray s inwhic h grainwa s gathered: 1 — 3 threshing separation,4 ... 8walke r separation, 9walke r loss, 10threshin g loss

TSE 0.90H

0-85

080- \ O v O ,\

075

1 —I 1 1 1 0.5 10 1.5 2.0 AFSkg.s- 1.m-i

FigureA 2.3.2.6 . Threshing separation efficiency (TSE) related to specific straw feed rate for variously treated wheat (see text): wheat 1: MCS= 15% (O); wheat 2: MCS=30 % (•); wheat 3: MCS =43 % (n),a t conveyer speedo f 3.5 m*s_1 and wheat 4: MCS = 15% (x)a t conveyer speed of 1.2 m-s ' Threshing separation model BETA = 1.550( ), BETA = 1.625( )

The low feed ratesdeviate ,becaus e thedifference s in the supply speed of the conveyer (0.75m* s 1) and in the intake speed of the elevator (3.5m* s 1) generate an irregular feed rate.Thi s effect ishighe r at a low feed rate,becaus e then there is so little coherence of the material on theconveye r that the elevator takes over themateria l separately.

At tests (Sytsma, 1981)wit h equal conveyer and elevator speeds of 1.2 m's_1, resulting in amor e regular intake,highe r threshing separation efficiency values were found.Her e themateria luse dwa swhea twit h a

226 straw moisture content of 14.7% and the threshing speed was 30.6 m*s '. In figure A 2.3.2.6 the averages of 4 tests with wheat 4 are shown. In this case, too, the Caspers model for BETA = 1.625 (model 4) is fairly satisfactory although the threshing cylinder diameter of the test (= 0.45 m) differs from that of Caspers (= 0.60 m). The results of tests under the same conditions as before for wheat 1, 2 and 3 are processed in figure A 2.3.2.7. Every point represents the result of one test on one type of spring wheat or oats or winter wheat. With winter wheat there are 6 straw moisture-content variations studied; early (at the time of harvesting), medium (after 1 month of storage) and late (after 2 months of storage) and of each type there is a dry and wettened version. For the illustration, there are two lines of the model for BETA = 1.625 and BETA - 1.550 in this figure.

TSE 0.85

0.80

0.75

070- 0-65t 0.5 1.0 1,5 2.0 2.5 AFST kg.s-i.m-i

FigureA 2.3.2.7 .Threshin gseparatio nefficienc y (TSE) relatedt o specificstra wfee drat e (AFST) oflaborator ytest swit hdifferen tcrops : x= sprin gwheat ,o = winte rwheat ,+ = oat s Linesar erelation scalculate db yth emode lfo r BETA= 1.625 ( ) and BETA=1.5 5 ( )

A2.3.2. C Field tests Fieldmeasurement shav ebee nperforme dwit hmachin eA unde rdifferen thar ­ vestconditions .A walke rlos smeasuremen tmachin ewa sbuil tfo rthi si n accordancewit hfigur eA 2.3.2. 8an duse di nth eperio d 1974 ...197 6 (Gelder,1975) .Th estra wfee drat ewa sfoun db ymeasurin gth eauge rtor ­ quean db yrelatin gthi st oth ecalibrate drea lstra wfee drat eo f1 5m tests (see 3). Inadditio nt othi sth edisplacemen to fth eelevato rchain , drivingspeed ,grai nlos smonito rsigna lan di n197 6th econten to fth e graintan kwer emeasure d continuously.I n197 5th emateria lfallin gthroug h thewalker sove rth epar tB- Co frun so f12 0m wa scollecte d (seefigur e A2.3.2.8) .Th ewalke rlosse san dth etota lgrai nfee drat ewer eals o measured,s otha tth etota lgrai nseparatio no fth econcav efinge rgrat e andth efirs tpar to fth ewalke rcoul db edetermined .Th etota lseparatio n

227 en c Ol •H Ol u M • U i u 0 01 J. di in ai c •rl 4-> •a* . en c -ri Ifl ai 3 0a •H 1$ id O>l ai id u n id ri T3 0>) >g *H en Cn rH 0&1 Cn - 1 4J 0) r~• C a Ol in • G ai •H m *H oi CT1 Ol 4-1 C >t C 0 0 ri S C •rl 0 id - rH Ol 01 •P ai ai 01 1 H S •S rH M 4J M id* . 3 1 Jd A 3 -r) 0 ai ai rH Cn .. 4-> rl H (d U Di 4-> 4J 3 C> S ai — a •d * 4-(!>) c 01 0 >i O -H a ai 0) 01 id o ai ai •rH > oi s 01 B > ai § 5 c -| S rH n> u kO 0 ri M XI ia 3 >i o ai 4J 4J Ä 01 •*> a 10 04 . ai ai . J, a) ai ai •a o > a 00 CM c S ri» 4J ai ••H c ai T-H -.H ai 01 +j 0 rH h. .g • 4J id h o ai » ai CM •M M H M ~ ci 10 •H ai id o . Cn 00 0 o S x a id -H c " rH 0*1 01 rH ai 01 "H -ri O 1H 3 id 01 4J +> >1 0 O1 § S S » ri id Ü M SH rH id >1 O c 01 0 4-> 4J ai ri H Bit) • 0 C 4J 01 •rl 4-1 rH 01 ai o TH •H •0 H H 01 id c 4J rg •p J3 U •H ai o id o U 0) S« H •p •0 -ri >H n* » n) Cn tri C 4J 4-1 id oi § e 3 01 C id H Ol M Hl S-l 0 a m . ai o tu « ai 5 id •O m ai n •rl id rl a - MH 01 CM• 3 4-1 r-l r-l M Cn id oi id 01 c a. 0 4-1 Xi o m• IO 92 & 144 >1 rH O -r| Si S aid Cn Cl• rH ai 4-1 CN• S Cl C n rH A • 01 M •rt 01 id r~ 3 01 3 m• u S 4-»1 4J U •rH 0 rt 01 01 ai 0 C a ai O ai 0 id •H 9J 0 >i - id M r-\ ai C» . 0> .Q N ai ai 3 •H o •H > >l 01 Oi T) a 18 •a sn M c 10 01 •H J3 Ö id 0 0 ri 0 • • 4J rH h S *-* Ü in id Q) J5 O

228 canb e compared to the function of Caspers,becaus e there is a close linear relationbetwee n the concave separation and the sumo f the separationb y the finger grate and the firstwalke r part (A-B)(see A 2.3.4).

The datao f the testwit h oats(* ) and springwhea tar e shown in figure A 2.3.2.9. In the tests indicated by (o)th e firstpar t of the walkers (A-B)wa s covered with sheets.Fro m this iti s found thati tdoe sno t matterwhethe ro rno tthi spar t is covered,s o thatth e separation atth e firstpar to f thewalker s issmal l and aan be considered as apar t of the concave separation. The figure also shows the line of themode l of Caspers for BETA =1.58 and VT-VE =30. 0m-s" 1 and concave adjustment 8/4ran. I t is found that this line isn't steep enough.Wit h regard to this it should be realized that themoistur e content of the strawo f themode l ofCasper s is 13%whil e the straw moisture content ofth e oats in the tests varied from 53%t o62 %an d of the springwhea t in the tests from22 %t o37 % during the field tests.Consequently ,on e is dealingwit h quite another crop.A n adaption of NUan d RPS is the only solution owing toth e difference in cropproperties .

The observations on tests carried out in 1976wit h winter wheatwit h straw moisture,content s of 15%- 24%ar e plotted in figure A 2.3.2.10 (Snel, 1977).Th e testswer e performed with the same machine as given in figure 2.3.2.8.However , in this case themeasuremen t stretch of 120m could be splitu p into 4 separate parts of •»3 0m .Fo r this theweigh t of the grain tank contentwa s measured and the losses andwalke r separation collected in separate trays and sacks.Therefor e the measurement points refer to averages over stretches of 30m .

TSE TSE 1.00 1.00-

0.95 0.95

0.90 0.90

0.85 - 0-85

3 4 5 AFST kg.s-i.m- i AFST kg.s-

FigureA 2.3.2.9.Threshin g separation Figure A 2.3.2.10.Separation efficiency efficiency {TSE) of field tests (1975) of field tests (1976) inwinte r wheat in oats:-Jfwithwalke rplates, ®withou t ( '•)model_wit h BETA =1.66, walkerplate s in springwhea t xwit h VT-VE=30.0 m's l, concave adjustment and ®withou twalke r plates (see text) = 8/4 mm

229 Awell-fittin gmode lfo rthes emeasuremen tpoint sca nb eobtaine dfo r BETA =1.66 , VT-VE= 30. 0m» s' an da concav eadjustmen to f8/ 4mm .Thi s modelfit sth emode lo fCasper swell /thank st oa dr ycro punde rdr yhar ­ vesting conditions.Th egenera lconclusio ni stha tth emode lo fCasper s performswel lunde rfiel dcondition san dbette rstil li fth ecro pi s dryertha ni nth eCasper stests .

A2.3.2. d The threshing separation efficiency in relation to feed rate variations Theexten tt owhic hth eamplitud ean dfrequenc yo ffee drat evariation s affectth ethreshin gseparatio nefficienc y (Smook,1980 )ha sbee ninves ­ tigated.Thi swa sachieve di nlaborator ytest swit hth etes tri gshow n infigur eA 2.3.2.5 . Winterwhea t (moistureconten t16% )wa sdistribute di npile so nth e 12m lon ghorizonta lconveye rmovin ga ta spee do f1 m* s l. Thepile s were 1m i nlengt han dcontaine dequa lquantitie so fmateria lpe rm for eachfee drat elevel ,th edistance sbetwee nth epile sbein gequa l(se e fig.A 2.3.2.11) .Th egreates tdistanc ewa s4 m ,other sbein g2 ,1 an d 0m (thelas tmentione dmeanin gclos etogether ,bu tseparate) .Test swer e alsodon ewit hpile s0. 5m i nlengt hwit ha distanc eo f0 metr ebetwee n them.Ther ewer eals otest swit hcro ppu tdow nregularl ywit hth eear s forwardan dupwar d (see:eve nfee di nfig .A 2.3.2. \l)_. Thespee do fth e elevator (behindth ehorizonta lconveyer )wa s3. 5m- s Thepile sar eal ltake nu pa tonc eresultin gi na nactua lfee drat e underth eelevato ran dt oth ethreshin gcylinde ro f3. 5time sth eorigi ­ nalfee drat e (seeth edotte dlin ei nth eto po ffigur eA 2.3.2.11) .Thi s momentaneousfee drat ei scalle dth ecylinde rfee drate .I nthi sway , thefrequencie so fth efee drat evariation swer e0.2 ,0.3 ,0.5 ,1. 0an d 2.0Hz .

^ A £-02 va m< w\ m\ 0.33 s"1 va m. vm m\ m\ m\ z^mmmmmmmmmwû « mmmmmmmwm 2.0 s-

even feed > 10 11

FigureA 2.3.2.11 .Depositio no fstra wa tth econveye rbel t V// /i and anexampl eo fexpecte dresultan tcylinde rfee drat e ( )

230 Theregula rfee drat eo reve nfee do nth econveye rals obecome sirregula r wheni ti stake nove rb yth eelevato rchain .I twa sfoun dfro mth ere ­ gistrationo fth edisplacemen to fth elowe raxi so fth eelevato rchai n thatth ewad sa tth eintak ear edependin go nth efee drat elevel .I twa s triedt ocalculat eth ecylinde rfee drat efo rth eeve nfee do nth econ ­ veyer. Itwa spossible ,especiall ya thig hfee drates ,t oascertai nth eleve l ofth epeak so fth emeasure d feedrate , FSE, ateve nfee d (seefigur e A 2.3.2.12).Th eaverag evalu eo fth epeak sha sbee ncalculate d (= TE) andcompare dt oth epea kvalu eo fth eirregula rfee da tth esam efee drat e level (= TI) (seefigur eA 2.3.2.13) .Thi sgive sa valu e A= TE/TI. The amplitudeo fth eirregula rcylinde rfee drat ei ncas eo feve nfee da t theconveye rca ni nthi swa yb ecalculate dalso ,namel y

cylinderfee drat e= sPee& elevator .4. (ka«s'm~l) speedconveye r conveyer feed rate

FSF

FSE

V *U VJ «IL UL, - 12 15 time s FigureA 2.3.2.12 .Measure dfee drat e FigureA 2.3.2.13 .Measure dfee drat e atth eelevato rfo ra neve nfee do f atth eelevato ra ta nirregula rfee do f 4kg* s* 0.5kg* s *o fmea nfee drat e4 kg's" 1 (samescal ea sA 2.2.2.12 )

TableA 2.3.2. 2show sth evalue so f Aan dth ecalculate dcylinde rfee d ratefo rvariou sfee drat elevel sa teve nfeed .

TableA 2.3.2.2 .Th ecalculate dcylinde rfee drat efo rirregula rfee dan d evenfee d

Strawfee drat eo nth econveye rbel t kg#s l'm (widtho fcylinder ) 1.28 1.71 2.13 2.50 Cylinderfee drat efo rirregula r feed (kg« s _1) (A = 1) 4.48 6.00 7.46 8.75 0.19 0.31 0.42 0.50 Cylinder feed rate for even feed (kg's l -m ') 0.85 1.86 3.13 4.38

231 Nowi ti sfoun dan dshow ni nfig .A 2.3.2.1 4tha tther ei sn osignifican t differencebetwee nth evariou sfrequencie swhe nth ethreshin gseparatio n efficiency, TSE,an dth ethreshin gloss , TLF,(th eaverag eo f4 repetitions ) isregarde da sa functio no fth ecylinde r feed.rate.Thi smean sther ei s noimportan tredistributio ni nth ethreshin gcylinde rbecaus eth eactuall y presentedcylinde rfee drat edetermine sth ethreshin gseparatio nefficiency . Thethreshin gseparatio nefficienc yo fth e2. 0H zan dth eregula rfee d ratevariant si sproportionall yto ohigh .Thi si sbecaus ether ear elowe r feedrate sbetwee nth epea kfee drate swhic hcaus ea mor efavourabl e concaveseparation .Consequentl yther ewa sa redistributio ni nthes etest s ontakin gove rfro mth econveyer .Th esam econclusio nha st ob edraw nfro m othertest swit ha varyin gfee drat e (Sytsma,1981 ;Groothuis ,1979) , namelytha tth efrequenc ydoe sno taffec tthreshin gseparatio nefficiency .

TSE 0.9

0.8-

0.7

0.6

0.5 <

TLF 0015-

0010-

0-005

8 10 AFST kgs-

FigureA 2.3.2.14 .Threshin gseparatio nefficienc y TSEan dthreshin glos s (fraction) TLFrelate dt ospecifi cfee drat e AFSTan dirregula rfeed : 0.2s^fx) ;0.3 3s * (o ); .5s Ho); 1.0s (•J ); 2. 0s l(x )an deve nfee d (•)

A 2.3.4.a Relation between separation front of walkers and concave separation It has been ascertained from other tests with the test rig given in A 2.3.2.5 (Donkersgoed, 1980) that the relation between the content of tray 4 (= separation first walker part and concave grate) and the content of trays 1+2+3 (= concave separation) is well described for different

232 cropsb ya linea rrelation .A nexponentia lo rsquare drelatio ni sbette r forsom etype so fcrop ,bu tth edifferenc ei ssligh twhe nal lth ecrop s aretake ntogether .Tabl eA 2.3.4. 1give sa resum eo fth eresult so fregres ­ sionanalysi san dfig .A 2.3.4. 1show sth eobservation stogethe rwit hth e tworegressio nline sfo ral lth ecrop stake ntogether .

TableA 2.3.4.1 .Result so fregressio nanalysi so fth eseparatio no fth e fronten do fth ewalker s (tray4 )explaine db yth econcav eseparatio n withtw omodel s n =numbe ro f 12-sec.test s MCS =moistur econten to fth estra w (%w.b. ) WS4= separatio no ftra y4 (gram sdr ymatter ) CS =concav eseparatio n (gramsdr ymatter ) b =regressio ncoefficien t MCCS=multipl ecorrelatio ncoefficien t + crop n MCS WS4 = \V CS ln(HS4)= b2 + b3' CS MCCS h MCCS 2 b3 oats 25 17 95.0 0.043 0.98 3.78 3T3 IO-1* 0.94 win­ 25 15 -10.8 0.069 0.98 4.67 1.7 10* 0.97 ter 25 30 -122.0 0.094 0.92 4.30 2.3 ïo""" 0.99 wheat 25 43 -81.8 0.071 0.91 4.19 2.2 lO-" 0.97 allcrop s 100 — -66.9 0.076 0.91 4.25 2.2 10» 0.93

FigureA 2.3.4.1 .Relationshi pbetwee nconten to ftra y4 {WS)a tth efron t ofth ewalker san dconcav eseparatio n [CS) D =oats ,o = whea t1 , A =whea t2 ,x = whea t3

A 2.3.4.b Steady-state model of walker separation The grain content in the straw on the walkers G at x decreases as a func­ tion of the distance x from the point at the waïkers where the exponential model starts (at o)_. The unity of G is kg's l because the mass is moving x backwards and kg«s when the content is considered for width of the walkers in metres. At the start the grain content is G . The decrease at any place behind o is assumed to be proportional to G itself

233 so that

dG

inwhic h WE =th eproportiona l factor,calle d walker efficiency. From (a2.1 )i tfollow s that

dG —x- - - WE-dx (a 2.2) x When we want to know the value of G at any place w it can be calculated by integrating (a 2.2) so that

w dG w J ~fx =-J WE-dx (a 23)

Solving (a2.3 )give s w w In G I -- WE'X I (a2.4 ) Xo o

Thus In G,- I n G = - WE'W+ o (a2.5 ) W O or G JG = exp(-WE w) • (a2.6 ) w o or G = G exp{-WE'W) kg*s_1 (a2.7 ) u o In fig.A 2.3.4. 2th ecurv eo fth egrai n content G isdraw n including the initial process from Jt o0 .Th einitia l processca nb eclearl y seen inth ewalke r separation curve representedb ylin e WS.Thi s function holds dG,

Thus from (a2.1 )an d( a2.7 )w ehav e

WS- -G •WE'&xpl-WE'V) kg*s-1'm-1 (orkg«s~ l«m~2)

Now,th e assumption inth emodel , WEi sconstant ,ca nb eteste d fromth e measured WS'.Thi sca nb edon ei ntw oways : 1) WSmeasure d overa certai ndistanc e Aw,giv eth ecalculate d W?(s) yielding fortha tdistanc e andtha tplace .I ntha tcas e G hast ob e known at W. 2)A loca l WE(t) canals ob ecalculate db ytakin g G atplac eE an db y measuring WS fromE t o w. Both curveso f WEar esketche d infig . A 2.3.4.2.

Whenconsiderin gth eresult so fsom e laboratory testsi tbecome s clear thatth ebehaviou ro f WSabov e tray4 i sa ninitia l process.Therefor e thisha st ob econtemplate d asi ncoherenc e with theconcav e separation (seeAppendi x 2.3.4a). This also showsth eimportanc e ofth ebaffl e curtain,becaus e theseparatio n starts just behind thecurtain .

234 FigureA 2.3.4.2 .Sketc ho fth egrai nconten ti nth estra w (G ),walke r separation {WS), localwalke refficienc y (WE{1)an dwalke refficienc y holdingfo rth edistanc efro m b to w, asa functio no fth eplac eo nth e walkers (w)measure dfro tihem fron to fth ewalker s (b)

Boyce (1974)reache sth esam econclusio nthat ,withou tth ecurtain ,th e majorpar to fth eseparatio nstart sa tth erea ro fth ewalker sbecaus e thereth estra wreache sa spee d slowenoug hfo rseparation .A secon d curtaina tth erea ro fth ewalker sdoe sno thav ean yfunctio ni fther e isa firs tcurtain . Reed (1972)obtaine da lowe rwalke rseparatio nwit ha ligh tcurtain .

