Surface Texture Measurement on Complex Geometry Using Dual-Scan Positioning Strategy

applied sciences

Article Surface Texture Measurement on Complex Geometry Using Dual-Scan Positioning Strategy

Fang Cheng 1, Shaowei Fu 2,3,* and Ziran Chen 1

1 Engineering Research Center of Mechanical Testing Technology and Equipment (Ministry of Education), Chongqing Key Laboratory of Time Grating Sensing and Advanced Testing Technology, Chongqing University of Technology, Chongqing 400054, China; [email protected] (F.C.); [email protected] (Z.C.) 2 School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore 3 JM VisTec System Pte Ltd., Singapore 417942, Singapore * Correspondence: [email protected]

Received: 3 November 2020; Accepted: 24 November 2020; Published: 26 November 2020

Featured Application: This work is potentially applicable to in-line surface measurement. Integrated with robots or other manipulation devices, the proposed technology will be able to capture surface finishing parameters, including roughness and surface texture uniformity.

Abstract: In this paper, a surface measurement method based on dual-scan positioning strategy is presented to address the challenges of irregular surface patterns and complex geometries. A confocal sensor with an internal scanning mechanism was used in this study. By synchronizing the local scan, enabled by the internal actuator in the confocal sensor, and the global scans, enabled by external positioners, the developed system was able to perform noncontact line scan and area scan. Thus, this system was able to measure both surface roughness and surface uniformity. Unlike laboratory surface measurement equipment, the proposed system is reconfigurable for in situ measurement and able to scan free-form surfaces with a proper stand-off distance and approaching angle. For long-travel line scan, which is needed for rough surfaces, a surface form tracing algorithm was developed to ensure that the data were always captured within the sensing range of the confocal sensor. It was experimentally verified that in a scanning length of 100 mm, where the surface fluctuation in vertical direction is around 10 mm, the system was able to perform accurate surface measurement. For area scan, XY coordinates provided by the lateral positioning system and the Z coordinate captured by the confocal sensor were plotted into one coordinate system for 3D reconstruction. A coherence scanning interferometer and a confocal microscope were employed as the reference measurement systems to verify the performance of the proposed system in a scanning area of 1 mm by 1 mm. Experimental data showed that the proposed system was able to achieve comparable accuracy with laboratory systems. The measurement deviation was within 0.1 µm. Because line scan mechanisms are widely used in sensor design, the presented work can be generalized to expand the applications of line scan sensors.

Keywords: surface texture measurement; confocal sensing; surface form tracing; 3D reconstruction; roughness

1. Introduction An important tool for product quality assessment, surface texture measurements are traditionally performed based on laboratory systems, due to the high degree of measurement resolution required [1,2].

Appl. Sci. 2020, 10, 8418; doi:10.3390/app10238418 www.mdpi.com/journal/applsci Appl. Sci. 2020, 10, 8418 2 of 13

With the rapid development of advanced manufacturing technologies, such as five-axis machining and additive manufacturing (AM), new surface measurement solutions are needed to address the challenges of complex geometries and irregular surface patterns [3,4]. Stylus profilometry is widely used for conventionally machined samples [5]. Equipped with a coordinate measuring machine (CMM), the measurement space of stylus profilometry can be enlarged to accommodate samples of large volume and complicated geometry [6]. However, stylus profilometry is not an ideal solution for measuring surfaces with irregular patterns due to its contact measurement mechanism and flanking errors [7,8]. Another limitation of stylus profilometry is its low efficiency for areal surface texture measurement. Therefore, based on ISO 4287 [9], stylus profilometry is mainly used in line scan mode for conventionally machined surfaces with known directional surface patterns. 3D microscopy [10], such as confocal microscopy [11–13], coherence scanning interferometry [14,15] and focus variation microscopy [16,17], are suitable for area scans. 3D microscopic systems are able to determine surface roughness and surface isotropy based on ISO 25178-2 [18,19]. Using objectives with high numerical aperture (NA), 3D microscopic systems are able to achieve much higher lateral resolution compared with stylus profilometry. However, the vertical measurement range relies on mechanical scanning, which significantly limits measurement efficiency. In order to avoid mechanical movement, the concept of chromatic confocal microscopy (CCM) [20,21] has been developed in the past decade. However, for high-accuracy measurement, CCM’s sensing range is within a few hundreds of microns, which limits its application to free-form surface measurement. Furthermore, when measuring high-roughness surfaces, long scans are required to differentiate surface roughness from surface waviness and surface form [22]. Therefore, a large vertical measurement range is needed to cover surface fluctuations over a long scan range. Based on the above literature review and analysis, the motivation of this presented work is to develop an optical surface texture measurement system able to perform both line and area scans for challenging surfaces with complex geometry and irregular surface patterns. Unlike a laboratory solution, the proposed system has the potential to be utilized for in situ measurement [23,24].