Behindth ebaffl ecurtai nth ewalke rseparatio ncoefficien t WE(s) has theoretically tob eindependen to fit splac eunde rth ewalkers . Resultso flaborator ytest swit hth etes tri g (explainedi nparagrap h A2.3.2.b )an dthree-kind so fwinte rwhea t1 ... 3 (Donkersgoed,1980) , showho wthi sconclusio ndepend so nth efee drat eleve lan dth ecro p properties. Fig.A 2.3.4. 3give sa numbe ro fresult sa ta fee drat eleve lo f about2. 3kg' s *m 1. Theleve lo f WEdecrease sslightly ,probabl y becauseo fstra wcompaction .A tlowe rfee drat elevel sth eseparatio n abovetra y6 an d7 i shighe r (seefig .A 2.3.4.4) .Th ereaso nca nb etha t therei sstil lirregula rfee da tlowe rfee drate sa tth efron to fth e walkerswherea si tha sbee nflattene d towardsth een do fth ewalker s(se e A2.3.2.4-c) . Thecro ppropertie saffec tth elevel ,a scoul db eexpected .Th e influenceo fth efee drat eleve lo nwalke rseparatio ni sshow ni nfig . A2.3.4. 5fo rwhea t1 .Fo rwhea t2 an d3 th esam epatter ni sfoun da ta higherlevel .Th eseparatio ni scalculate d forth epositio no fth edif ­ ferenttrays .Tw oconclusion sca nb edrawn :th evarianc ei shig ha tth e lowerfee drat elevels ,probabl ybecaus eo fth eirregula rfeed .Th ede ­ creasei n WE(s) withincreasin gfee drat ei sslight ,especiall ywhe ncom ­ paredwit hth eresult so fth efiel dtest s (paragraph2.3.4) .

235 Wflslm-1 3- 3-

2 2- î, « H + 1- k

0.4 0.8 1.2 1-6 0.4 0.8 1.2 1.6 im Lm

FigureA 2.3.4.3 .Walke refficienc y WE{s) FigureA 2.3.4.4 .Sam ea sfigur e relatedt oth edistanc efro mth een do f A2.2.4. 3fo rstra wfee drat elevel s tray4 (L) fordifferen tkind so fwinte r ofabou t0. 6kg« s x»m^ wheatat_ astra wfee drat eleve lo f2. 3 x= whea t1 (0.6 3kg's_ 1«m 1), += kgs '» m* wheat2 (0.57kg« s x-m x), •= whea t x= whea t1_(2. 8kg« s l-m 1), += whea t 3 (0.52kg* s^ m l) 2 (2^1kg« s1 «m 1), •= whea t3 (1.9 9 kg*s l-m 1). Thepoint sx ar eplotte d inth ecentr eo fth etra ywhil e+ an d oar eshifte dt oth erigh tfo rclea r recognition

Thetes tri gcondition sapparentl ydiffe ra goo ddea lfro mthos eo f machineA i nth efield .A probabl ereaso nca nb efoun di nth eshor ttes t lengtho ftim e (10sec) ,becaus ei twa sregistere dtha tth eperio di n whichth ecro plef tth ewalker swa slonge rtha nth eperio di nwhic hi t wasfe dint oth emachine ,s otha tfee drat ewa si nfac treduced .Furthe r researcho nthi smatte ri snecessar yt omak ethes edifference sclear .

Theresearc hdon eb yRee d (1970,1972 )support sth eexponentia lmode lan d thedependenc eo fou rfiel dtest so nfee drate .Fo rthi sreaso nth eus e ofth eexponentia lmode li nou rmode li s thought tob e justified.

A2.3.4. C Dynamic model of walker separation

Pulse type feed rate variations Thewalke rseparatio nha sals obee nconsidere di nth ewor kdescribe di n A2.3.2.d ,i nwhic hth estra wfee drat evarie dconsiderabl ya tdifferen t frequencies.Th econtent so ftray s1 to -10 ,wer eweighe dan dth esignal s ofth edisplacemen to fth eelevato rchai n (M), thepulse-typ esignal so f theacousti csensor sa tpoin tA ,B ,C ,D an dE wer erecorded .Thes esen ­ sorswer eplace dabov eth ecorrespondin gtray s1 ,3 ,5 ,7 an d8 .I na subsequenttes twit hsinusoida lvariation s (Sytsma,1981) ,th eposition s ofC ,D an dE wer eshifte dt oth eplace sindicate db yth emeasure si n figureA 2.3.2.5 .Th esignal so fsensor sA an dB (10x20m meach )wer e addedbefor erecording .Sensor sC ,D an dE wer eeac h50x15 0m man dth e signalswer eseparatel yrecorded .Afte rth etest si twa sfound ,however , thatth esigna lo fE wa so fn oeffect .Cross-correlation swer emad eo f allth eremainin gcombination san dth ehighes tvalue swer eaverage dove r 4repetition san dth e3 o r4 fee drat elevel spe rfrequenc y (seefigur e A2.3.4.6) .

236 WE(s )m- ' WE(s )m- '

TRAY 5 TRAY 7

I +** *i* ** •*

0.8 1.6 2.4 o 1 1 0.8 16 2.4 AFSW kg.s- .m- 4FS1Vkg.s- 1-m-i

WFIslm-1 WF(s)m- 1

TRAY6 TRAY8 + 3- +

2- *«• * * +•%

0-8 1.6 2.4 0 0.8 1.6 2.4 .4FSWkg .s- 1-m- 1 AFSW kg.s- 1.m-1

Figure A 2.3.4.5.Walke r efficiency WE{s) above various trays in the test rig related to specific straw feed rate

From thisth e following observations canb e derived,bearin g inmin d that the feed rate varies pulse-wise with frequencies indicated by F^. The correlation(r)betwee nM and AB (*) is rather high and somewhat lower for F = 2s" 1, so thatth e feed ratevariation s below 2 s_l are evident­ ly transitory,whil e some suppression of variations of 2s seems to occur.Th e correlationbetwee nM and C (o),a swel l asA B andC (x)ar e about the same,thoug h lower thanbetwee nM and AB (*),becaus e ofdistur ­ bances in the threshing cylinder.Excep t for thevariatio n of 0.2 s the correlation isno t obviously dependent on thevariatio n frequency. This leads to the conclusion that,i n fronto f thewalkers ,variatio n isonl y suppressed slightly. As regards the correlationbetwee nM andD (A),A B andD (o), and especially betweenC andD (•), adeclin e canb e seen at the lower frequencies.

237 r 0.8

0.6

0.Ü

0.2

0.4 0.8 1.2 1.6 2.0

Figure 2.3.4.6. Correlation (r)o f feed rate sensor (M)an d acoustic grain kernel sensors AB,C andD tovariatio n frequency. Correlation between AB-C (x), AB- D(a) ,c- D (•), M-A B (#), M- C (o) andM- D (A)

Interm so fa decreas ei nth eamplitud eo fsine-typ evariation spassin g througha first-orde rprocess ,ther ei sa noticeabl edecreas ea t0.3 3H z andhighe rfrequencie swhic hi sobviou sabov eD .Althoug hw eare ,o f course,no tdealin gwit hsine-typ evariation sa tth einpu tt oth ethreshin g cylinder,th evariation sa tth ewalker shav ebecom emor eo rles slik esin e functions.Thi si seve nmor eth ecas efo rlonge rwalker swher eth elowe r frequenciesar esuppresse dsomewha tmore . Assuming thatth ebreakpoin t frequencyo fth evariatio nsuppressio ni sa t0. 2 Hz,the nth etim econ ­ stanti sT = l/(0.2*2ir)= 0. 8s .Althoug hthi sdeductio ni sno tquit e watertight,i tis ,however ,a nindicatio ni na directio naffirme dlate r on.Additiona lresearc hi snecessar yo nthi spoint .

Nevertheless,th etw ofollowin gconclusion s aan be justified 1)Th ecorrelatio n ishighe r atlo wfrequencie s because thepile s remain more easily identifiable. Inthos e cases theredistributio n is slight. 2) Redistribution does occur, especially behind thebaffl e curtain,be ­ cause thesignal s of sensor C, which is positioned under the curtain, show less suppression of variation than those of sensor D.

It is important to realise that, when there isn oredistribution , the wal­ kers, too,ar edealin g with thecylinde r feed rate asdefine d inA 2.3.2.d and then thewalke r efficiency WEwil l deviate from the WEa ta regular feed rate. WEca nb e calculated from thetra y contents. If there is in fact a redistribution, thevalue s of WE asa function of thepositio n underneath thewalkers , will turn outt ob e like even feed, that iswil l be shown tob e slowly decreasing. Figure A 2.3.4.7 shows WE(V) ofa regular feed rate at6 levels ando fa varying feed rate atth e highest feed rate level of2. 5kg' s l-m l. G hasbee n taken from tray 5 o and higher.

238 W£-(l)m-1 1.8-

1.6

1.2

0.8-

0.4

tray5 tray6 tray7 tray8

—i— 0.5 1.0 1.5 LWm

Figure A 2.3.4.7. Walker efficiency (WE(Z) related topositio n onwalker s (LW) oftra y 5fo reve n feed (_- )a tdifferen t levelso fmea n straw feed rate asindicate d inkg' s 1«m J (seeals otabl eA 2.2.2.2 )an dfo r irregularfee da tmea nfee drat eleve lo f2. 5kg' s thisbein ga cylinderfee drat eleve lo f8.7 5k gs -m ( )a tdifferen tvariatio n frequencies:A=2s 1,0=ls1,D =0. 5s * =0.3 3 0.2s

Thefollowin gca nb esee ni nfi g A 2.3.4.7: A)Th evariation so f2 s 1 an d1 s behave like "even feed" ata somewhat lower level. Ittherefor e canb econclude d that there isa redistribu­ tion atthes e frequencies because thelin e isstraigh t just asi ti s with "even feed". Theredistributio n already occurs under thecurtain . However,th eredistributio n isincomplete , since WE(i) remains lower than at"eve n feed". This ispossibl y aconsequenc e ofanothe r type of redistribution under thecurtain .

239 B)Th e variations of 0.5,0. 3 and 0.2-s"1 show a lower WE(l) at the front and ahighe r WE(SI) at the rear of the walkers.I ttherefor e canb e concluded that WE(i.) is low atth e frontpar to f the walkers because of the cylinder feed rate,s otha t there the redistribution isslight . At therea r of the walkers the redistribution transferring the cylinder feed rate into the feed rate iscomparabl e to "even feed".Th e calcu­ lated value of WE(I) at the endo f the walkers isshow n to reach the value of "even feed".

The conclusion tob edraw n can be that there is also redistribution at the end of the walkers forvariation s of 0.2 s 'an dhighe r so that the break­ point frequency of the assumed first-order transfer isa t0. 2 s *o r lower, with the result thatT = 0.8 or larger for the researched type ofvariations .

In figure A 2.3.4.7i t also appears that the low feed rates initially have a lower WE(V) value and also that theydon' t show the expected increase toth e finalvalu e of WE. Therefore the conclusion is that the irregular parto f a low feed rate cannotb e corrected by redistribution.

Sinusoidal feed rate variations Conclusions havebee n drawn from thepreviou s research,expresse d in terms of frequencies ofpuls e like functions.A laboratory test (Sytsma, 1981) wasperforme d to check these conclusionswit h sinusoidal feed rate varia­ tions. In these tests,3 feed rate levelswer e used,averagin g 0.71, 1.33 and 2.07 kg-s 1«m ',wit h varying feed rates atamplitude s of 20%an d frequencies of 0.2,0.4 ,0. 8 and 1.6 Hz.I n addition there was ates twit h even feed and onewit h anaverag e feed rate of 2.07 kg's 'm and an amplitude of 40%.Eac h testwa s performed withwinte rwhea t MCS= 15% with 4 repetitions.Th e speed of thehorizonta l conveyer and the elevator chainwer ebot h 1.2 nrs 1 inorde r topreven tredistributio n at the elevator chain (seeA 2.3.2.d).

The results showed noeviden teffec t of the frequency on the concave sepa­ ration and the totalwalke r separation at 20%amplitude .However ,th e concave separation was lower at an amplitude of40 %tha n at 20%.Also , thewalke refficienc ywa s lower at an amplitude of 40%an d a frequency of 0.2 Hz.Th e feed rate at "even feed" could be characterized asirre ­ gular,too .Th e frequencies introduced couldb e visually recognised from the signals of the acoustic sensors A ...E positioned as indicated in figure A 2.3.2.5.Fro m the power-density spectra,mad e only for the40 % amplitude/0.4 Hzvariant ,i twa s apparent that the 0.4 Hz component could be clearly recognised asa peak atM , B and D. Acoustic sensor A didn't work,senso r C showed apea k at0. 2 Hz and at sensor E therewa s a peak at0. 2 Hzbu t at aver y lowlevel .

The conclusions tob edraw n from this are that 1)Ther e isn o redistribution at the threshing cylinder. 2) On thewalker s there is a redistribution at frequencies above 0.2 Hz according to thewalke r efficiency and in accordance with the power- density spectra.Th ehighe r frequencies are indistinguishable from "even feed",allowin g the conclusion T= 0.8 tob e maintained. Itca n be expected thata redistribution is intensifiedb y longerwalkers . This research has tob e continued.

240 Field research Thecours eo fth ewalke rlosse sa sa functio no ftim eha sbee nrecorde d fora larg enumbe ro ffiel dtest swit ha grai nlos smonito ra tth een d ofth ewalker so fmachin eB .Specia lattentio nha sbee npai dt ob erespons e ofwalke rlos st oa ste pfunctio no nstra wfee drat egenerate db ya combineharveste rdrivin gint oth ecro pa ta give ndesire dspeed .

FigureA 2.3.4. 8show sth erespons eo fth ewalke rlos svalues , averagedpe r0.2 5s . Assuming afirst-orde rtransfe ro nth ewalker senable sa nestimatio n ofT t ob emad esinc e63 %o fth eleve lo fth este pfunctio na ta first - orderproces si sreache dafte rx seconds .Th e63 %leve li sindicate di n thefigur eb ya dotte dlin egivin gT value svaryin gfro m0. 2t o0. 9second s andaverage da s0. 6s .I na nempt ymachin eth estra wintroducin gth efirs t lossesa tlo wfee drate smove sfaste rbackward sunde rth ecurtai ntha na bigstra wmas si na continuou sprocess .Therefor ei ti sbette rt oderiv e theT fo ra continuou sproces sfro mrecording so fhig hlosse s (highstra w feedrates) .I ti sindee dremarkabl ei nth efigure stha tth ehighe rlosse s areaccompanie db yth ehighes ttim econstant s0.6 ,0. 8an d0.9 .I t would appear tob ejustifie dt oprefe rth evalu eT = 0.8 .

Walkerlos s gd.m./0. 2s 0.9

012 012 012 012 012 01

FigureA 2.3.4.8 .Walke rlos srespons et ostra wfee drat este pfunctio n

241 A2.3.4. a Time delay on walkers Thestra walmos to rcompletel ycome st oa standstil lunde rth ebaffl e curtaina tth efron to fth ewalkers .Henc eth etota ldela yo nth ewalker s cannotb eestimate d fromth espee do fth estraw .A naccurat eestimat ei s desired,sinc etota ldela yi nth eproces si sa ver yimportan tdeterminin g factorfo rcontrol .Durin gthre eyear so ffiel dresearc hth etim etha ta colouredwa do fstra wi stransporte d throughth ecombin eharveste rwa s tracedwit hmachin eA .

Itwa scalculate dtha tth edela yo fstra wfro mth emiddl eo fth ecutte r baro fth emachin et oth een do fth ewalker svarie sbetwee n7 an d1 3 seconds (Wevers,1972) .Th eaverag ewa s9.7 5s ove rthre eyears .Wit hth e samemeasuremen tmetho da naverag eo f7. 1s wa slate rfoun d formachin eB . Adisadvantag eo fthi smetho di stha tth ewa ddoe sno tbehav elik eloos e material.Averag evalue so f7. 3an d1 0s fo rmachine sA an dB ,respectively , havebee nfoun db ymean so fcross-correlation sbetwee nth esignal so fth e lossmonito ran dth eauge rtorque .Th elast-mentione dmeasuremen tresult s willb euse dt ocalculat eth edelay ,becaus ethe yar eth emos taccurat e ones (seeparagrap h 4).Incidentally ,i nth ecas eo fmachin eA 7 observa ­ tionswer einvolved ,varyin gbetwee n8 an d 11.8s .Thi svariatio nca nals o befoun di nth eothe robservation san di spresumabl ydu et omateria lstand ­ stillunde rth ecurtai nan dvariation si nspee do fth emateria lo nth e walkers,especiall ya tth eside so fth emachine .

Thedela yfro mth eauge rt oth ethreshin gcylinde ri s1. 0s fo rmachin e Aan dt oth erotar yseparato ro fmachin eB 1.1s .Th efirst-orde rproces s on thewalker sals ogive sa phas eshif trepresentin ga tim edela yo f about0. 7 sfo rth elo wfrequencies .Th edela yt ob eapplie da tth ewalker s willb etherefor e 10.0- (1. 1+ 0.7 )= 8. 2s . Althoughsystemati ccause sfo rth edeviation scoul dno tb eascertained , theimpressio nnevertheles sexist stha tcro pconditions ,fee drat elevel s andslope scertainl yhav ea nimpac to nthi sdelay .

A2.4.3 . Dimensions threshing cylinder vari-drive Theexistin gvari-driv esize sar eindicate di nfig .A 2.4.1 .Th emaximu m displacementD o fth edrivin gvariato rdisc sca nb ederive dfro m

dR = B „ - R . „ =0.213 5- 0.122 5= 0.09 1m max max,eff mm,eff §_ =26 °s o h&= 13 ° (a2.8 ) x = dR -tg^ (a2.9 ) max D = 2x =2'0.091-t g13 °= 0.04 2m (a2.10 ) Achang ei nth eworkin gradiu s dRfollow sfro mth edisplacemen t dD.

^-T^T-^2 <•'•"> sotha tth eworkin gradiu so fth edrivin gdis ci s

0.122 5+ - when goe sfro m0 t o0.4 2m . (a2.12 ) R.i n = u.462 D

242 x 0ma x

Figure A 2.4.1. Threshing cylinder vari-drive. Dimensions and symbols

The radius ofth edrive n disc canb e derived aswil l be explained below, from

R Ä + 2 (a2.13 ) out~ in" 2 ° ]/ij~ 2)-C + C'L - 2ifC-R± so for C = 0.5028 and L = 2.184(th elengt h ofth eV-belt )w e getequatio n (a2.14 )

Though themanufacture r stated that L =2.15 5m , thebel t was presumably larger because of elasticity. Thevalu e of L used inth eequation , is cal­ culated from theaverag e ofth e extreme positions ofth evariato r discs, indicated in thedrawing . R = R. - 0.7898+ /1.216 - 3.159-fl. (a2.14 ) out in in

RT = f(0 ) (a2.15 ) out 243 At D= O -»ff =0.1225-»i? =0.243-*R2=0.50 4 in out D =0.042-»Ä .=0.2134-* R =0.1597-»RÎ=1.34 in out

Derivation V-belt length For open, flatbel tdrive sth ebel t length (seefigur eA 2.4.2 )i saccoun ­ ted forb y

L = 2'C'cos j_ + ir(i?i+f?2} + 2x(ffi-#2) (a2.16 )

namely BD+AG+EF+AB+(DE+GF) A more accurate approachi stha tgive ni nth etechnica lmanual s(e.g . Roloff, 1972)i nwhic h

L= 2'C +ir(ff 1+ff2)+ X(Z?l-i?2 ) (a2.17 )

namely BS+AT+(EF+AB)+1jDE+ä5GF For small angles yields

I » tg * - &-=-&. (a2.18 )

andi nth efigur ei ti s

ffi- ff2 ^1' c (i?i--ffz) " Hence L = 2C + ir-Cffi + Rz) + (a2.19 )

S E

FigureA 2.4.2.Sketc h forth ecalculatio no fbel t length relatedt o the dimensions

244 Since a relation is needed in which i?i = f (i?2,....), the formula is trans­ formed to read as

2 2 z C'L = 2 C + I'C-Bi + TT« C'R2 + fli - 2Ri-R2 + Ri (a 2.20)

2 2 2 2 C'L = i?i -2Ä1rff2+i?2 + TT.OÄ1- IT C'R2+~"C

2 OL = j 'C2 - 2TT C-Ä2-2C2+C«L (a 2.21)

2 2 C'L = (f?i - R2 + f C) = (j - 2) C + CL - 2 TTCÄ2 (a 2.22) or, finally, as

fli = A> - | C + ]/{j - 2)C2 + C'L - 2ir-C-i?2 (a 2.23)

When Ran dL ar ereplace db y R andL (estand sfo reffective )the nthi s formulaca nb e approximativelyeapplied toV-belts .

A3.1.1 . Auger torque and elevator chain displacement as feed rate sensor Duringfiel dmeasurement swit hmachin eA th eauge rtorqu ean dth edis ­ placemento fth eelevato rchai nhav ebee nmeasure dan drelate dt oth e strawcollecte dbehin dth emachin eo na shee tafte ra nestimate d timedelay . Thistim edela yha sbee nestimate da sindicate di nA 2.3.4-d .Th eresult s ofthes emeasurement sca nb efoun di nth efigure sA 3.1.1. 1.. .A 3.1.1.9 . Bothparameter sar ecollate dpe rmeasurin gyea rt omak ei teasie rt oascer ­ taincomparabl etendencies .Th eelevato rchai ndisplacemen tha salway s beenmeasure db ymean so fa ninductiv elinea rdisplacemen tt ovoltag e transducer (Bergman,1976) . From196 9 ...197 1th eauge rtorqu eha sbee nmeasure db ymean so fstrai n gaugesmounte do nth edrivin gaxl ean dsinc e 1972i tha sbee nmeasure db y meanso fa specia ltransducer ,a sshow ni nfigur eA 3.1.1.10 ,whic hrecor ­ dedth edrivin gforc ei nth edriv echain .Thi stransduce rha sbee ndesigne d especially forthi sresearch ,bu ti sunsuitabl efo rprotracte dmeasurements , asth epivotin gpoin tdoe sno trotat eenough ,dus tan dmoistur ecausin g* jammingwhe nth epoin ti sno tcleane d frequentlyenough . Uptil l197 2th estra wwa scollecte do na shee tconsistin go f5 separat e .parts,an d3 0metre si ntota llength .Collectin gstarte dafte r2 0m har ­ vesting.Th emateria lo nth esheet sha sals obee nuse dt odetermin eth e walkerloss .Afte r197 2th estra wwa scollecte do na shee t1 5m i nlengt h whileth emachin eentere dth ecrop .

A3.1.3 . Auger torque to elevator displacement relation In197 3th emeasurin gsignal so fth eauge rtorqu ean do fth eelevato rdis ­ placementwer erecorde d from1 4test swit hmachin eA o nwinte rwhea tan d springwheat .Th elengt ho fth estretc hwa s24 0m ,resultin gi na recordin g timeo fabou t20 0s .Bot hsignal swer efiltere dfirs twit ha low-pas sfil -

245 TA N-m DE nur 180- 45 - • 1971 160- 40 - • A' 1971 • J uo- 35 - • 'KÀ 120 - 30 - 100- 25 - 0 * 80- 20 - 60- 15 - 40- 10 - / •• 20- 5-

0 1 () 1 2 3 1 2 3 FS kg.s-1 FS kg.s-1 FigureA 3.1.1.1 .Auge rtorqu et o FigureA 3.1.1.2 .Displacemen t strawfee drat erelationshi pi n elevatort ostra wfee drat erela ­ fieldtest so f30- mstretche swit h tionshipi nth esam efiel dtest s winterwhea t (Manella)i n197 1 asi nfigur eA 3.1.1. 1 (—)DE = 11.5-28.2 % -7.7+12.l«#S(r=0 .78) ; ( )DE= MCS = 2 ( ):linea requation : TA= -11.1+15.2«#S-0.56'(FS) (r=0.78) - 16.6+ 48.1»FS (r= 0.82 ) ( ):quadrati cequation : TA = 13.5+ 23.4 .FS+5. 53«{FS)2 (r=0.82)

1 2 FS kq.s-1 FigureA 3.1.1.4 .Relationshi po f displacementelevato rt ostra wfee d ratei nsam efiel dtest sa si nfigu i A3.1.1.3 :winte rwheat : ( )FS = 0.041 'DE+1.16 (r=0.73)sprin gwhea l ( )FS =0.097£»£'+0.74(r=0.86 )

FigureA 3.1.1.3 .Auge rtorqu et o strawfee drat erelationshi po f fieldtest si n30- mstretches(draw n points)wit hwinte rwhea t (Manella) (•); MCS= 21.3-36.3 %an dsprin g wheat (Solo) (o); MCS=20.7-55.8 % (datao f5- mstretches) ; ( )winter wheat: FS = 0.0050-2V1+0. 83 (r=0. 79) ; ( )spring wheat: FS = 0.012-2^ FS kg.s-1 - 0.39 (r=0.86) 246 TAN- m KO 1973 DE mm 120 30 - // 1973 100 25 - // 80 20 - yV / ' 60 15 - y / o

(0 10 • fS 20 5 - V'' À" 0 u 1 1 2 3 1 2 3 FS kg.s- 1 FS kg.s -1

FigureA 3.1.1.5. Auger torquet o Figure 3.1.1.6. Relationshipo fdis ­ straw feed rate relationship infiel d placement elevatort ostra w feed rate testso f15- m stretches with winter in same field testsa si nfigur e wheat (Manella)earl yi nth eseaso n A 3.1.1.5 (t)MCS = 22.3-27.3%( )FS=1.03+0.0146« ( )K=l.ll+0.069ö£'(r=0.99) E4(r=0.98)an dlat e (x)MCS =12.3 % ( )ffS=l.01+0.07805(r=0.98) ( )FS =0.93+0.0147-2Vl(r=0.98)an d ( )pS=1.08+0-096DE(r=0>96 ) spring wheat (Fundus)(o): MCS=23.5 % ( )ps =0.99+0.0184ffA(r=0.97)

TA N 180 160 1974 U0• DE mm 120 12 • 0 •V' 1974 100• 10 • y/s 80• 8 • 60 - 6 • 40 4 - • 0 ^ 20H 2

0 1 1- n 1 • 1 - -1 1 1 "4 5 4 5 6 FS kg.s-1 F S kg.s-1

Figure 3.1.1.7. Relationshipo fauge r FigureA 3.1.1.8. Relationshipo fdis ­ torque tostra w feed rate in15-m - placement elevator tostra w feed rate stretch with winter wheat (Clement)(•) in same field tests asi nfigur e MCS=56.3-57.7%, ( )FS=0.426+0.0287« A 3.1.1.8 TA (r=0.98)an dsprin g wheat (Fundus) ( )(• ) FS=Q.480+0.335 DE (r=0.93) (0),MCS =31.8=42.2% ( )FS =0.394+ ( ) (o)FS=0.236+0.37 9 DE (r=0.94) 0.0283ffi4(r=0.94)

247 TA N- 160 - 1975,1976 U0 - / / / / / / 120 - / / / / auger / / / ^ driving 100 - / chain 80 - / / •/• 60 - // / 40 - pressure 20 • transduc

0 1 1 1 1 2 3 4 FS kg.s-1 0-500mV

FigureA 3.1.1.9. Relationship ofauge r FigureA 3.1.1.10. Torque sensor mea; torque tostra w feed rate; field tests ring thetensio n inth eauge r drivini over stretcheso f1 5m wit h oats (1975, chain. Astor) (+).MCS=58% (—); ^5= 0.491+0.0129 » TA (r=0.98), spring wheat (1975, Fundus) {o);MCS =23% ( )FS=Q.229+0.022l'TA (r=0.99)an dwinte r wheat (1976, Clement) (•);M7S=17.8-18.5 ; ( )FS =1.35+0.0186 TA (r=0.97)

l-Vl-r* 0.7H

0.6 0.5 k/Yf >/ 0.4 -A 0.3-

0.2-

0.1

1 1 1 1 1 I 0 0.5 1.0 1.5 2.0 2.5 3.0 APs

FigureA 3.1.3.1.Th evalu e representing thepar to fth eauge r torque variation that isexplaine d byth eelevato r displacement: 1- /1-r asa functio n ofth eperio d APove r which thesigna l isaverage dfo r two different testso fabou t20 0s

248 terhavin ga break-poin tfrequenc yo f12. 5rad' s 1 andafterward ssample d ata samplin ginterva lo f0.0 8 s.B yshiftin gth edat ao fbot hsignal s andcarryin gou tcross-correlations ,th etim ela gca nb edetermine dfo r eachmeasure dstretch .Th edat ao fbot hsignal so ftw otest swer ethe n averagedove ra perio do f APand ,th ecorrelatio nr wa sdetermined ,th e lagbein gtake nint oconsideration . Infigur eA 3.1.3. 1th evalu eo f1 - A -r * hasbee nplotte da sa functiono f AP. Thisvalu erepresent sth epar to fth eauge rtorqu esigna l explainedb yth edisplacemen tsignal .

Inaddition ,th ecorrelatio nha sbee ncalculate dfo reac htes ta t AP= 2 fora linea rrelatio n DE = a + b'TA andfo ra nexponentia lrelatio n DE = a'expib'TA). TableA 3.1.3. 1show sth eresults .Sometime sth erelatio n israthe rgood ,sometime spoor .Bot hsignal ssee mt oinclud econsiderabl e measuringnoise .

TableA 3.1.3.1 .Coefficient so fcorrelatio nbetwee nelevato rdisplacemen t andauge rtorqu efo raveragin gperiod so f2 s ww= winte rwheat ,s w= sprin gwheat ,li n= linea rrelation ,ex p= expo ­ nentialrelation , DE = a'exp{b-TA)

trial crop lin exp

1 WW 0.64 0.63

2 WW 0.93 0.93

3 WW 0.82 0.80

4 WW 0.86 0.85 5 WW 0.80 0.80 6 WW 0.65 0.63 7 WW 0.67 0.62 8 WW 0.93 0.93 9 WW 0.87 0.88 10 WW 0.90 0.88 11 sw 0.74 0.70 12 sw 0.88 0.87 13 WW 0.53 0.51 14 WW 0.92 0.93

249 WL kg. s-'

0.07- WZ. kgs-

X 0.025- 006- X X

X 0.05- 0.020

x 0.04 - X X 0.015 X X

0.03- * >s< x x» X X .. x X aoio " x x ^ X X XX X * X 002- X x x?" x *> X xx ^ x * ^x/ x ** I *« X 0.005 0-01- * Jxï **xx * x x/«$** X*<*S< *jfr xxX ' x1K?"xxXxx

10 20 30 40 50 200 400 600 800 1000 WLM s-1 WLM S"1

FigureA 3.3.1.1 .Relatio nbetwee nmeasu ­ FigureA 3.3.1.2 .Sam ea sfigur e redwalke rlos sb yrethreshin go fstraw , A3.3.1. 1 fortest sdurin g197 3 gatheredb y6- msheets . (WL)an db ycoun ­ tingth enumbe ro fpulse sfro mth egrai n lossmonito rove rth esam estretche s (WLM) Testsi n 1972

WL kg.s- WL kg.s-' 0.020-

0.005- X

0004 0.015-

X 0.003- X 0.010-

X X 000 2 X xx 0.005- X 0.0 01 X X X X ! XX x X * * x*x* x XX* "x J£ X 11—It S—

10 20 25 1 WLM s-1 WLM s-

FigureA 3.3.1.3 .Relatio nbetwee nmea ­ FigureA 3.3.1.4 .Sam ea sfigur e suredwalke rlos sb ygrai nlos smeasurin g A3.3.1. 3 forth e197 6test s machine (WL)an db ycountin gth enumbe ro f pulsesfro mth egrai nlos smonito r (WLM) overth esam estretche so f30- mi nlength . Testsi n197 5

250 A3.3.1 . Grain-loss monitor Results from literature Inliteratur etw okind so ftes tresult sar ereported .Investigator swh o testedth emonito rove ra shor tperiod ,o ri na crop ,o rperio dwit h constantcro pproperties ,repor to nlinea rrelation sunti lpuls esatura ­ tionoccurs .The yrepor tals oo ncoefficient so fvariatio nsmalle rtha n 10% (Bouman,1971 ;Eimer ,1973 ;Kühn ,1970 ;Maler ,197 4an dReed ,1968) . Theresult sbecom eworse ,especiall ya sregard sth evariatio nwhe n testswer edon eove ra longe rperio dwit hchange si nth ecro pcondition s (Anonymus,1973 ;Graeber ,1975 ;Glaser ,197 6an dGullacher ,1979) .Th e reasoni sth evariatio ni nwalke rseparatio nefficienc yove rth econsi ­ deredperiod ,whic hals oaffect sth eseparatio nefficienc yabov eth e sounding-boardo fth emonitors .Som emonitor stherefor ehav ea switc hfo r selectingsensitivity .However ,ther e isn opoin tt othi ssinc eth eexten t towhic hth esensitivit yha st ob ealtere di sno tknown .

Results of field tests Thefield-tes tmethod sfo rth eyear s 1971 ...197 3ar eexplaine dshortl y inA 3.1. 2and ,fo rth eyear s197 4.. .197 6i nA 2.2.2.c .I nal lthes e yearsth eadde doutpu t (pulses)o ftw ograin-los smonitor sfixe da ttw o differentelement so fth ewalker swa scompare dt oth emeasure dwalke rloss . Inth eperio d 1971 ...197 3th ewalke rlos so fstra wwa sgathere do n sheets6 m i nlengt han dmeasure db yrethreshin gth econten to fthes e sheetsi na stationar ythreshin gan dseparatin gmachine .I nth eyear s 1974 ...197 6th estra wan dgrai nfro mwalker swa sreshake ni na mobil e machineconnecte d toth ecombin eharvester .I nthi smachin eth elos s overa travelle ddistanc eo f4 time s3 0metre swa sgathere d (seefig . A 2.3.2.8).

Infigure sA 3.3.1. 1 ...A 3.3.1. 4th edat aar eplotte do fwalke rlos si n kg"s asa functio no fth emonito routpu ti npulse spe rsecond .Th e figuresfo r197 1an d 1974ar eshow ni n3.3.1 .Th emeasurement si nal l theseyear swer edon ei nsevera lcrops ,winte rwheat ,sprin gwhea tan d oatsunde ra wid erang eo fcircumstances ,whic hi sth ereaso nfo rth e amounto fscatte ri nth eresults .

A3.3.2 . Principle of an improved loss monitor system Figure3.3.2. 1 of3.3. 2 showsth ebasi cide ao fimprove dlos smeasure ­ mentb ymeasurin gth eseparatio nunderneat hth ewalkers .T overif ythi s principle,dat ao flaborator ytest sa sintroduce di nA 2.3.2. bwer e usedt ocalculat eloss ,base do nth ewalke rseparation .Th eseparate d grainwa scollecte di ntray sunderneat hth ewalker s (Donkersgoed,1980) . Theseparatio nwa s assumed tob eexponential ,startin ga ttra y5 ,s otha t theconten to ftra y5 wa suse dfo rth ecalculatio nan dtra y8 wa schose n tob eth esecond ,becaus ei ti sneares tt owher eth elos soccurs .Th e separationabov etra y5 durin gth etes tperio do f1 0s wa scalle dS 5kg» m ,l thisbein gth econten to fth etra yi nk gdivide db yth elengt ho fth e trayi nm . S8wa sdefine di nth esam eway . Thedistanc e dbetwee nth ecentr epoint so fth etray swa s1.3 8m ,th e lengtho ftra y5 an dtra y8 wa s0.4 8m an d0.3 5m ,respectively .A swa s showni n3.3.2 ,

S =- WE'G-exp( - WE'X) (a3.1 ) w o where S =th eseparatio no fgrai na t x kg-s' «m' 1, x•-=th edistanc efro m

251 thebeginnin go f the correctexponentia lproces sm , WE =walke r efficiency m ,G =amoun to f graina tth e starto f the correctseparatio nprocess . S isnegative ,becaus e itconcern s thedecreas e ofgrai no n the wal­ kersbein g the grain collected inth e tray.Fo rS 5 x =o ,s otha tS 5= WE'G kg*m 1 for the testperio do f 10s .Fo r 58w ehav e

58 =S5-exp(Jffi>1.38 ), s otha t WE =In(58/55)/l.3 8an d Go =S5-1.38/ln(58/S5 ) Withknow n an d thewalke r loss ca nb e calculated from WE G o G„ x. Gç = G *exp(- WE'x) kg for x 1.38 + Jj'0.35m

Theresult so f this calculation are shown in figureA 3.3.2.1.Fou rkind s of crops:oats ,whea t 1,2 ,3 (seeA 2.3.2.b)ar euse d atdifferen t feed rates. WIMrepresent s themeasure d loss and WLCth ecalculate d loss for aperio d of 10s .Th e fulllin e inth e figure representsth e relation WIM= WLC,whil e thedotte d line isestimate db y linearregression ,givin g

WIM =- 0.03 4+ 1.00'WLC (r= 0.95)

We see thatth e low losses areoverestimate d and thehig h lossesunder ­ estimated,bu t the principleworks . Possibly thepositio n of the traysi s notoptimal .

WLC kg 0.4

FigureA 3.3.2.1.Walke r lossmeasure d in 03 OX the laboratory testri g (WLM)relate d to WLM kg walker loss calculatedo nbasi so fth e Fig.A 3.3.2.2.Calculate d loss contentso f tray 5an d tray 8 (WLC) . The {WLC)relate d tomeasure d loss cropswer eoat s (o)an dwinte rwheat , (WLM); (x)i n the casethat th e treated in threeways: .o=whea t 1,jus t contentso f tray 5an d 8ar e stored sotha tM7S=15% .A =wheat2 , combined; (•) in the case that stored and slightly moistened so that trays 5an d6 ar e combined, WC5=30%; += whea t 3,store d andconside ­ line ( )i s for WLC = WLM rablymoistene d sotha tACS=45% . The lines represent: ( ) WLM=WLCan d ( ) WLM=-0.034+1.00-WLC calculated by linear regression (r=0.95)

252 Glaser (1976)foun da linea rrelatio nwit hr =0.9 9 forth esam ekin do f testswit ha shakin gconveye rinstea do fstra wwalkers .

Inothe rtest s (Sterren,-1983),monitor swer efitte dabov etray s5 ,7 an d 8 (seeA 2.3.4. Can dfigur eA 2.3.2.5 ) andth emeasure dmonito routpu t wasuse dfo rcalculatio no floss .I nthi scas emonito rcalibratio ni s necessary.Thi si sdon eb ycomparin geac hmonito routpu tt oth eseparatio n giveni nth eseparatio ncurv ecalculate dwit hth econten to fth etrays . Themonito routput sshowe dpuls esaturation ,s otha ta nexponentia lrela ­ tionwa suse dfo rth ecalibration .Losse swer ethe ncalculate dfo rth e threepossibl epair so fmonitor si nth esam ewa ya salread yindicated . The_resultsagai nshowe da noverestimatio no fth elo wlosses .Th ebes t resultswer eobtaine db ycombinin gth emonitor sabov etray s5 an d6 a s wella s5 an d8 (seefigur eA 3.3.2.2).Measurin gfault so f40 %howeve r stilloccur .Furthe rresearch ,especiall yi nfiel dstudies,i snecessary .