2. Principle of Confocal Sensing with Internal Scanning A laser confocal sensor, Keyence LT9011 (KEYENCE, Osaka, Japan), was utilized for surface height measurement in this study. Figure1a shows the general principle of a single-point confocal sensor. Only when the measurement point is in focus will the detector receive the peak intensity of the reﬂected laser. Figure1b shows the working principle of the Keyence LT9011. The optics are driven by a tuning fork to generate high-frequency vibration, enabling vertical scanning. In the meantime, the focus position can be detected and height can be measured accordingly. The optics are also driven by an oscillating unit for lateral scanning, with a frame rate of 2.8 fps covering a scan length of 1.1 mm. This product was originally developed for height or thickness measurements. The vertical resolution of the LT9011 is 0.1 µm. The laser beam spot size is 2 µm with a scanning spacing of 2 µm, which complies with the requirements for surface roughness measurements based on ISO 4287 [9]. In this study, this sensor was further developed for surface texture measurement. Appl. Sci. 2020, 10, 8418 3 of 13 Appl.Appl. Sci.Sci. 20202020,, 1010,, xx FORFOR PEERPEER REVIEWREVIEW 33 ofof 1313

((aa)) ((bb))

FigureFigureFigure 1.1.1. PrinciplePrinciplePrinciple ofof of confocalconfocal confocal sensinsensin sensinggg withwith with internalinternal internal scanning:scanning: scanning: ((aa)) ( aprincipleprinciple) principle ofof confocal ofconfocal confocal sensor;sensor; sensor; ((bb)) (internalbinternal) internal scanningscanning scanning mechanism.mechanism. mechanism.

WithWithWith the thethe internal internalinternal scanning scanningscanning mechanism, mechanism,mechanism, this thisthis sensor sensorsensor is isis able ableable to toto measure measuremeasure surface surfacesurface roughness roughnessroughness subject subjectsubject to twototo twotwo conditions: conditions:conditions: (1)(1)(1) thethe surface surface is is relatively relatively ﬂat;flat;flat; thethe surfacesurface ﬂuctuationfluctuafluctuationtion doesdoesdoes notnotnot exceedexceedexceed thethethe sensingsensing rangerangerange ofofof 0.60.6 mm;mm; (2)(2)(2) thethe surfacesurface isis relativelyrelativelyrelatively smooth;smooth;smooth; thethethe measurementmeasuremenmeasurementt ofofof roughnessroughnessroughness parametersparameteparametersrs doesdoesdoes notnotnot requirerequirerequire aaa roughnessroughness evaluationevaluation lengthlength longerlonger thanthanthan 1.11.11.1 mm.mm.mm.

FigureFigureFigure2 2 2shows showsshows the thethe measured measuredmeasured surface surfacesurface proﬁle profileprofile of ofof a aa calibrated calibratedcalibrated roughness roughnessroughness master mastermaster (178–602, (178–602,(178–602, Mitutoyo MitutoyoMitutoyo Corporation,Corporation,Corporation, Kawasaki-shi, Kawasaki-shi,Kawasaki-shi, Japan) Japan)Japan) with withwith knownknown RaRa andand RtRt valuesvalues of of 2.97 2.97 µmµµmm and and 9.49.4 µm,µm,µm, respectively.respectively.