A4.2.1. a Disturbances in erop density Variationsi ncro pdensit yhav ebee nmeasure di nfiel dexperiment san dstu ­ diedi nliterature .Th ecro pdensit yi sdefine da sth eamoun to fcro p(kg ) tob espli tu pint ograi nan dstra w (alsocalled :materia lothe rtha ngrain ) perare a (m2).Th eare aconsidere ddiffer san da sthi scoul daffec tth e results,th esubjec twil lb etreate dsystematicall yo nth ebasi so fincrea ­ singarea . Plotso f0. 5m 2,bein gtw orow so fwinte rwhea t1 metr ei nlengt hwer ecu t onbot hside so fa 30- mstri pharveste db ya combin eharveste r (Hijma,1970 ) Ineac hstrip ,6 plot sa tth eleft-han dsid ean d6 a tth erigh twer ese ­ lecteda trando man dcu tb yhan djus t0.0 5m abov eth eearth .Th emean_ ^ yieldo f 120plot swas :0.50 7kg' m2 straw (drymatter )an d0.47 8kg« m grain (drymatter) .Stra wlengt hwa s7 7c man dth emea nnumbe ro fear s perm 2wa s 192.Tabl eA 4.2.1. 1give sth ecoefficient so fvariatio no f the1 2plot spe rstrip .

TableA 4.2.1.1 .Coefficient so fvariatio n (CV% )o fcro pmeasurement s of 12plot so f0. 5m 2 atbot hside so fa stri pharveste db ya combin e harvester

YIELD grain number grain straw grain to of + straw ears strip straw ratio 1 16.6 15.2 13.7 8.2 11.7 2 10.8 9.1 9.6 5.0 11.7 3 17.0 22.6 19.0 11.5 17.9 4 9.1 9.2 8.7 5.5 7.0 5 14.3 15.4 12.4 8.6 13.1 6 9.7 11.7 10.4 5.9 11.8 7 16.1 16.7 15.7 5.9 15.4 8 10.5 9.9 9.2 8.8 14.0 9 9.2 11.1 9.7 5.9 9.7 10 11.1 14.7 12.8 6.4 15.0 msan 13.0 16.0 7.6 7.2 12.7 CV

253 Thecalculate dcoefficient svar yconsiderably .Th emea nvalue so fth ees ­ timatedcoefficient ssho wth ehighes tvalu efo rth estra wyiel dan da relatively lowvalu efo rth egrain-to-stra wratio .Th eyield so fth elef t andth eright-han d sideso fth estri pshowe dn ocoherence ,an dneighbou ­ ringplot sshowe dgrea tdifference si nyiel dthoug hth esoi lseeme duni ­ form.I twa stherefor econclude dtha ti nshor tdistance sth eyield ssho w littleo rn ocoherence .

Eimer (1973)measure dcro pdensitie so fplot s6 rows-wid ean d0.6-m-lon g (0.6-0.72m 2). Instanding ,weedles scro ph eregistere dcoefficient so f variationi nyield so fgrai nan dstraw :i nry e7.5 %i nwinte rwhea t9% , insprin gbarle y 14.5%an di noat s 18.2%. Inlodgin gcro pwit hweed sh efoun di nrye :15.6% ,i nwhea t14.6 %an d inoat s 19.6%.A greate rvariatio ni nstra wyiel dtha ni ngrai nyiel dca n beconclude dfro mth ediagram si nthi spublication .

Feiffer (1964)publishe dsimila rresults .Fo rwinte rwhea th eregistere d avariatio no f21.4 %an di nsprin gwheat,figure sbetwee n8 %an d64% .H e propablycalculate dth evalue so fth edifferenc ebetwee nminimu man d maximumyield sexpresse da sa percentag eo fth emea nyield .H eals oshow s thevariatio ni ncro pyiel dfo rfield so f3-m-wid ean d1-m-lon gi na sequenceu pt oa nare ao f3 m b y 15m .H efoun dth egreates tvariatio n forinterval so f0.6 6m an dlowe rvariatio nfo rlarge rintervals .

Heinrich (1968)measure dcoefficient so fvariatio no f4 0plot smeasurin g 0.5m b y 1.0m lyin gadjacen tt oeac hothe ri na directio nparalle lt o theseede drow sa swel la sperpendicula r toth edirectio nfo rwhea tan d rye.Th emaa nvalu ewa s10 %i nbot hcases . Largerfields ,wit ha widt hcomparabl et oth ecuttin gwidt ho fa com ­ bineharvester ,wer eteste dt odecid eo nth evariatio ni nmas stha tth e machinewil lusuall yenter .Som eauthor sexpec tlowe rcoefficient so f variationbecaus eo fth eeffec to ftakin gth emea nove ra large rarea . However,a sth evariatio ni nth ex -an dy -direction si sth esame ,thi s effectwil lno toccur . Feiffer (1964)indee dregistere dth esam evariatio ni nfield smeasurin g 1m b y3 m . Eimer (1973)measure dth eyiel do fplot s1-m-wid ean d0.6-m-long ,thre e nextt oeac hother ,ove rth elengt ho f 1m .Th eyiel do fth elef tan d rightplot sdeviate d 3%o ftha to fth ecentra lplot .

Ownresearc h (Huisman,1973 )o nfield s5-m-wid ean d1.5-m-lon gi na direc ­ tionparalle lt oth edrainag etube san dperpendicula rt otha tdirectio n showedcoefficient so fvariatio n forstra wyield so f10.3 %an d10.2 % respectivelyan dfo rgrai nyield s5. 2an d6.7% ,respectively .Th emea n strawyield swer e0.5 6 and0.7 6kg* m2 andth egrai nyield s0.5 5 and0.6 3 kg*m2 ,respectively .Fig .4.2. 1 showsth epatter no fthes eyields . Infiel dtest si nwhic hth estra wmas sou to fth ecombin eharveste rwa s gatheredo nsheet san dweighed ,th ecoefficien to fvariatio no fth eyield s of5 m x 5 m field so fsprin gwhea tturne dou tt ob e 15.9%(o f10 2measure ­ ments). Whe nth esam eyiel dfigure sar etaken ,bu tpu ttogethe rb yth e 6 sheetsformin gon esingl erun ,th ecoefficien to fvariatio nbecome s 23.1% (Huisman,1974-b) .I n197 0th ecoefficient so fvariatio no farea s of 154m 2 comprisingth esam e1 0run smentione di nTabl eA 4.2.1. 1wer e foundt ob e 14.3%fo rth estra wyiel d (plotso f0. 5m 2 showed 16.0%)an d forth egrai nyiel d 3.9% (compare 13.0%) (KleinHesselink ,1971) .

254 Bogdanova (1960)report so ncoefficient so fvariatio ni nyield so f50- m runsvaryin gfro m7 %t o40% .

On'th ebasi so fal lthes eresult si twa sconclude dtha tther ei sn orea ­ sont oexpec ta differenc ei nth evariatio ni nrelatio nt oth eare acon ­ sidered.Th emeasure dvalue sar eestimate so fvariation stha tca ni nfac t differowin gt ovariation si nsoi lan dcro pproperties .

A4.2 .l. b Disturbances in measured stram feed rate and loss signals Themeasure dsignal so fa numbe ro frun si nth efiel dwer eanalyse db y meanso fstandar dFas tFourie rtransfor mtechniques .Withou tgoin gint o detailsom eo fth eresult swil lb epresente dhere .Th ecoherenc ebetwee n feedrat esigna lan dlos ssigna lwil lb estudie dtoo ,whic hmake si tuse ­ fult opresen tth eresult so ffee drat ean dlos stogether .Tw okind so f datawer euse d A)Dat ao fmea nvalue so fth eauge rtorqu esigna lan dgrai nlos smonito r per0.25- mstretc h (~0.2 5 sa tmachin espeed so fs 1 m- s l). Inthi s case75 0sample swer eavailabl epe rrun .T othes edat azero swer eadde d until102 4dat awer eavailable . B)Dat ao fmea nvalue so fthes esignal spe rperio do f0.0 5 s.I nthi s case360 0sample swer eavailabl ean dzero swer eadde dunti l409 6sam ­ pleswer eavailable . Beforezero swer eadde dsom ecorrection swer eapplied .Firs tth emea n valuean dtren dwer ecalculate dan dth edat acorrecte daccordingly .The n atape rwa sapplie dove r10 %o fth edat aa teac hen dan dth estandar d deviationcalculate d forstandardisation .Fo rth eplot sa Barlet twindo w of 10%o fth edat awa sapplied .Th evalue suse dwer ecalculate dt ouni t offee drat ean dlos si nkg* s 1. Thedat ao fB wer eonl yuse dfo rfig . 4.2.3 inth etext .

Inth efigure snex ti nsequenc eresult sar eshow no fru n41 ,comprisin g 750sample so f0.25- mmeans .Fig .A 4.2.1. 1show sth eprobability-densit y functionaroun dth emea nvalue .Th emea nvalu ean dstandar ddeviatio nfo r thefee drat ewer e2.25_an d 0.0241kg #s * respectively,andfo rlos s 0.00844an d0.024 1kg' s1 respectively.A sca nb eseen ,th efee drat e

P 0-6 -\

0.4 n 02

IrRR- L 5

FigureA 4.2.1.1 .Probabilit ydensit y (p) functiono fmeasure dwalke r loss ( ;—)an dstra wfee drat e ( ) fortes tru n4 1 255 distributioni spracticall ya Gaussia none .Th edistributio no flos si s skew,a scoul db eexpecte dfro mth eexponentia lrelatio nbetwee nfee d ratean dloss .Othe rtest ssho wth esam epattern . Fig.A 4.2.1. 2show sth estandardise dautospectr ai nlinea rscal ean d fig.A 4.2.1. 3doe ss oi ndoubl elogarithmi cscale .Th emachin espee do f thistes twa sconstantl y0.8 4m*s -1 sotha tth escal ecoul db econverte d tocorrec tfrequencies .Th epea ka t3.1 5rad-s -1i nfee drat ei sdu et o therotationa lspee do fth eauger .Th epowe ri sdecreasin gwit hincreasin g frequency.Abov e6 rad's -1 thedro pi sno tcause db yth eaveragin gpe r 0.25-Œstretch(o r0. 3s i nthi scase )a sfig .4.2.3 ,wit hdat aaverag e over0.0 5s ,show sth esam epattern ,bu ti scause db yth efirst-orde rnois e character.I ti sno tclea rwher eexactl yth ebreakpoin tfrequenc y ofth edecreas eo fpowe rlies ,possibl ya frequenc ysmalle rtha n0. 1 rad's-1.I nfigur e4.2. 3th epeak sdu et oth epenetratio no fth eauge r fingersar ever yclear ,jus ta si sth epea ka tth elos slines ,owin gt o therotationa lfrequenc yo fth ewalkers .Thi si sbecaus eo fth eextr a droppingo fseed so nt oth esenso rboard swhe nth ewalke rmove supward s again.

Inth eplot sno wgive nbelo wth ecoherenc ebetwee nlos san dfee drat e ofa nothe rtes tru n(52)_wil lb eshown .Th emea nleve lo fth efee drat e ofthi stes ti s3.0 7kg- sx an dth estandar ddeviatio n0.51 6kg-s" 1.Th e valuesfo rth ewalke rlos sar e0.02 7an d0.19*1 0" * kg«s-1.Th eaverag e machinespee di s1.0 2m' s* .Fig .A 4.2.1. 4show sth eprobabilit ydensit y functionan dfig .A 4.2.1. 5th eautospectr aa tlinea rscale .Thes efigure s showth esam epatter na sth eothers . Thedela ybetwee nfee drat ean dwalke rlos swa sestimate db ymean so f aphas espectrum .Fig .A 4.2.1. 6show sth ephas espectru mcalculate dafte r adela yo f9. 5s wa sapplied . (Barlettwindo w10% )Whe ncoherenc ei sgoo d thephas eca nb ecalculate dcorrectly .I tca nb econclude dfro mthi s phasespectru m (andothers )tha tonl ya dela yoccurs . Fig.A 4.2.1. 7show sth ecoherenc espectru mfo rthre edifferen tBarlet t windowsapplied .Othe rspectr asho wth esam epattern .Ther ei spoo rcohe ­ rencei ngenera lwhil eth ebes tcoherenc ei smostl yfoun da tth elo w frequencies.Thi sprove stha tther ei sa causalit ybetwee nfee drat ean d loss. Fig.A 4.2.1. 8show sth ecros san dautocorrelatio n functionso flos s andfee drate .Th eautocovariancie sdecreas ever yrapidly ,s otha tther e isles spredictiona linformatio ni nthes esignals ,a sca nb econclude d fromth evalu eo f1/ e= 0.3 7tha ti sfoun da ta la go f0.3 6s fo rth e feedrat ean da t0.2 1s fo rth elosses .Th ecros scovarianc ei salway s lowbu ti sjus tabov eth enois elevel .I nthi sfigur ei tca nb esee ntha t thedela ywa sestimate dcorrectly .

Thegenera lconclusion st ob edraw nfro mthi sshor tsigna lanalysi sar e: -th esignal-nois erati oi slow ,especiall ya tth elos ssignal ; -th etransfor mi snonlinea ra sca nb eshow ni nth eplots ; -mor eresearc hha st ob edon et ofin dth ereason sfo rth epoo rsignal - noiserati oan dt oexplor ei ndetai lth ecoherenc eo fthes etw osignals . Fromforme rtest si ti sknow ntha tth edisplacemen televato rchai nshow s thesam epatter ni na nautospectru ma sth eauge rtorqu edoes .However , itwil lb ewort hwhil estudyin gth ecoherenc eo fth edisplacemen tsigna l toth elos ssigna li nfutur etoo .

256 0.004

radf .s- 1

FigureA 4.2.1.2.Autospectr ao fwalke r loss ( )an dstra w feed rate ( )o fth esam e dataa s figure A4.2.1. 1 (inlinea r scale)

20-|*10-3

• i 1111 1—i—i i i i iii i—i ii i m 002 005 01 0-2 0-5 1 2 5 10 f rad-s" 1

Figure A 4.2.1.3. Autospectra ofmeasure d walker loss ( )an dstra w feed rate ( )o fth esam e data as figure A 4.2.1.1 and figure A 4.2.1.2,bu tplotte d indoubl e logarithmic scale

257 p 0.8-

0.6-

0-4-

0.2-

,1 ».ri f -T-,1 , -5 -4 -3 -2 -1 0 12 3 4 5

Figure A 4.2.1.4. Probability density function of measured walker loss ( ) and feed rate ( ) for test run 52

0-004

000 2

FigureA 4.2.1.5 .Autospectr ao fwalke rlos s( - -)an dstra wfee drat e ( )o ftes tru n5 2

258 phase° 1000-

8 10 12 frad-s- 1

FigureA 4.2.1.6 .Phas espectru mo fwalke rlos san dstra wfee drat esignal s oftes tru n5 2

r 10-\

08

0.6

OX

0.2

10 12 /rads" 1

FigureA 4.2.1.7 .Coherenc e spectrumo fwalke rlos san dstra wfee drat e signalfo rthre edifferen tBarlet twindow s ( )=10%,( )=5 % (- )=2.5%

259 Figure A 4.2.1.8.Autocorrelatio n function of straw feed rate ( ) andwalke r loss ( )signal s aswel l as crosscorrelation ( ) while the delay iscorrecte d succesfully

A4.2.1. C Registration of crop variations and machine performance in a practical situation Field studies were performed for thepurpos e of 1) registering realistic variations in cropdensit y andothe r cropproper ­ ties affecting losses, and 2) the machine performance of amanuall y controlled combineharveste r for comparison with simulated automatically controlled machines.

A combineharveste r of the large-scale grain farmo f the IJsselmeerpolders Development Authority was fitted with measurementdevice s and a four-channel tape recorder.Th e recorded signals were:th e forward speed of the machine, the feed auger torque,th e grain loss monitor pulses.Calibratio n runswer e performed every three or fourhour s toestablis h the relationbetwee n real speed and measured speed,outpu t signal of the feed auger torque measure­ mentan d straw feed rate aswel l as.thato f the grain lossmonito r output and real losses.Th e speed was measured by apuls e generator»generating about 76 pulses for each traversed metre.Th e feed-auger torque wasmea ­ sured by a special device shown in fig.A 3.1.1.14 and calibrated by comparing themeasuremen t output toth e feed rate.Th e feed ratewa s cal­ culated from the speed of themachin e and the straw collected over a dis­ tance of 12m on a sheetbehin d the machine and thenweighed .

260 The results are shown in figure 3.1.1.3. The lossmonito r output was compared toth e walker lossgathere d together with the straw from the walkers on sheets 50m in length and separated from that strawb y a spe­ cial loss-measuring machine.Thi smachin e consisted of a sheet-pick-up device atth e front of the loss-measuringmachin e shown in fig.A 2.3.2.8. The losspulse swer e later on converted into an analog signal.Fig . A 4.2.1.9show s themeasurin g points of the twocurve suse d for calibra­ tion.Thes e datawer e thebasi s forexponentia l curves which were used for calculating losses from the analog signal generated by the test runs of interest.

Eight test runs of twoday s (August 21st and 23rd)wer e selected tob e used for the calculations.Thes e runs concern tests of twovarietie s of winter wheat,Nauticaan d Anouska,harveste d under the moisture conditions of the whole day. The mean values of speed, loss and feed ratewer e calculated over each 0.25 mdistanc e covered in a total distance of 200m .

WLkg.s- 1 0.3-

0.2- 1 1 1 1 1 1 1 1 / « / / 11 / / 0.1- 7 /

. x M, ^=r 1 -i 1- 0 -0.5 -1.5 -2 -2.5

FigureA 4.2.1.9. Calibration curves ofwalke r loss WL= walke r loss measured at the sheets, WLM= walke r lossmeasure d by grain loss monitor,+ , x= two different test runs in nautica ( , ), A = test run in anouska( - )

261 Thedela ybetwee nlos san dfee drat ewa scalculate db ycross-correla ­ tionfo reac htes trun .!h ecalculate ddelay swer eliste di nTabl e A4.2.1.3 .Th edela yo fspee dan dit seffec to nth efee drat e was assumed tob e0. 4s an dconverte dt oth efigur e appropriatet oth edistanc eo f0. 5m . Knowingthes edelays ,i twa spossibl et ocalculat estra wdensitie san d loss- fee drat erelation sfo reac htes trun . Theapparen tstra wdensit ype rdistanc eo f0.2 5 mwa scalculate db y dividingth edelaye dstra wfee drat evalu eb yth eproduc to fth emachin e speedan dth econstan tcuttin gwidt ho f5. 9m . Thelos s- fee drat ecurve swer eobtaine db ycalculatin gth emea nva ­ lueso ffee drat ean ddelaye d lossove ra distanc eo f8 m an dfittin gcur ­ vesb ylinea rcorrelatio no fth emode l

XnWL = DO+ Dl-FS

Thesevalue so f DO and Dl areliste di ntabl eA 4.2.1.3 . Thedistanc eo f8 m wa schose nafte rcompariso no fth ecurve sobtaine d byaveragin gove r0.25 ,0.5 ,1 ,2 ,4 ,8 ,1 6an d3 2m .I ngenera lth eave ­ ragingcurve sove r8 ,1 6an d3 2m wer esimilar ,bu twhe nth eaveragin g dataove rshorte rdistance swer ecorrelate d thecorrelatio nwa sfoun dt o bepoo rand ,a sa result ,th ecurve sflat .Th ereaso ni st ob esough ti n thevariatio no fth edela yan dothe rdisturbances ,whic hcaus epoo r coherencewhe nth eeffec to fth evariatio ni sno tfiltere dout .

Thegenera lcro pcondition sdurin gth etest sar eshow ni ntabl eA 4.2.1.2 .

TableA 4.2.1.2 .Genera linformatio no ncro pcondition so fth etes trun s usedi nth esimulation s

Varietyo fwinte rwhea t Nautica Anouska Harvestdat ei nAugus t 21st 23rd Moistureconten tgrai n% 16 17 Moistureconten tstra w% 31 17 Grainyiel dkg'h a 6200 6200 Grain-to-strawrati o 1.06 1.44

The BETAan d WEPvalue so fth ethreshin gan dwalke rseparatio nmodels , calculatedb yparamete restimatio ntechnique sar eals oliste di ntabl e A4.2.1.3 .Thi swil lb eexplaine d inparagrap h6.2.1 .

262 TableA 4.2.1.3 .Dat ao fcalculate dparameter san dmea nvalue so ftes t runsuse di nth esimulation s Var. =variety :N mean snautica ,A mean sanousk a Delay= calculate ddela ybetwee nmeasure dauge rtorqu ean dgrai nlos s monitorsigna l DO, Dl= parameter si nloss-to-fee drat eequatio n BETA1= threshin gcoefficien testimate db ysimulatio n BETA2 =threshin gcoefficien testimate db ycorrectio no f BETA1 WEP= estimate dwalke refficienc yparamete r SDAV= averag estra wdensit yo ftes tru n VMAV =averag emachin espee dmeasure da tth efiel dtes t FSAV= averag estra wfee drat emeasure da tth efiel dtes t WLAV= averag ewalke rlos smeasure da tth efiel dtes t

Test Var. Delay DO Dl BETA1 BETA2 WEP SDAV VMAV FSAV WLAV nr. _,_,_,_. kg«m m«s kg»s kg«s 12 N 10.0- 8. 3 1.1 1.806 1.75691.74 7 0.66 0.98 3.80 0.0163 33 N 8.5 -6. 3 1.1 1.561 1.42121.60 0 0.60 0.99 3.50 0.1105 37 N 9.5- 5. 70. 9 1.451 1.31501.93 1 0.50 0.98 2.89 0.0502 39 N 10.0- 6. 7 0.5 1.818 1.75391.78 9 0.62 0.90 3.29 0.0071 52 A 9.0- 5. 90. 7 1.643 1.61551.79 1 0.52 1.02 3.10 0.0263 55 A 10.5-10. 83. 0 1.531 1.36201.89 6 0.42 0.94 2.29 0.0176 A 57 9.5 -10.12. 6 1.546 1.40381.87 7 0.45 0.95 2.53 0.0298 A 61 9.0 -8. 5 1.3 1.766 1.71251.69 2 0.49 0.96 2.01 0.0074

A4.6.4 . Measurement of losses on combine harvesters of farmers and contractors in practice Machineperformanc etes tmeasurement si npractica lsituation swer ecarrie d outi n 1972 an d1980 .Simpl emeasuremen ttechnique swer euse dt ob eabl e toresearc ha sman ymachine sa spossibl ei neac hseaso nb yon eo rtw omen . Farmswer eselecte da trando mfro mal love rth eNetherlands .Th eoperato r wasaske dt od ohi swor ka sh ewa si nth ehabi to fdoing .Th emeasure d variablesan dth euse dmeasurin gtechnique swer ea sfollows . Walkerloss .Walke r+ siev elosse swer egathere di n197 2o na shee t2 m long,whil ei n198 0jus tth ewalke rlosse swer egathere do na 10- msheet . Sieveloss .Thes ewer ecollecte di nbot hyear si na catc hnet ,hel d behindth esieve sb yhan dove rth e10- mstretch . Strawfee drate .Th estra wcollecte do nth esheet swa sweighe dan dth e machine speedwa smeasure dove r 10m ,s otha tth efee drat ecoul db ecal ­ culated. Moistureconten to fstra wan do fgrain .Sample' swer etake nimmediatel y afterth edischarg eo fstra wo rgrain ,an dth emoistur econten t (wetbase ) wasmeasure db yth eove nmethod . Threshingloss .Th elosse swer eestimate db ytakin g5 0threshe dear s fromth estraw ,rethreshin gthe mb yhan dan dcomparin gth ethreshe dgrain s toth enumbe ro fgrain si n5 0unthreshe dears . Adjustments,machin ean dgenera lcro pdat awer eals orecorded . 263 Themeasuremen tdat ao f 1972ar eliste di nTabl eA 4.6.4.1 .Th emeasure - mentdat ao f 1980ar eliste di nTabl eA 4.6.4.2 . Twomeasurement swer e donethe na teac hmachine .Fo rthi stabl eth estra wfee drat ei scalculate d ona 1-metr estandar dwidt ho fth ethreshin gcylinder .Th emas sfigure s arebase do nth ewe tweight .

TableA 4.6.4.1 .Dat ao fmeasurement si npractica lsituation so f197 2 (seetext) . AFS =specifi cstra wfee drate , VM= machin espeed , MCS= stra wmoistur e content, MCG= grai nmoistur econtent , TL =threshin gloss , SL =siev eloss , WL= walke rloss , GY= grai nyiel d

User Crop AFS_ VM MCS MCG TL SL_ WL GY kg's 1 m-s"1 % % % kg«ha 1 % kg*ha 1 % kg'ha' C wb 1.9 0.7 55 21 1.7 32.5 0.47 418.0 6.10 6860 F sb 1.6 0.9 40 25 4.5 3.8 0.01 10.0 0.25 4000 C wb 1.7 0.6 58 19 1.4 55.8 0.98 123.0 2.20 5600 C sb 1.6 1.2 13 20 1.4 3.0 0.08 33.0 0.83 4000 C sb 2.3 1.0 61 26 2.9 8.8 0.20 117.0 3.75 4400 C sb 2.3 1.2 63 23 0.8 192.0 4.80 280.0 7.00 4000 C sb 0.7 1.1 33 21 0.0 1.8 0.11 6.7 0.39 1700 C sb 1.5 1.0 48 18 2.5 56.3 1.33 69.0 1.64 4200 C wb 1.6 1.2 45 12 0.7 15.5 0.31 17.7 0.35 5000 C sb 1.9 1.5 17 13 2.1 32.2 0.86 37.9 1.02 3730 F wb 0.6 0.7 20 15 2.0 1.4 0.03 15.5 0.30 4600 F ww 2.3 0.7 61 18 1.5 8.1 0.20 30.2 0.74 4070 C sw 2.2 1.5 12 20 0.0 33.5 0.80 238.0 5.67 4200 C sw 2.2 1.5 47 18 0.0 4.0 0.10 6.5 0.17 3840 C ry 2.3 1.6 24 26 0.6 4.2 0.15 43.3 1.54 2800 F ry 1.1 0.9 30 20 1.2 1.6 0.05 3.3 0.09 3500 F ry 1.3 1.1 25 20 0.5 19.5 0.53 22.2 0.60 3700 C ww 1.8 0.9 31 27 1.5 4.2 0.09 8.3 0.19 4450 C ww 2.6 1.0 31 21 1.5 4.8 0.11 14.8 0.30 4450 F ww 1.5 1.8 22 20 0.7 19.3 0.37 26.4 0.50 5250 F ww 1.7 0.6 19 18 0.5 4.4 0.08 6.7 0.12 5700 F oa 1.6 1.0 48 18 0.5 6.7 0.11 48.0 0.80 6000 C ww 2.8 1.1 46 20 1.0 61.4 1.23 347.0 6.94 5000 F oa 0.8 0.6 30 15 1.4 12.5 0.22 181.0 3.20 5675 C ww 2.2 1.2 42 20 0.4 26.8 0.54 391.0 7.82 5000 C oa 2.3 0.8 48 20 0.1 5.7 0.10 127.0 2.23 5700 C oa 0.9 0.6 23 14 0.6 5.8 0.12 184.5 3.93 4700 c oa 1.8 1.2 7 14 0.0 5.8 0.13 221.0 5.04 4400 c ry 2.7 1.1 16 20 0.7 4.4 0.11 68.7 1.73 4000 c ry 1.9 1.0 33 19 0.6 4.4 0.18 158.0 6.45 2450 c sw 2.3 1.2 21 20 0.5 10.5 0.23 28.7 0.62 4630 F oa 1.3 0.6 20 19 1.0 20.8 0.50 111.5 2.79 4000 F sw 1.5 0.9 27 19 1.5 5.7 0.16 6.7 0.19 3600 F sw 3.0 1.6 24 20 2.2 65.5 2.43 75.4 2.80 2700 C oa 1.9 0.8 65 21 0.4 9.2 0.20 129.0 2.76 4700 C sw 3.6 0.8 54 20 — 8.7 0.26 97.0 2.94 3300

264 TableA 4.6.4.2 .Dat ao fmeasurement si npractica lsituation si n198 0 (seetext) .Cro pi swinte rwhea tonly . FS =stra wfee drate , VM= machin espeed , MCS= stra wmoistur econtent , MCG =grai nmoistur econtent , TL= threshin gloss , SL =siev eloss , WL=walke r loss, GX= grai nyield .

User FSFS VMVM MCS MCG TL SL WL GY -1 kgj» s m m'S 1 % kg-ha kg»ha 'l kg-ha"1 kg«ha x 1.27 1.15 26 17 14.9 0.3 0.8 6700 1.42 1.14 35.6 0.5 1.9 1.40 1.05 30 18 6.7 3.9 13.8 7500 1.43 1.09 10.0 2.8 10.0 1.21 0.74 62 20 52.0 1.9 232.0 7500 1.01 0.70 87.9 1.6 137.2 1.16 0.82 45 17 60.8 33.2' 14.0 6800 1.20 0.83 12.4 11.2 14.2 1.44 0.96 37 19 10.1 3.1 14.7 8000 1.31 0.97 31.2 2.4 19.0

1.17 0.82 27 19 9.7 10.1 2.3 6700 1.24 0.80 5.5 7.3 2.5 0.88 0.50 53 18 17.8 9.8 16.1 7500 0.95 0.79 10.6 13.0 10.6 0.69 1.02 50 17 6.2 3.4 1.9 7000 1.14 1.06 9.2 3.7 7.2 0.68 0.80 58 21 8.8 3.8 14.4 6500 0.88 0.89 6.8 1.0 19.1 0.84 0.98 28 16 7.7 0.9 2.3 6000 0.88 1.00 6.2 1.0 6.2

0.49 0.81 54 17 0 2.5 3.6 7000 0.75 1.08 0 1.1 7.6 0.81 1.08 29 15 3.4 2.9 1.7 6000 1.14 1.06 6.9 3.0 7.8 1.38 0.75 34 16 26.9 3.3 8.9 750 0 1.42 0.69 64.2 3.6 19.6 1.53 1.00 46 20 80.9 2.5 74.7 6500 1.86 0.98 53.8 2.5 118.0 1.87 1.09 24 18 3.3 6.8 11.1 6500 1.53 1.08 0 9.3 8.3 1.78 0.70 38 18 3.0 6.9 30.3 7200 1.25 0.62 4.5 4.4 25.6

265 A6.1.2 . Short description of C.S.M.P.

Thesimulatio nlanguag eContinuou sSyste mModelin gProgra mII Iwhic hwa s usedallow sth edigita lsimulatio no fcontinuou sprocesse so nlarge-scal e digitalmachines .Th edetail so fthi sprogra mar ecomprehensivel ydescribe d inth emanua l (Anonymus,1975 )fro mwhic hth efollowin ggenera ldescrip ­ tionsar etake nt ogiv ea nimpressio no fth epossibilitie san dstructur e forth econvenienc eo freader sunfamilia rwit hthi saspec to fth eproblem .

"Theprogra mprovide sa napplication-oriente d languagetha tallow smodel s tob eprepare ddirectl yan dsimpl yfro meithe ra bloc kdiagra mrepresen ­ tationo ra se to fordinar ydifferentia lequations .I tinclude sa basi c seto ffunctiona lblock swhic hca nrepresen tth ecomponent so fa continuou s systeman daccept sapplication-oriente d statementsdefinin gth econnection s betweenthes efunctiona lblocks .CSM PII Iaccept sFORTRA Nstatements , allowingth euse rt oreadil yhandl enonlinea ran dtime-varian tproblem s ofconsiderabl ecomplexity .

Inputan doutpu tar esimplifie db ymean so fuser-oriente d controlstate ­ ments.Forma toption sar eprovide dfo rprint-plottin gi ngraphi cform , scaledplottin gi ncontoure dan dshade dform ,an dprintin gi ntabula rform . Thesefeature spermi tth euse rt oconcentrat eupo nth ephenomeno nbein g simulated,an dno tth emechanis mfo rimplementin gth esimulation .Th epro ­ gramprovide sbot ha basi cse to ffunctiona lblock s (alsocalle dfunctions ) andth emean sfo rdefinin gfunction sespeciall ysuite dt oth euser' spar ­ ticularsimulatio nrequirements .Include di nth ebasi cse tar esuc hcon ­ ventionalanalo gcompute rcomponent sa sintegrator san drelays ,plu sman y special-purposefunction slik edela ytime ,zero-orde rhold ,dea dspace , limiterfunctions ,variable-flo wtranspor tdelay ,generalize dLaplac e transform,an dth earbitrar yfunctio no ftw ovariables .Thi scomplemen t isaugmente db yth eFORTRA Nlibrary ,whic hinclude ssubprogram sfo rloga ­ rithmic,exponential ,trigonometric ,an dothe rmathematica lfunctions .

Specialfunction sca nb edefine deithe rthroug hFORTRA Nprogrammin gor , moresimply ,throug ha macr ocapabilit ytha tpermit sindividua lexistin g functionst ob ecombine dint oa large rfunctiona lblock .Th euse ri sthere ­ bygive na hig hdegre eo fflexibilit yfo rdifferen tapplicatio nareas . Forexample ,b yproperl ypreparin ga se to fspecia lblocks ,h eca nrestruc ­ tureCSM PII Iint oa napplication-oriente d languagefo rchemica lkinetics , controlsyste manalysis ,o rbiochemistr yfo ran yparticula rspecial-purpos e fieldi ncontinuou ssyste msimulation .

CSMPII Ials oprovide sth eCSM PII ILanguag eTranslator .I taccept sa model (orbatche so fsevera lmodels )compose do fman ydifferen ttype so f statementsclassifie da sfollows :

266 1.Structur e Statements,use d todescrib e the structure and properties of the system tob e simulated. 2.Dat a statements,use d togiv e values toparameters ,constants , initial conditions,tables ,an d other data characterizing the specific situa­ tiont ob e simulated. 3.Executio n control statements,use d toreques tparticula r simulation runs and specify,i nparticular , their integration stepping andcon ­ ditions of termination. 4.Outpu t control statements,use d to request particular printed and machine-readable documents. 5.Translatio n control statements,use d to impose structure on themodels , to extend modeling facilities,t o separate models,an d to provide additional capacity in the simulation vehicles produced. 6. FORTRAN statements (incertai n contexts),use d tosupplemen t any of the above typeso f statements.

The Translator analyzes each model and produces from it two files and a Translation Output listing.On e file contains allo f the data,Executio n control, and Output control statements for conducting aparticula r simu­ lation session. Iti scalle d the Execution Input file.Th e second file contains FORTRAN language subprograms ofwhic h the ones ofmos t interest here are the BLOCKDAT A subprogram and subroutine UPDATE.

These areproduce d by theTranslato r from the structure,translatio n con­ trol, and FORTRAN statements included in the model.UPDAT E is the sub­ routine executed in the CSMP IIIExecutio n phase incomputin g model dyna­ mics during a simulation run.UPDAT E and the other routines in the second file are compiled under FORTRAN tobecom e themodel-specifi c portion of a simulation vehicle.Th e Execution phase then uses the simulation vehicle toperfor m the simulations requested by the statements saved in theExecu ­ tion Input file and generates any documents requested there.

A simulation vehicle produced from aparticula r model mayb e saved and used repeatedly in separate Execution phases as long asn o changes need tob e made inth e structure,translatio n control,o rFORTRA N language portions of the model.Th e user simply prepares ane wexecutio n input deck (seto f data. Execution control,an dOutpu t control statements) according to the further simulationsh e wishes performed and supplies them to adifferen t CSMP IIIprocedure. "

267 FigureA 6.1.2. 1show sho wblock si na bloc kdiagra mo rmathematica l functionsar erepresente db yCSM PII Ilanguag estatement scalle dstructur e statements.

BLOCK REPRESENTATION

*1 DEVICE

INPUTS X2 (Parameters ^ -I I OUTPUTS

X n Pi,P 2,...,P.,) m

MATHEMATICAL EXPRESSION

Y *1, ft,.. - m= f(Pi ,P 2,..., P., Xi, Xi,..., Xn)

EQUIVALENT CSMP III STATEMENT

Yl, Y2,.. ., Y M= DEVICE (PI,P2,... ,PJ ,XI ,X2,... ,XN )

FigureA 6.1.2.1 .Th evariou srepresentation so fa relatio n

Intabl eA 6.1.2. 1th eCSM Pstatement suse di nthi sstud yar elisted .

Thestructur estatement stha tw edevelope d forou rprogra mwer ea "corrector " andth ecos tminimisatio nalgorith mfo rcontro lsyste m1 an dcontro lsyste m2 . The"corrector "wa srequire dfo rsimulatin gth ebehaviou ro fth ehydrauli c cylinder.Th etranslatio no fth era mo fa hydrauli ccylinde rwa ssimulate d bya nintegrato ran da limiter .Th eoutpu to fth eintegrator ,however ,ca n stillincreas ewhe nth euppe rboun do fth elimite ri sreached .Th eoutpu t ofth elimite rwil lonl ydecreas ewhe nth einpu to fth elimiter ,th eout ­ puto fth eintegrato rundershoot sth euppe rboun do fth elimiter ,th e oppositetake nplac ei nth ecas eo fth elowe rlimit .Th ecorrecto rthere ­ forebehave slik eth eoi linpu to routpu to fth ehydrauli ccylinder .I fth e cylinderi sa tit smaximu mo rminimu mth eoi lstrea mwil lb ezer oan dth e outputo fth eintegrato rlikewise .I nFortra nlanguage :

Y=x IF(OINT.LE.LMIN.AN DX.LE.0.0 )Y=0. 0 IF(OINT.GE.LMAX.ANDX.GE.0.0 )Y=0. 0

Inth eCSM Pstatemen t Y=C0RR (LMIN,LMAX ,OINT ,X )

Where Y =outpu to fth ecorrecto r X =inpu to fth ecorrecto r OINT= outpu tintegrato r LMIN= minimu mo flimite r LMAX= maximu mo flimite r

268 Table A 6.1.2.1-a. Library of used CSMP III function blocks

CSMP III Statement Equivalent Mathematical Exprastion

INTEGRATOR y(t) - f xdt • ypj Y - INTCRLOC.X).