Figure 2. FigureFigure 2.2. LineLine scanscan forfor roughnessroughnessroughness measurement measuremmeasurementent using usingusing confocal confocalconfocal sensing. sensing.sensing. The arithmetical mean roughness (Ra) can be calculated using Equation (1), where N is the TheThe arithmeticalarithmetical meanmean roughnessroughness ((RaRa)) cancan bebe calculatedcalculated usingusing EquationEquation (1),(1), wherewhere NN isis thethe number of data points acquired in a measurement and Zi is the ith data point in height direction of the numbernumber ofof datadata pointspoints acquiredacquired inin aa measurementmeasurement andand ZZii isis thethe iithth datadata pointpoint inin heightheight directiondirection ofof roughness profile. The total height of roughness profile (Rt) is defined as the difference between the thethe roughnessroughness profile.profile. TheThe totaltotal heightheight ofof roughnessroughness profileprofile ((RtRt)) isis defineddefined asas thethe differencedifference betweenbetween largest profile peak height and the largest profile valley depth within the evaluation length [9]. thethe largestlargest profileprofile peakpeak heightheight andand thethe largestlargest profilprofilee valleyvalley depthdepth withinwithin thethe evaluationevaluation lengthlength [9].[9].

NN 11XN RZ== 1 . (1) RRZa aiai= Zi .. (1) (1) NNN i==1| | i=i 11

Therefore,Therefore, withwith ZZii valuesvalues capturedcaptured byby thethe confocalconfocal sesensornsor LT9011,LT9011, thethe surfacesurface roughnessroughness Therefore, with Zi values captured by the confocal sensor LT9011, the surface roughness parameter parameterparameter RaRa overover aa scanscan lengthlength ofof 1.11.1 mmmm cancan bebe calccalculated.ulated. ToTo verifyverify thethe measurementmeasurement capabilitycapability Ra over a scan length of 1.1 mm can be calculated. To verify the measurement capability of the ofof thethe laserlaser confocalconfocal sensorsensor LT9011,LT9011, measurementmeasurement resultsresults ofof thethe roughnessroughness mastermaster areare shownshown inin TableTable laser confocal sensor LT9011, measurement results of the roughness master are shown in Table1. 1.1. TheThe nominalnominal RaRa andand RtRt valuesvalues ofof thethe roughnessroughness mastermaster areare 2.2.9797 µmµm andand 9.409.40 µm,µm, respectively.respectively. TheThe The nominal Ra and Rt values of the roughness master are 2.97 µm and 9.40 µm, respectively. The mean meanmean errorerror andand standardstandard deviationdeviation areare 0.060.06 µmµm andand 0.040.04 µmµm forfor RaRa measurementsmeasurements andand 0.100.10 µmµm andand error and standard deviation are 0.06 µm and 0.04 µm for Ra measurements and 0.10 µm and 0.08 µm 0.080.08 µmµm forfor RtRt measurements.measurements. TheThe measurementmeasurement errorerror isis partiallypartially duedue toto shortshort samplingsampling length.length. for Rt measurements. The measurement error is partially due to short sampling length.