: «*"« IC • ylm where: t, - nan time

AJtenatrre "SpKÜlcukm' Form: 1« time

V - INTCW.OC,X,N) * • ),** • y(V

where: Y * output imy K « Initial condition amy Sauraient Laplace Transfer Function: X * inteiraad amy N * numbero f ekmantsI n me intenrator amy V(s) . 1 (N mostti ecode da sa litera lintege r constant)

DERIVATIVE y • dx

Y • D£IUV(]C,X) Equivalent LaplaceTransfe r Function: where: K - *• 1 V(.) . , *lt-t. TT»

1ST ORDER LAG (REAL POLE) p iy + y • x

Y • REALM.(IC ,P .X ) Equivalent Laplace Transfer Function: "In«: K - yt, _,

Y(s) - 1 TCsT "pTTT

DEAD TIME (DELAY) y • x(t-p) ; t>p

Y • DELAY (N. P,X ) y • 0 ; K p where: P • delay lime Equentant lapis» Transfer Function: N • amear of petals ••«»in m tour») > Omaner constant) and mm fee > 3. and •»•*.»• A" -

MODE-CONTROLLED INTEGRATOR

y • I x,dt • le ; i, XLaayx, Y • MOOWTOC.X1.X2 , XÎ) y • le ; x, < 0. x, >o

y - lestoute « ; x, < 0, x, <0

IMPLICIT FUNCTION

Y - BanOC.P.FOfY) y - f(y) wkerc: IC" flrstfecss ly- «MKplyl P* errorbound FOFY* outputnam efro mfina lstatemen t b algebraicloo pdefinitio n

STEP FUNCTION y-0 ;t

269 TableA 6.1.2.1-b .Librar yo fuse dCSM PII Ifunctio nblock s

III rniilwtinl Millmiwlhrt rmmwu m

ARBITRARY FUNCTIONGENERATO R (LINEAR INTERPOLATION)

AFGEN (FUNCT, X) y * fi»

ARBITRARY FUNCTIONGENERATO R V (QUADRATIC INTERPOLATION)

^

NLFGEN (FUNCT,X ) y * «»)

LIMITER y - p, -*p,

y - * • P,

NOISE (RANDOMNUMBER )GENERATO R Uniform Distribution of Variabley WITHUNIFOR MDISTRIBUTIO N P

INPUT SWITCH RELAY

Y - INSW(X1,X2,X3) y = x, x,<0 x.>0

OUTPUT SWITCH x <0 Y1.Y2 - OUTSW(Xl,X2) y. • s.y. t y, - O.y, - x>0

FUNCTION SWITCH y "M x,<0 Y - FCNSW(X1,X2,X3,X4) y - ">; x,-0

y " *.; x,>0

270 The cost minimisation algorithm calculates the optimum machine speed as is explained in 5. using the implicit function statement of CSMP.

A 6.2.4.1. The subroutine MECEF for filter and discrete time simulation

The program of the subroutine in FORTRAN is

SUBROUTINE MECEF1 (GF,INITI»MEAN,WHAT,TINTLO ,DELT,TDT»TIME REAL INITI,MEAN TYO* TYD+DELT WI-ATSC= WKATSOWHAT ITEL =ITEL+1 IF (TIME .LT. TDT)MEAN = INITI IF CTYD .LT. TINTLO GOTC 9999 MEAN*

Inthi sprogra m GF isth eproportiona lfacto ro fth esmoothin gfilte r INITI isth einitia lvalu eo fth einpu tWHA T MEAN isth eoutpu to fth efilte r WHAT isth einpu tgive nfo reac hsimulatio nste p TINTLOi sth esampl einterva l (TD) DELT isth etim einterva l (=simulationstep )o fCSM P TDT isth einitia lperio d TIME isth ecurren tsimulatio ntim e Theoutpu ti si nthi swa yINIT Ifo rth efirs tTD Tsecond san dafte rtha t MEAN,a valu econstan tfo reac hTINTL Ointerval .

271 Summary

The design of agricultural machines is determined by the requirements of the user and the techniques available at the time.Th e user requires systems which enablehi m toear n areasonabl e income.A contribution to this can be madeb y maximising thedifferenc e between the returns and the costs incurred in obtaining these returns.Th e technical skills are continually being improved on,an d offer newpossibilitie s for optimisation of methods ofproductio n so that the last-named are constantly being modified. Thene wpossibilitie s thusoffere db y electronics and automation should alsob e exploited by the agricultural industry.Th e aim of the present study is to indicate themetho d for the development and application of automation of agricultural machinery. Themetho d isworke d out in detail for the automatic control of the forward speed and threshing cylinder rotation speed of a combine harvester, a highly complexpiec e of machinery that cuts, threshes,separate s the threshed grain from the straw and then stores and transports them. The accento f the study is laido n themetho d for developing automation systemswhic h implicitly calculate the economic benefits expected from the said systems.Th emetho d used will be worked out stepwisebelow .

Study of literature showed thatvariou s automatic control systems for combineharvester s havebee n developed and tested,wit h the aim of keeping thegrai n loss and/or the straw feed rate (the amount of crops going into themachin e per unittime ) constant invie w of the varying crop density on the field and differing cropproperties .Th e level atwhic h feed rate or lossha s tob e setwa s considered as arising fromharves t optimisation studies. In these studies,model s are used inwhic h juston e equation is used for the relationship between loss and feed rate.Automati c losscon ­ trol,however ,i s capable of adapting to the change in this relationship so that thisha s tob e taken into consideration in the control system.

273 Inno tmor e than 2 caseswa s the costbenefi t calculated that arises outo f the automation of combine harvesters. In these'calculations;how ­ ever,th eassumptio n ofon e loss-to-feed rate relationship,referre d to abovewa s incorporated. Moreover,th e calculations werebase d on control systems inwhic h the lossmeasurin g systems were inaccurateall ,o f which makes itdifficul t to assess the results at their truevalue .

IIWhethe r iti sworthwhil e developing and applying more accurate lossmea ­ suring devices orothe r control systemswil l depend on the economic benefit, whichmake s itnecessar y to find outwha t these benefits are likely tobe . Itwa s therefore decided todesig n other control systems than those in the literaturewit h the aimo fobtainin g themaximu m economic benefit and adapting to thevaryin g relationship between loss and straw feedrate . The calculation of thebenefi t accuring from these systems was carried outb y means of computer simulation,tha ti st o say,copyin g the real course of the combine in the fieldwit h the aid of the computer.Thi s enabled us toprocee d as if good lossmeasurin g systemswer e tohan d and to compare control systems whichhav e noteve n been made yet. Inaddition , every system canb e tested under the samevariation s in conditions and thus thebenefit s correctly compared.

IllTh e nextphas e was thedevelopmen t of a criterion to serve as a guideline or as a target forcontro l of the forward speed and threshing cylinder rotation speed. By assuming that the maximum harvestable amount of grain isknow nwhe n the crop isrip e enough for combineharveste r operation, the losses incurred as the result ofmakin g changes inmachin e (forward) speed and threshing cylinder rotation speed, couldb e taken as costs and themaximisatio n of returns converted into termso f costminimisation . Then themai n cost factors of the grain harvestwer e expressed as functions of machine speed and threshing cylinder speed. The cost factorswer e:

1)machin e costsproportiona l to the harvested area; 2)machin e and labour costsproportiona l totime ; 3) fixedmachin e costs for theharves t season; 4) the grain losses incurred in the combine harvester; 5) the timeliness losses arising outo f the inability toharves t in one operation at thebes t time,an d

274 6) theextr a wear ofth ethreshin g cylinder drive caused byth eautomati c control. By putting thecos t factors together itcoul db eshow n that therear e optimum values formachin e andthreshin g cylinder speeds. Moreover,th e way inwhic h these values aredependen to nth ecro p properties became evident,i nparticula r crop density inth efiel d andothe r crop properties affecting thethreshin g andseparatio n processes inth emachine .

In order todescrib e thecos t functions accurately, thesubcondition s had tob edefine d with respect toth especifi c conditions under which the machine isused . Thenumbe r ofpossibilitie s were bundled together soa st oresul ti na numbe r determined byth efollowin g choices: 1) Choice of the fixed area to be harvested per season per machine The choice fello n10 0h ao fgrai npe rcombin e harvester peryea ri n the case ofa singl e farmero rsmal l group offarmer s ando n17 5h a per machine onth elarge-scal e farm specialised ingrai n harvesting, such asth eIJsselmeerpolder s Development Authority (IJ.D.A.) 2) Weather risk choice If theare a tob eharveste d isfixed ,th ecost s aremainl y determined by thetimelines s losses which differ greatly from year toyear .I n the present study these losses arecalculate d onth ebasi so fdata , taken from theliterature ,o nworkabl e hours ingrai n harvesting over a large number ofyears . Whenw econside r theworkabl e hours in9ou t of the1 2year s available, they willb efoun d tob emor e than in1 0 outo fth e12 .However , there isa smalle r chance that such a number will infac tb eavailable . Insuc h a casew espea k ofa greate r weather risk. With these data anda develope d formula which indicatesth e increase inlos s thelate r theharves t takes place,th etimelines s losses canb ecalculate d asa function ofth emachin e speed. Forth e present study there aretw ocurve s which have been calculated asstate d above. 3) Planning terms On theassumptio n ofa fixed harvesting period, ahighe r machine speed means that alarge r area canb eharveste d perseason . Machine costs per hectare arethu s reduced. There isals o a saving ifmor e canb e harvested perseaso npe rmachine . This must therefore beplanne do n the long term.Th eshor t term planning hasbee n discussed in1 )an d2 ) above. 275 IVA sha sbecom e evident from the foregoing, a large number of simplifications have tob e carried out in order tomak e the complexproble m capable of solution.Th e following oneshav ebee n made for simulation purposes. As regards the control systems we took asou r startingpoin t the assump­ tion that themai n disturbances that affect theproces s are variations in theaverag e values and that,t obegi nwith ,th e systems canb e consi­ dered asquas i static.Moreover ,th eproces sparameter s during control of the machine in the field are unknown and therefore have tob e estimated. That isdon e in the simulation using simple models and simplified methods of estimation. We have restricted the large number ofpossibl e control systems to 5, one or other ofwhic h usesmor e measuring signals or controls more varia­ bles. The controlled systems are: System 0:Manua l control:th e speeds are chosen by the driver on the basis of his experience and customary observation in the field. System 1:Los s control:machin e speed is controlled on thebasi s ofmea ­ sured loss; threshing cylinder speed is controlled by the driver. System 2:Loss-fee d rate control:machin e speed iscontrolle d on the basis of measured loss and straw feed rate.Threshin g cylinder speed iscontrolle d by the driver. System 3:Loss-fee d rate-threshingcylinde r speed control:a threshing cylinder speed control isadde d to system 2,whic h controls the speed on the basis of the measured straw feed rate. System 4:Loss-fee d rate-threshing efficiency control.A control is added to system 3whic h sets the average threshing cylinder speed of rotation on thebasi s of information on the measured grain sepa­ ration efficiency in the threshing cylinder.

V The development of the above stated control systemsha sbee n based on a large number of tests and measurements carried out in the field, inwhic h the cropproperties ,o r theproces s disturbances as they are called in control terminology, are established. The purpose of the control systems is,o f course, that the reaction to the disturbances is such that the costs are reduced toa minimum . This comes aboutbecaus e the optimum speed is cal­ culated anewever y time and isadjuste d to thatvalu eb y a feedback control system.Th e opportunities are restrictedbecaus e the disturbances cannot be measured accurately while the combineharveste r isworkin g (signal- noise ratio ispoor ) and alsobecaus e the effect of the control on the orocess can onlyb e measured after a certain delay.

276 The effect of the control system on the costswil l depend on the nature and volume of the disturbances towhic h the system reacts.A random sample of croppropert y variation was taken and recorded duringpractica l tests with acombin e harvester. At the same time themachin e speed chosenb y the driverwa s also recorded, thusprovidin g a record of themanuall y control­ led situation. These datawer e used as inputdat a for the simulations.

VI Comparison of the contributions of the various control systems to the minimisation of the costs was then calculated by computer simulation. The following stepswer e taken for simulationpurposes : 1)Th e systemboundar y was defined on thebasi s of thepurpos e of themodel . 2)The n amode l wasmad e of the combine harvester process on thebasi s of physical laws and measurements. Usewa smad e of data given in litera­ ture, laboratory research and extensive measurements in the field.De ­ tailed information on these measurements is available in the appendix. 3)Model swer e alsomad e for control of themachin e speed and threshing cylinder rotation speed aswel l as for themeasurin g systems needed in the control systems. 4)A computerprogra m written in CSMP III,a simulation language fordyna ­ micprocesse s on digital computer,wa smad e of thesemodel s and the controlsystems . 5)Simulation s were then carried out to check themodel s and to ensure that the control systemswer e correctly set. 6) Finally the combine harvesting costswer e calculated depending on the various controls and cost situations.

VII The simulations have led to the following conclusions: 1)Th e chosen speeds of the manually controlled IJ.D.A. machine were very close to those atwhic hminimu m costswer e found.Th eminimu m cost area is, moreover,ver ywide . 2)Th e reduction in costsb y means of automatic control is slight and, under the above mentioned conditions,les s than the cost reduction arising out of âmachin e design improvement leading to a 5% increase in speed at the same losslevel . The benefit is greater if the curve of the timeliness losses at lowerweathe r risk isapplie d in the control.Th e speed atwhic h minimum costs occur is then much higher namely, than that in themanuall y control-

277 led situation. Moreover, the range of speeds atwhic h low costs are obtained, ismuc h narrower.Thi smean s that the timeliness lossespla y an importantpar t and that the adjustment ofmachin e speeds to the expected timeliness losses,fo r instance as the result of changes in theweathe r during the harvesting process is important for minimisation of costs. 3)Controllin g tomee t rapidly varying crop density valuesha s not been found to lead to cost reductions.Th e main savings in costs are obtained by adjusting to the slowly varying croppropert y and crop density levels, which isver y evident from the fact that control system 4 (loss feed rate threshing efficiency control) and control system 1 (loss control) give the greatest reduction in costs.Contro l system 2 (feed rate-loss control) brings no reduction in costs,partl y as the resulto f the assumptions in the simulation. Control system 3 (loss-feed rate-cylinder speed control) even leads to a rise in costs.Here ,i nparticular , it ismad e clearho w important thepar t iso f the threshing cylinder speed in limiting machine losses andho w vital apar t isplaye d by timeliness losses inoptimisatio n of the grain harvest. 4)A reliable lossmeasurin g system isa necessar y condition in minimising costs. Present daymeasurin g systems are notaccurat e enough,whic h means that the development ofbette r systems is apressin g need. 5)Follo w up research is also required to find outwhethe r speedoptimi ­ sation could be carried outwit h the helpo f computers not inqorporated in the combineharveste r but installed elsewhere. Theprogram s in those computers can then include optimisation models inwhic h the accent lies on adjustment of the timeliness curve to the actual weather variations during theharves t period. It is expected that such systemswil l be introduced in the immediate future. Later on,system s canb e introduced into the machine,compri ­ sing a loss feed rate control system (system 2) inwhic h the loss to feed rate relationship is continuously estimated. Only when more measuring devices are available will automatic threshing speed control be developed.

278 Samenvatting

Optimalisering vanhe t gebruik vanmaaidorser s door automatische regeling van rijsnelheid en dorstrommelomtreksnelheid.

Hetontwer p van landbouwmachines wordtbepaal d door hetgeen de gebruiker nodig heeft en demogelijkhede n die de techniek op datmomen tbiedt . De gebruiker heeft systemen nodig diehe m in staat stellen een redelijk inkomen teverwerven .Ee nbijdrag e hiertoe ishe tmaximalisere n van het verschil tussen de opbrengst en de kosten die gemaaktmoete n worden voor het realiseren van de opbrengst. De technische mogelijkheden worden voort­ durend verruimd en bieden daardoor nieuwe kansen totoptimalisati e van de productiemethoden die daarom steedsworde n gewijzigd. Demogelijkhede n die de electronica en de automatisering thansbieden , dienen ook voor de landbouw teworde n benut. Indi tkade r heeft deze studie ten doel demethodie k aan te geven voor de ontwikkeling en de toepassing van automatisering bij landbouwwerktuigen. Demethodie k is in detail uitgewerktvoo r de automatische regeling van de rijsnelheid en de dorstrommelomtreksnelheid van eenmaaidorser . Dit is een complexwerktui g dathe t rijpe graanmaait ,dors t en hetge ­ dorste graan scheidt vanhe t stro,tijdelij k opslaat en transporteert. De nadruk van de studie ligto p de methodiek van de ontwikkeling van automatiseringssystemen, waarbij impliciet de te verwachten economische voordelen van de ontwikkelde systemen zullen worden berekend. Detoege ­ pastemethod e zalhieronde r stapsgewijs worden beschreven.

I)Ui tbestuderin g van de literatuurblee k date rdivers e automatische regelsystemen voor maaidorsers zijnontwikkel d en beproefd die de hoe­ veelheidpe r tijdseenheid ingevoerd gewas (devoeding ) constant pro­ beren tehouden . Ditword t gedaan door de rijsnelheid aan te passen aan de variaties in de gewasdichtheid ophe t veld, die echter zelf niet

279 gemetenkunne nworde n maar herleid worden uitd e meting van de voeding ergens voorin de machine.Oo k zijn systemenontwikkel d diemete n hoe­ veel graankorrels niet vanhe t gedorste stro gescheiden zijn en als z.g. schudderverlies methe t stro demachin e verlaten. Indi t geval wordt de rijsnelheid geregeld methe t doel het schudderverlies niet te groot te latenworde nomda the t verliespercentage meer dan evenredig toe­ neemtme t toenemende strovoeding en zeer sterk afhangt van variërende gewaseigenschappen zoalsbijvoorbeel d vochtgehalte,rijphei d enge ­ wassoort. Metbehul p van economische modellen isdoo r diverse onderzoekers berekendwa the toptimal e verliesniveau is.Di t isnie tbi j geen ver­ lies,wan t datka n alleen wordenbereik t door heel langzaam te rijden. Dit isnie t gewenstomda tda n teveelmachine snodi g zijn of de oogst te laatklaarkomt,waardoo r de zogenaamde tijdigheidsverliezen te zeer toenemen.Bi j aldez e studies gaatme n uitva n één relatie tussen de strovoeding enhe t verlies terwijl deze nu juiststeed s varieert. Hierdoor kan voor systemen,waarbij de rijsnelheid continuword taange ­ past aan de omstandigheden, van deze optimalisatie modellen geenge ­ bruik worden gemaakt. In tweepublicatie s is eenberekenin g gegeven vanhe t kostenvoor­ deel datbereik tka n worden met automatische snelheidsregeling op een maaidorser. Bij deze berekeningen waren echter regelaars gebruiktwaar ­ bij de verliesmeetsystemen nietnauwkeuri g waren zodathe t moeilijk isd e resultaten ophu n juistewaard e te schatten.

II)Hetza lva n deeconomisch e voordelen afhangen ofhe td emoeit e loont nauwkeurige meetsystemen en andere regelsystemen te gaan ontwikkelen en toepassen. Er moet dusworde n nagegaanwa t dehierme e te verwachten voordelen zullen zijn. Daarom werd besloten andere dan in de literatuur genoemde automatische regelsystemen te ontwerpen enhierme e debereke ­ ningen uit te voeren. De regelsystemen dienen teworde n ontworpen vanuit de doelstelling van economische opbrengstmaximalisati e en er dient daarbijwe l rekening teworde n gehouden met de steeds veranderende relatie tussen verlies en strovoeding.

Deberekenin g van het voordeel van deze systemen isuitgevoer d door middel van computer simulatie, d.w.z. nabootsen vanhe t echte verloop

280 vanhe t maaidorsen ophe t veld inberekeninge n met een computer. Op deze manier kan worden gedaan alsof er goede verliesmeetsystemen zijn enkunne n regelsystemen worden vergeleken die nog nietgemaak t zijn. Bovendien kan elk systeem onder dezelfde variatie in omstandigheden wordenbeproef d enkunne n de voordelen goed worden vergeleken.

III) Devolgend e fasewa s het uitwerken van een criterium als leidraad of wel als doelstelling voor de regelingva n de rijsnelheid en de dorstrom- melomtreksnelheid kon fungeren. Door ervan uit te gaan dat ten tijde van "maaidorsrijpheid" vanhe t gewas demaximaa l oogstbare hoeveelheid graan vastligt,konde n de verliezen,ontstaa n als gevolg van het ingrij­ pen in de rijsnelheid en dorstrommelomtreksnelheid, worden aangemerkt alskosten .Hierdoo r kon de opbrengstmaximalisati e worden omgevormd naarkoste n minimalisatie. Vervolgens zijn debelangrijkst e kosten­ factoren van de graanoogst uitgedrukt als functie van de rijsnelheid en dorstrommelsnelheid. Deze kostenfactoren waren: 1.machinekoste n die evenredig zijnme t de geoogste oppervlakte, 2. machine- en loonkosten die evenredig zijnme t de tijd, 3.machinekoste n die vast zijn voor het oogstseizoen, 4. de graanverliezen die ontstaan in demaaidorser , 5. de tijdigheidsverliezen die ontstaan doordat de oogstnie t in één keer ophe t optimale tijdstipka nworde n uitgevoerd en 6. deextr a slijtage in de aandrijving van de dorstrommel door de automatische regeling. Door deze kostenfactoren op te tellen kon worden aangetoond dat er optimale waarden voor de rijsnelheid en de dorstrommelomtreksnel­ heidbestaan . Bovendien werd duidelijk hoe deze waarden afhankelijk zijn van de gewaseigenschappen. Vooral de gewasdichtheid ophe t veld en die gewaseigenschappen die het dors- en scheidingsproces in demachin ebe ­ ïnvloeden zijn daarbij van belang.

Om de kostenfuncties nauwkeurig tebeschrijve n was het noodzakelijk nevenvoorwaarden te definiëren metbetrekkin g totd e specifieke omstan­ dighedenwaaronde r een machine wordt gebruikt. De veelheid van mogelijk­ hedenwer d gebundeld totee n aantal datbepaal d wordt door de volgende keuzes:

281 1) De keuze van de vaste oppervlakte die per seizoen per machine wordt geoogst. Gekozen isvoo r 100h agraa npe rmaaidorse rpe r jaar bijee nakkerbouwe r ofee ngroepj e akkerbouwers envoo r 175h ape rjaa r vooree nmaaidorse r vanhe tgrootlandbouwbedrij f dat gespecialiseerd isi nd egraanoogs t zoals de Rijksdienst voor deIJsselmeerpolder s (RIJP). 2) De keuze van het weerrisico Indien det eoogste n oppervlakte vast isworde n dekoste n vooral bepaald door detijdigheidsverliezen . Deze verschillen,als gevolg vanhe tweersverloop , sterk vanjaa r totjaar . Voor deze studie zijn deze verliezen berekend opbasi sva ngegeven s uitd eliteratuu r over werkbare ureni nd egraanoogs t vanee ngroo t aantal jaren. Wanneer we kijken naar dewerkbar e uren diei n9 va nd e1 2jaa r beschik­ baar zijn danzulle n date rmee r zijnda ni n1 0va nd e1 2jaar .E r is echteree nkleiner e kansda tdi eure noo kbeschikbaa r zullen komen.W espreke n danva nee ngrote r weerrisico.Me tdez e gegevens enee nontwikkeld e formule died etoenam e vanhe tverlie s aangeeft naarmate deoogs t later plaatsvindt,kunnend e tijdigheidsverliezen worden berekend alsfuncti e vand egekoze n rijsnelheid. Voor deze studie zijn twee curves gebruiktdi ebereken d zijn opbasi sva nd e beschikbare uren zoals hierboven isaangegeven . 3) De planningstermijn Alsme nuitgaa tva nee nvast e oogstperiode danbeteken tee ngroter e rijsnelheid date rpe rseizoe n eengroter e oppervlakte geoogstka n worden. Demachinekoste n perhectar e worden danlager .Di tlever t ook eenbesparin g opindie npe rseizoe n meerpe rmachin e geoogst gaat worden. Ditmoe t dano planger e termijn zogeplan d worden.D e korte termijnplanning isonde r punt 1e n2 beschreven .

IV) Zoals uithe tvoorgaand e reeds blijkt moet eengroo t aantal vereenvou­ digingen worden doorgevoerd omhe tcomplex e probleem oplosbaar temaken . Ten behoeve vand esimulati e zijn devolgend e vereenvoudigingen doorge­ voerd. Ten aanzienva nd eregelsysteme n werd ervan uitgegaan datd ebelang ­ rijkste storingen dieo phe tproce s inwerken variaties in gemiddelde waarden zijne nda td esysteme n vooreerst quasi-statisch mogen worden benaderd. Verder zijn deprocesparameter s tijdens hetregele n opd e machine inhe tvel d onbekend enzi jmoete n dusgescha t worden. Ind e 282 simulatie is dat gedaan meteenvoudig e modellen en vereenvoudigde schattingsmethoden. Het grote aantal mogelijke regelsystemen isdoo r onsbeperk t tot 5, waarvan elk ofwel meer meetsignalen gebruikt ofwe l meer variabelen regelt. Debestudeerd e systemen zijn: Systeem 0:Han d regeling: de snelheden zijn gekozen door de chauffeur op grond van zijn ervaring en gebruikelijke waarnemingen inhe t veld. Systeem 1:Verlie s regeling: de rijsnelheid wordt geregeld op basis van het gemeten verlies;d e dorstrommelsnelheidword tgere ­ geld door de chauffeur. Systeem 2:Verlies-voeding s regeling: de rijsnelheid wordt geregeld opbasi s vanhe t gemeten verlies en de strovoeding. De dors­ trommelsnelheid wordt geregeld door de chauffeur. Systeem 3:Verlies-voedings-dorstrommelsnelheid s regeling: aan systeem 2 isee n dorstrommelsnelheidsregeling toegevoegd die de snelheid regelt opbasi s van de gemeten strovoeding. Systeem 4:Verlies-voedings-mantelafscheidingsefficienti e regeling: aan systeem 3i see n regeling toegevoegd waarbij de gemid­ delde dorstrommelomtreksnelheidword t ingesteld aan de hand van informatie over de gemeten graanafscheidingsefficientie in de dorstrommel.

V) De ontwikkeling vanbovengenoemd e regelsystemen isuitgevoer d mede op basis van een groot aantalveldmetinge n waarin de variaties in de gewas­ eigenschappen, in regeltechnische termen de storingen op hetproce sge ­ noemd, zijn vastgelegd. Hetdoe l van de regelsystemen is immers dat zo op de storingen wordt gereageerd dat de kostenworde n geminimaliseerd. Ditword t gerealiseerd doordat de optimale snelheid telkens opnieuw wordtbereken d en zo goed mogelijk wordt ingesteld. De mogelijkheden daartoe zijn echterbeperk t omdat tijdenshe tmaaidorse n de storingen nietnauwkeuri g kunnen worden gemeten (designaal-rui sverhoudin g is slecht)maa r ook omdatpa sme t enige vertraging het effect van de ingreep van de regeling ophe tproce s gemeten kanworden .

De invloed van de regelsystemen op de kosten zalva n de aard en omvang van de storingenwaaro phe t systeem reageert afhangen. Een steek­ proef van variatie in gewaseigenschappen isgenome n en vastgelegd tij­ densmetinge n aan eenmaaidorse r in depraktijk . Tegelijkertijd isge ­ registreerd hoe grootd e door de chauffeur gekozen rijsnelheid was,zo -

283 dat isvastgeleg d watd e "handgeregelde" situatie was.Dez e gegevens zijngebruik t als ingangsgegevens voor de simulaties.

VI) De vergelijking van debijdrag e van de verschillende regelsystemen totkostenminimalisati e isvervolgen s door computer simulatie berekend. Tenbehoev e van de simulatie zijn de volgende stappen uitgevoerd: 1)Uitgaand e vanhe t doel vanhe tmode l isd e systeemgrens gedefinieerd. 2) Vervolgens isva nhe tproce s in demaaidorse r eenmode l gemaakt,ge ­ baseerd op natuurwetten enmetingen . Hierbij isgebrui k gemaakt van gegevens uitd e literatuur,va n laboratorium onderzoek en uitvoerige metingen in het veld. Hetproefschrif t geeft inbijlage n uitvoerige informatie over deze metingen. 3)Oo k werden modellen gemaakt voor debesturin g van de rijsnelheid en de dorstrommelomtreksnelheid,alsmed e van demeetsysteme n nodig voor de regelsystemen. 4) Van deze modellen en de regelsystemen werd een computerprogramma geschreven in CSMP,ee n simulatietaai voor dynamische processen op een digitale computer. 5) Vervolgens werden simulaties uitgevoerd om demodelle n te controleren en een goede instelling van de regelsystemen teverkrijgen . 6) Tenslotte werden dekoste n van hetmaaidorse n berekend in afhanke­ lijkheid van de verschillende regelsystemen en de verschillende kostensituaties.

VII) De simulaties hebben geleid totd e volgende conclusies: 1)D e gekozen snelheden van dehand-geregeld e machine van de RIJP lagen zeer dichtbi j de,snelhede nwaarbi j minimum kosten optreden. Hetgebie d van de rijsnelheden waar de kosten dichtbi jhe t minimum liggen isoverigen s zeer breed. 2) Dekostendalin g door automatische regeling isonde r dehierboven - genoemde omstandigheden gering enkleine r dan eenkostendalin g die ter vergelijking bijvoorbeeld tebereike n zou zijn door eenverbete ­ ring van de machine constructie die resulteert in een hogere rij­ snelheid van ongeveer 5%bi jhetzelfd e verliesniveau. Hetvoordee lword t groter indien de curve vand e tijdigheids- verliezen bijkleine r weerrisico wordt toegepast in de regeling. De snelheid waarbij minimum kosten optreden isda n namelijk veel hoger dan de snelheid bij dehan d geregelde situatie.Bovendie n ishe t

284 gebied van snelheden met lage kosten veel smaller. Ditbeteken t dat de tijdigheidsverliezen een belangrijke rol spelen en dat aanpassing van rijsnelheden aan een verandering in de verwachte tijdigheids­ verliezen,bijvoorbeel d ten gevolge vanweersveranderinge n tijdens de oogst,belangrij k is. 3)He t regelen op snel variërende gewasstanddichtheidswaarden blijkt geenkostendalin g te geven.D e belangrijkste kostenbesparing wordt verkregen door aanpassing aan de langzaam veranderende gewaseigen­ schappen en standdichtheidsniveaus. Ditblijk t duidelijk uithe t feit dat regelsysteem 4 (verlles-voedings-mantelafscheidingsefficientie regeling) en regelsysteem 1 (verliesregeling) de grootste kostendaling geven. Regelsysteem 2 (verlies voedingsregeling) geeft geen kosten­ daling en systeem 3 (verlies-voedings-trommelsnelheids regeling) geeft zelfsee n kostenstijging. Hierbij ishe tvoora l duidelijk geworden welke belangrijke rol het niveau van de dorstrommelsnelheid speelt in debeperkin g van de machineverliezen enwelk ebelangrijk e rol de tijdigheidsverliezen spelen in de optimalisatie van de graanoogst. 4)Ee nbetrouwbaa r verliesmeetsysteem isee n noodzakelijke voorwaarde voor kosten minimalisatie. Dehuidig e meetsystemen zijn niet voldoende nauwkeurig zodatd e ontwikkeling naar betere systemen dringendge ­ wenstis . 5)Vervolgonderzoe k is tevens gewenst om teonderzoeke n of snelheids­ optimalisatie zoukunne nplaat s vinden metbehul p van computers, die zichnie t op de maaidorser bevinden maarwaarbi j gebruik wordt gemaakt van eldersopgesteld e computers b.v. personal computers met optimalisatie programma's. Hierin kan dan de tijdigheidscurve worden aangepast aan het actuele weersverloop tijdens de oogstperiode. Te verwachten valtda t een dergelijk systeem heteers t zal kunnen worden toegepast enpa s later een systeem op de machine.He t systeem op de machine zalda n moetenbestaa n uitee n verlies-voedings regeling (systeem 2)me t continue schatting van de relatie tussen verlies en strovoeding. Pas later zal een dorstrommeltoerentalregeling kunnen worden geautomatiseerd omdatd e benodigde meetapparatuur nog veel onderzoek zalvereisen .

285 References

Anonymus, 1967.Groepsbeproevin g maaidorsers. ILRpublikati e 110, Wageningen. Anonymus,1969 .Th eutilizatio n andperformanc e ofcombin eharvesters . Farmmechanizatio n studies No. 18,Min .o fAgr .Fish , and Food;NAAS , Silsoe,U.K . Anonymus, 1973.Th eutilizatio n and performance of combine grain loss monitors. 1971-2Far mmechanizatio n studiesNo . 25,ADA S LiaisonUnit . Anonymus, 1975.Continuou s SystemModellin g Program III (CSMP III) Program reference manual,Progra m number 5734-XS9. International Business Machines Corporation. Anonymus, 1976.Merkenonderzoe k maaidorsers. IMAGpublikati e64 , Wageningen. Anonymus, 1979.Leidraa d kostprijsberekeningen 1979/1980,Stichtin g Bovalpers,Utrecht . Anonymus, 1981.Kwantitatiev e informatie 1981/1982.PAG V publikatie nummer 12,Lelystad . Audsley,E .& D,S ; Boyce,1974 .A metho d ofminimisin g the costo fhar ­ vesting and high temperature graindrying . J. Agric. Engng Res.19 , p. 173-189. Arnold,R.E. , 1964.Experiment s with raspba r threshingdrums .J .Agr . Engng Res.9 , p.99-131 . Artner, H-, 1971.Zu r Durchsatzregelung des Mähdreschers. D. Agrartechnik. 21, p. 172-173. Baader,W. , 1966.Durchsatz -un dVerlustmessun g imRahme nde rGebrauchs ­ wertprüfung vonMähdreschern .Landbauforschun gVölkenrod e 16,H 2 p. 93-98. Baader,W .e t al. 1969.Di e Entmischung eines Korngut-Fasergut-Hauf­ werkes auf einer vertikal schwingendenhorizontale nUnterlage .Grundl . der Landtechnik 5,p .149-157 . Baumgartner,G. , 1969.Anpassun g desMähdreschereinsatze s an Klimaver­ hältnisse und Ernterisiko.KTBL-Bericht eübe r Landtechnik. Heft125 . Bergman,O.C. , 1976.'D emeettechnisch e aspectenva n het maaidorsveldonder- zoek. Intern rapport,vakgroe p Landbouwtechniek, Landbouwhogeschool, Wageningen. Bogdanova,L.I. ,1960 .Automatio n of SK-3 selfpropelle d combine harvester. NIAETranslatio n 262o fVestnik . selsk. nauki (5)p . 104-113. Bouman,A .& A .Cappon , 1971.Verliesindicato r opmaaidorsers .Landbouwme ­ chanisatie,p .217-219 . Boyce,D.S .& I.Rutherford , 1972.A deterministic combineharveste r cost model. J. Agric. Engng.Res . 17,p .261-270 . Boyce, B.H. et al., 1974. The separation characteristics of a combine harvester and a comparison of straw walker performance. J. Agric. Engng. Res. p. 77-84

287 Brizgis,L.J .e t al.,1980 .Automati c cylinder speed control forcombines . Trans.ASAE ,p . 1066-1071,1075 . Brouër,B.P .& J.R. Goss, 1970.Som e approaches to automatic feedrate control for self-propelled combine harvesters. ASAEpaper ,70-632 . Brown,W.T .& G.H . Vasey, 1967.Whea t harvester survey.Dept .Agr .Engng . W.R.I.C.Rpt .Universit y Melbourne,Australia . Bruyn,C.P.M .de ,1979 .Simulati e van enkele regeltechnische mogelijk­ heden terverbeterin g vanhe t maaidorsproces.Doctoraalscripti e meet-, regel- en systeemtechniek en landbouwwerktuigkunde, Landbouwhogeschool Wageningen. Caspers,L. , 1966.Eintxus s von Spaltweite,Spalt -un d Korbform aufde n Dresehvorgang. Grundl.Landtechnik . 16 p.220-228. . Caspers,L. , 1973.Di e Abscheidungsfunktion als Beitrag zur Theorie des Schlagleistendreschwerks.Landbauforschun gVölkenrode.Sonderhef t 19. Claesson,S .e t al., Skördetröskning .Meddeland e nr.344 .Jordbrukste - kniska institutet,Sweden . Cool, J.C.e t al.,1979. Regeltechniek. Elsevier,Amsterdam/Brussel . Cooper, G.F., 1971.Cylinder/concav e performance from laboratory tests. ASAE paper, 71-625. Dongen,H.A.J.M .van , 1981a.Verliesmonitore n in depraktijk . Praktijk­ verslag,vakgroe p Landbouwtechniek, Landbouwhogeschool,Wageningen . Dongen,H.A.J.M .van , 1981b.Schattin gva n parameters inhe t CSMP model van een maaidorser metveldqegevens . Doctoraalscriptie, vakgroep Landbouwtechniek, Landbouwhogeschool,Waaeninge n Donkersgoed, K. van, 1980.Ee n laboratoriumonderzoek naard e relatie van voedingsniveau, gewas en vochtgehalte opmantelafscheiding , schudder- afscheiding en schudderverliezen.Doctoraalscripti e Landbouwwerktuig­ kunde,vakgroe p Landbouwtechniek, Landbouwhogeschool,Wageningen. Dymnich,V.G. , 1956.Automati c control of grain combine harvesters. NIAE Translation 137 ofMekh .Elektrif .Sots .sel . Khoz., (4),p .23-26 . Eimer,M. , 1966.Stan d der Regelungstechnik beim Mähdrescher.Grundl . Landtechnik 16, p. 41-50.L Eimer,M ., 1970 . Entwicklungen von Regelungseinrichtungen amMähdrescher . Grundl. Landtechnik 20,p .137-140 . Eimer,M .1973a . Untersuchungen zur Durchsatzregelung amMähdrescher . Habilitationsschrift der Georg-August-Universität,Göttingen . Eimer,M.,1973b .Funktio n und Arbeitsqualität der drehzahlgeregelten Dresehtrommel. Grundl.Landtechni k 23,p .158-163 . Eimer,M. , 1973c.Monitor e zurÜberwachun g derFunktio n und Arbeitsquali­ tätvo nMähdreschern . Landtechnik,p .215 . Eimer,M. , 1974a.Automati c control ofcombin e threshingprocess .Pape r F-5, IFACSymp .Aut .contro l forAgr ^ Saskatoon,Canada . Eimer,M. , 1974b.Untersuchunge n zur Steigerungde r Productivetatvo n Mähdreschern durch den einsatz von Steuerun d Regelungseinrichtungen. Paper 74-111-105.CIG RSymposiu m 1974.Holland . Eimer,M. , 1977.Optimierun g der Arbeitsqualität des Schlagleistendresch­ werks.Grundlage nde r Landtechnik, p. 12-17. Eykhoff,O. , 1977.Syste m identification. JohnWile y & Sons,London . Fedosejev,P.N.e t al.,1969 .Relatio n between grainmoistur e content and quality of thewor k of the SK4 combine harvester. Tractory. i selchosmasiny 9, p.27-29 . Feiffer,R .e t al.,1964 .Di e Impulssteuerung desVorschube s -ein eMög ­ lichkeitdurchgreifende r Verlustsenkung anTromme lun d Schüttler. Deutsche Agrartechnik 14 p.257-261. Feiffer,R ., 1967 .Elektronisch e Verlustkontrolle am Mähdrescher Deutsche Agrartechnik p.296-298.

288 Fekete,A .e tal.,1981 .Developmen tan dtes to fcombin efeedrat econtro l unit.Mezôgazdasâg igépesités itanulmânyok ,Gôdôllo . Feltz,G.C .va nder ,1979 .Ee nlaboratoriumonderzoe k naard einvloe dva n vochtgehalte,voeding ,rijphei de ngewa so pmantel -e nschudderafschei - ding.Doctoraalscripti eLandbouwwerktuigkunde ,vakgroe pLandbouwtech ­ niek,Landbouwhogeschool ,Wageningen . Filatov,N.V. ,1967 .Verstärkun gde rKörnerabscheidun gau fHorden-Stroh ­ schüttlern.Landtechnisch eForschun g6 ,p .196-200 . Fokkens,B .& M .Puylaert ,1981 .A linea rprogrammin gmode lfo rdail y harvestingoperation sa tth elarge-scal egrai nfar mo fth eIJssel - meerpoldersdevelopmen tauthority .J .Opl .Res .Soc .V 32, p. 535-547. Fokkens,B. ,K .v.d .Linde n& G .Velthuis ,1983 .Persona lcommunication . Friesen,O.H .e tal.,1965 .Automati c feedratecontro lo fcombines .ASA E Paper 65-167. Gasparetto,E .e tal.,197 7.Ultr ahig hspee dmovi eobservatio no fa conventionalthreshin gmechanis m (cylinder-concave-rearbeater )wor ­ kingo nwheat .Proceeding sgrai nan dforag eharvestin gconference . Ames,Iowa ,USA ,ASA EPublicatio n 1-78 ,p .104-111 . Gelder,J .van ,1975 .Schudderafscheidin ge nverlieze ni nee nmaaidorser . DoctoraalscriptieLandbouwwerktuigkunde ,vakgroe pLandbouwtechniek , LandbouwhogeschoolWageningen . Glaser,F. , 1976.Korn-Stroh-Trennun gunte rbesondere rBerücksichtigun g einesumlaufende nSiebbandschüttlers .Forschungsberich tAgrartechni k derMa xEyth-Gesellschaf t13 ,München . Goss,J.R .e tal. ,1958 .Performanc echaracteristic so fth egrain-combin e inbarley .Agr .Engng . 11,p .697-702 . Goss,J.R .e tal ,1965 .Automati c feedcontro lfo ra sel fpropelle dcom ­ bine.ASA Epaper ,65-168 . Graeber,E. ,1974 .Wirtschaftlich eun dtechnisch eAspekt ede rKornverlust ­ erfassunga mMähdrescher .Grundl .Landtechni k (1),p .15-17 . Groothuis,A. ,1979 .Invloe dva nvoedin ge nvoedingsschommelin go pd e korrelafscheidinge nd eschudderverlieze nbi jwintertarwe .Doctoraal ­ scriptieLandbouwwerktuigkunde ,vakgroe pLandbouwtechniek ,Landbouw ­ hogeschoolWageningen . Gubsch,M. ,1969 .De rEinflus zde rLängsneigun gde sMähdrescher sau fda s Abschiedungs-un dFörderverhalte nde sStrohschüttlers .Arch. .Landtechn . Bd8 .H2/3 ,p .127-139 . Guilacher,D.E .& L.G .Smith ,1979 .Grai nlos smonito rperformance .ASA E Paper,p .79-1579 . Gulyaev,G.A. , 1960.Investigatio no fa nautomati csyste mfo rth econtro l ofdru mloadin go ftracto rdraw ncombin eharvesters .NIA ETranslatio n 263o fTrud yVIM ,1960 ,p .189-213 . Gurarii,I.M. , 1964.Investigatin gth eautomati ccontro lsyste mo fcombin e harvesterloadin gb yanalo gcomputation .Problem yAvtomatvzatsi iS-Kh . ProizvodstvaKolo s287-304 . .Hagting,A. ,1976 .Managin glarge-scal eharvestin goperation so na grai n farmb ymean so fcomputerize doptimisatio nmodels .Pape rXVII Ith . InternationalCongres so fScientifi cWorkorganisatio ni nAgricultur e (Hungary). Harriott,P. , 1964.Proces scontrol .McGraw-Hil lBoo kCompany,Ne wYork . Heinrich,J. , 1968.Gleichmässig eDruschgutzuführun g zumDreschwer kal s Voraussetzung fürein eAutomatisierun gde rMähdrescherarbeit .Wiss . Zeitschriftde rHumboldt-Universitä tz uBerlin ,Math-Nat .R .XVII . Hijma,P. ,1970 .Ee nanalys eva ntarw ete nbehoev eva nhe tmaaidorsproces . DoctoraalscriptieLandbouwplantenteelt ,Landbouwhogeschoo lWageningen .

289 Himmelblau,D.M. , 1972.Applie dNon-linea rProgramming .Mc-Gra wHill . Hooper,A.W .& B .Ambler ,1979 .A combin eharveste rdischarg emeter . J.Agric .Engng .Res .24 ,p .1-10 . Huisman,W .e tal.,1974a .Automati cfeedrat econtro lo fa combin eharves ­ teri nwheat .Pape rIFA CSymposiu mo nAutomati ccontro lfo rAgriculture , Saskatoon,Canada . Huisman,W .e tal.,1974b .Automati cfeedrat econtro lo na combin ehar ­ vester.Pape r74-111-106 ,VI ICIG RConference ,Holland ,1974 . Huisman,W. ,1977 .Berekenin gva nd einvloe dva nd evariati ei nd evoedin g opd ecapacitei tva nhe tmaaidorsen .Intern enotitie ,Vakgroe pLand ­ bouwtechniek,Landbouwhogeschoo lWageningen . Huisman,W. ,1978 .Moistur econtent ,coefficien to ffrictio nan dmodulu s ofelasticit yo fstra wi nrelatio nt owalke rlosse si na combin e harvester.Proceeding so fth eFirs tinternationa lgrain -an dforage - conference.Ames ,Iowa ,USA ,ASA EPublicatio n1-78 ,p .49-54 . Huynh,V.M .e tal. ,1982 .Threshin gan dseparatin gproces s- a mathemati ­ calmodel .Trans ,o fth eASAE ,p .65-72 . Jansen,C.H.A. ,1972 .Maaidorsverlieze ni nd epraktijk .Praktijkverslag , VakgroepLandbouwtechniek ,Landbouwhogeschoo lWageningen . Jofinov,S.A .& V.U .Miroschnitschenko ,1967 .De rabgedrosselt eVer ­ dichtungsdruckde sMotor sal sRegelgröss ede rBeschickun geine s Getreidemähdreschers.Landtechnisch eForschun g 1,p .24-25 . Kampen,J.H .van ,1969 .Optimizin gharvestin goperation so na large - scalegrai nfarm .Rijksdiens tvoo rd eIJsselmeerpolders ,Zwolle , Holland. Kawamura,N .e tal. ,1972a .Automati cfeedrat econtro lfo rhydrostati c drivecombin eo fhea dfeedin gtyp e (1).Researc hrepor to nAgricultura l Machinery.LA MKyot oUniv .Japan ,No .4 ,p .55-70 . Kawamura,N .& M .Umeda ,1972b .Automati cfeedrat econtro lfo rhydrosta ­ ticdriv ecombin eo fhea dfeedin gtyp e (2). Researchrepor to nAgricul ­ turalMachinery ,LA MKyot oUniv. ,Japan ,No .5 ,p .1-10 . Kawamura,N .& K .Namikawa ,1974 .Automati cfeedrat econtro lo fhydrosta ­ ticdriv ecombin eo fhea dfeedin gtyp e- tw oinput scontro lsystem . PaperF-4 ,IFA CSymposiu mo nautomati cContro lfo rAgriculture ,Saska ­ toon,Canada . Kawamura,N .e tal. ,1975 .Automati cfeedrat econtro lo fcombin ei ntw o inputssyste man dit sadaptiv econtrol .Memoir so fth ecolleg eo f agriculture.Kyot oUniv. ,Japan ,No .107 ,1975 . Kawamura,T .e tal. ,1978 .Adaptiv efeedrat econtro lo fhea dfeedin gtyp e combine.Digita lsample dadaptiv econtro lsystem .Researc hrepor to n agriculturalmachinery ,1978 .Lab .o fAgr .Machinery ,Kyot oUniv. , Japan,p .68-96 . King,D.L .& A.W .Riddolls ,1960 .Damag et owhea tsee dan dpe asee di n threshing.J .Agric .Engng .Res. ,p .387-398 . Kirk,T.G .e tal ,1977 .Evaluatio no fa simulatio nmode lo fth ecombin e harvester.Proceeding sGrai nan dForag eHarvestin gConference ,Ames , Iowa,USA ,ASA EPublicatio n1-78 .p .134-138 . KleinHesselink ,J. , 1971.Ee nonderzoe knaa rmeetgroothede nvoo rd evoe ­ dingva nee nmaaidorser .Doctoraalscripti eLandbouwwerktuigkunde , vakgroepLandbouwtechniek ,Landbouwhogeschoo lWageningen . Klinner,W.E. ,1979 .Reducin gfiel dlosse si ngrai nharvestin goperations . TheAgricultura lEnginee r34 ,p .23-27 . Kroeze,G.H. ,1970 .Capaciteite ne nverlieze nbi jmaaidorsen .IL RRappor t 173,Wageningen . Kruse,J .e tal. ,1982 .Microprocessor-base d combinegroun dspee d controller.ASA Erepor t83-3040 .

290 Kühn,G. ,1970 .Zu rMessun gde rKörnerverlust ea mDreschwer kvo n Mähdreschern.Deutsch eAgrartechnik ,6 ,p .253-256 . Lange,J.M. , 1972.Exploitatiekoste nva nenkel elandbouwwerktuigen . ILRPublikati e164 . Lint,M.M .de , 1974.Glossar yo fterm suse d inth eIL RPapers .Paper so n Th.2 ,Sectio nV ,presente db yMAG ,Wageninge na tCIGR-Congres s23-2 7 sept.1974 . Lint,M.M .de ,1968 .D ecapacitei tva nmaaidorser si ntarwe .Landbouw ­ mechanisatie,p .537-542 . Loo,J .van ,1977 .A nautomati cfeedrat econtro lsyste mfo ra combin e harvester.Interna lPubl .Dept .o fAgr .Engineering ,Agr .Univ . Wageningen. Loorbach,G .& P.M .Rijk ,1972 .Ee nonderzoe kva nvoedin ge nverlieze n tijdensmaaidorsen .Doctoraalscripti eLandbouwwerktuigkunde ,vakgroe p Landbouwtechniek,Landbouwhogeschool ,Wageningen . Mailander,M.P .e tal. ,1979 .Compute rcontrolle dhydraulics .A combin e application.ASA EPaper ,79-1615 . Maler,J. , 1974.Regulatio no fth eoperatio nspee do fth eharvester - thresheraccordin gt oindicate d grainlosses .Zemed .Techn .2 0(6) , p.343-354 . McGechan,M.B .& C.A .Glasbey ,1982 .Benefit so fdifferen tforwar dspee d controlsystem sfo rcombin eharvesters .J . Agric.Engng .Res .27 , p.537-552 . Michajlov,M.W ., 1962 .Automati ccontro lo fgrai nfee di nth ethreshin g mechanismo fa combin eharveste r (Russ.).Westnyi kSelchos .Nauki , 7 (3),p .117-125 . Naaktgeboren,A. ,1976 .Landbouwkundige ,Regeltechnisch ee nErgonomisch e aspektenva nee nvoedingsregelin gvoo ree nmaaidorser ,werken donde r praktijkomstandigheden.Doctoraalscripti eLandbouwwerktuigkunde , vakgroepLandbouwtechniek ,Landbouwhogeschoo lWageningen . Nakhamkin,G.G .& M.V .Michajlov ,1960 .Automati ccontrolle ro floadin g fora combin eharvester .NIA ETransi .18 6o fTrakt .Sel'khozmash. , 30 (12),p .19-20 . Nakhamkin,G.G .& M.V .Michajlov ,1972 .Developin gautomati cgroun dspee d controlfo rsel fpropelle dcombines .Trakt .Sel'khozmash . (6),p .23-24 . Nakonetschny,I.I .& W.D .Schepowalow ,1967 .Automatische sRegel nde s Durchsatzesbe iErntemachinen .Deutsch eAgrartechni k 17,Hef t11 , p.522-524 . Nastenko,N.N .& I.M .Gurarii ,1959 .Automati ccontro lo fth edru mfee d ofth eSK- 3combin eharvester .NIA ETranslatio n16 3o fMekh .Elektrif . Sel.Khoz . (3),p .45-49 . Nyborg,E.O .e tal.,1968 .Grai ncombin elos scharacteristics .ASA EPape r 68-609. Oorschot,J.W.M ,van ,1979 .Technisc he neconomisc hvoordee lva nvoeding / verliesregelsystemen .Doctoraalscripti eLandbouwwerktuigkunde ,vak ­ groepLandbouwtechniek ,Landbouwhogeschoo lWageningen . Oosten,J.A .van ,1970 .Ee nman-machin e systeemi nd egraanoogst .Docto ­ raalscriptieLandbouwwerktuigkunde ,vakgroe pLandbouwtechniek ,Land ­ bouwhogeschoolWageningen . Oving,R.K .e tal. ,1980 .Overmechanisati eo fslagvaardighei dbi jd e graanoogsti nNederland .IMA Gpubl .143 ,Wageningen ,Th eNetherlands . Philips,P.R .& J.R .O'Callaghan ,1974 .Cerea lHarvestin g- A mathematica l model.J .Agric .Engng .Res .19 ,p.415-433 . Pickering,W.D. ,1974 .Compute rmodellin go fcombin eharveste rseparatio n dynamics.Interna lrepor tDivisio no fcontro lengineerin gUniv .o f Saskatoon,Canada . 291 Portiek,J.H. , 1975.Werkbar e uren voord e graanoogst,IMA G Publikatie 34. Portiek,J.H. , 1977.Workabl e time and theweather . IMAG Research Report 77-6. Reed,W.B .e t al-,1968 .Combin e harvester grain lossmonitor .ASA E Paper 68-607. Reed,W.B .& M.A .Grovum , 1969.Automati c forward speed control of com­ bines for optimum separation efficiency. Proc.o f theNat .Conf .o n automatic control, 1969.Nat .Researc h council,Univ . ofAlberta , Edmonton, Canada. Reed,W.B .e t al. 1970.A laboratory study of grain-straw separation. ASAE Paper no.70-604 . Reichel,H. , 1969.Ein eMöglichkei t zur automatischen Regelungde rFahr ­ geschwindigkeitvo n selbstfahrenden Landmachinen.Archiv , für Landtech­ nik 2/3,p .171-177 . Reumkens.F.J.H.A. . 1983.Vergelijkin g van veld- en modelgedrag van een maaidorser met strovoedingsregeling. Doctoraalscriptie Landbouwwerktuig- kunde,vakgroe p Landbouwtechniek,Landbouwhogeschoo l Wageningen. Rookmaker,D.P . &H.P . Kaper, 1967.Enkel e metingen terbepalin g van comfortwaardering inreizigersmateriaal .Rappor t 067/02, Nederlandse Spoorwegen,M W 4. Roloff,H . &W .Matek , 1972.Machinenelemente . Braunschweig, W.-Germany. Rumjantsev,J.K. , 1964.Automatio n of the process of control and regula­ tion ofdru m loading of the SK-4 combine harvester. Problemy Automatcii sel'kh.proisvodstra ,Moskou ,Kolo s305-312 . Schneller,J . et al,,1982.Combin e feed rate sensors.ASA E Paper82-1577 . Schrier,A.P. , 1982.Alco , Personal communication. Smook,R. , 1980.Ee n laboratoriumonderzoek naard e invloed van frequentie en niveau van de voedingsvariaties opmantelafscheiding , schudderaf- scheidinge n verliezen.Doctoraalscripti e Landbouwwerktuigkunde,vak ­ groep Landbouwtechniek, Landbouwhogeschool Wageningen. Snel, L., 1977 .Maaidorsveldonderzoe k 1976.Inter nversla g vakgroep Land­ bouwtechniek, Landbouwhogeschool Wageningen. Sonnenberg, H., 1970.Korn-Stroh-Trennun g mitDoppelkurbel-Horde nschutt ­ lern. Grundlagen der Landtechnik 6, p.161-166 . Souter,W.D. , 1967.Separatio n and conveying on the strawwalker s of the combine harvester.M.Sc . Thesis,Univ . ofMelbourne ,Australia . Sterren,J.J.E.M .va nde , 1983.Schudderverliesschattin gme tbehul p van monitoren onder de schudders van eenmaaidorser . Doctoraalscriptie Landbouwwerktuigkunde,vakgroe p Landbouwtechniek, Landbouwhogeschool Wageningen. Sytsma,H.D. , 1981.Dynamisc h gedrag vand e zaadafscheidingva nee nstro - schudder inee nmaaidorser .Doctoraalscripti e Landbouwwerktuigkunde, vakgroep Landbouwtechniek, Landbouwhogeschool Wageningen. Takahashi,Y . et al.,1972 .Contro l and dynamic systems.Addison-Wesle y publ. comp.Reading ,Massachussets . Theunissen,J.C.J. , 1979.Enig edynamisch e aspectenva n eenvoedingsver - liesregeling op eenmaaidorser .Doctoraalscripti e Landbouwwerktuig­ kunde,vakgroe p Landbouwtechniek, Landbouwhogeschool Wageningen. Trollope,J.R. , 1982.A mathematica l model of the threshing process in a conventional combine thresher.J . Agr.Engng .Res. ,p .119-130 . Verbruggen,H.B. , 1975.Digital e regelsystemen,dee l 4.Delfts e Univer­ sitaire Pers 1975. Vos, J. de, 1982.Persona l communication. Werkman, IJ., 1972.Regeltechnisch e enlandbouwkundig e aspecten van een voedingsregeling voor eenmaaidorser .Doctoraalscripti e Landbouwwerk­ tuigkunde, vakgroe p Landbouwtechniek,Landbouwhogeschoo l Wageningen.

292 Wevers, J., 1972.Ee nonderzoe k naar Verliesmodellen bijhe tmaaidorsen . Doctoraalscriptie Landbouwwerktuigkunde,vakgroe p Landbouwtechniek, Landbouwhogeschool Wageningen. Wieneke,F. , 1964.Da s Arbeitskennfeld des Schlagleistendreschers. Grundlagende r Landtechnik, 21,p . 33-34.

293 Curriculum vitae

Willem Huisman werd geboren op 23 juni 1944 teNieu w Buinen. Nahe tbehale n vanhe t diploma HBS-B in 1962aa nhe t UbboEmmiu s Lyceum te Stadskanaalbego n hij aan de studie in deElektrotechnie k aan de Technische Hogeschool teEindhoven . In 1963verwisseld e hij deze studie voor die aan de Landbouwhogeschool. In januari 1969wer d aldaar het ingenieursdiploma in deLandbouwwerktuigkund e behaald. Naast het hoofd­ vak landbouwwerktuigkunde omvatte de ingenieursstudie de vakkenwerk - tuigkunde en de industriële bedrijfskunde. Per 1februar i 1969 trad hij in dienst van de Landbouwhogeschool bij devakgroe p Landbouwtechniek, waar hij isbelas t methe t onderwijs in de oogsttechniek en deproducttechniek . Daarnaastwer d onderzoek verricht aan maaidorsers,waarva n een deel isverwerk t in ditproef ­ schrift.