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Table 1. Roughness master measurement result (unit: µm). Table 1. Roughness master measurement result (unit: µm). 1 2 3 4 5 Mean Std. Dev. 1 2 3 4 5 Mean Std. Dev. Ra (µm) 3.02 3.02 3.10 3.00 3.01 3.03 0.04 Ra (µm) 3.02 3.02 3.10 3.00 3.01 3.03 0.04 Rt (µm) 9.51 9.43 9.67 9.46 9.48 9.50 0.08 Rt (µm) 9.51 9.43 9.67 9.46 9.48 9.50 0.08 3. 3D Surface Topography Measurement with Dual-Scan Scanning 3. 3D Surface Topography Measurement with Dual-Scan Scanning Integrated with an external motorized stage (PT1/M-Z8, Thorlabs Inc., Newton, NJ, USA), a 3D surfaceIntegrated topography with measurement an external motorized system was stage configu (PT1/red,M-Z8, as Thorlabsshown in Inc., Figure Newton, 3a. By NJ, synchronizing USA), a 3D surfacethe internal topography and external measurement scan, the 3D system surface was topo conﬁgured,graphy of as the shown measured in Figure area3 wasa. By reconstructed, synchronizing as theshown internal in Figure and external3b. The scanning scan, the area 3D surface was 1.1 topography mm by 1 mm, of thewith measured point spacing area wasand line reconstructed, spacing of as2 µm. shown The in total Figure measurement3b. The scanning time was area 250 was s. 1.1 mm by 1 mm, with point spacing and line spacing of 2 µm.The The motivation total measurement for developing time was 250this s.system was to address the challenge of measuring geometricallyThe motivation complicated for developing samples. this Instead system of was accommodating to address the challenge the sample of measuring into the measurement geometrically complicatedspace of a laboratory samples. Insteadsystem, of the accommodating measurement the sy samplestem was into designed the measurement to approach space the of asamples laboratory for system,adaptive the measurement. measurement system was designed to approach the samples for adaptive measurement.

(a) (b)

FigureFigure 3.3. 3D3D surfacesurface topographytopography measurementmeasurement basedbased onon confocalconfocal sensing:sensing: (a) systemsystem conﬁguration;configuration; ((bb)) 3D3D surfacesurface topography.topography. Based on the captured 3D surface topography, surface texture parameters were calculated Based on the captured 3D surface topography, surface texture parameters were calculated as as follows: follows: (1) height parameters Sa and Sq, for general understanding of the surface roughness; (1) height parameters Sa and Sq, for general understanding of the surface roughness; (2) statistic parameters Ssk and Sku, to evaluate the dominant feature of the surface, peak dominant (2) statistic parameters Ssk and Sku, to evaluate the dominant feature of the surface, peak dominant or valley dominant, as reference for further surface ﬁnishing process; or valley dominant, as reference for further surface finishing process; (3)(3) spatial parametersparameters Str Str and and Std, Std, to characterizeto characterize the uniformity the uniformity and analyze and analyze the directional the directional patterns patternsof the surface of the texture, surface iftexture, any. if any. SectionSection 5.15.1 willwill provideprovide thethe experimentalexperimental datadata toto verifyverify thethe measurementmeasurement performance.performance.

4.4. Surface Tracing StrategyStrategy forfor LongLong ScanScan LengthLength InIn orderorder to expand both both the the lateral lateral and and vertical vertical measurement measurement ranges ranges of of the the line line scan scan sensor, sensor, a adual-scan dual-scan surface surface tracing tracing algorithm algorithm was was developed developed in in this this study. study. For For rough rough surfaces, a long scanning lengthlength isis neededneeded toto separateseparate thethe informationinformation ofof roughness,roughness, wavinesswaviness andand form.form. Based on ISO 4288, µ forfor example, if if the the RaRa valuevalue is is greater greater than than 10 10 µm,m, the the cut-off cut-o lengthff length is recommended is recommended to be to 8 be mm, 8 mm, and andfive fivecut-offs cut-o areffs arerecommended recommended for foraveraging averaging computations. computations. The The entire entire scanning scanning length length would would be be40 40mm. mm. For For a free-form a free-form surface, surface, the the profile profile over over such such a asc scanan length length is is very very likely likely to to exceed the vertical Appl. Sci. 2020, 10, 8418 5 of 13 Appl. Sci. 2020, 10, x FOR PEER REVIEW 5 of 13 sensing range of a laser confocal sensor. In this study, therefore, a surface tracing control algorithm sensing range of a laser confocal sensor. In this study, therefore, a surface tracing control algorithm was developed to extend the vertical measurement range. was developed to extend the vertical measurement range. 4.1. Surface Tracing Algorithm 4.1. Surface Tracing Algorithm For high-resolution surface measurement, the confocal sensing range in the vertical direction is For high-resolution surface measurement, the confocal sensing range in the vertical direction is typically less than 1 mm. The Keyence LT9011 laser confocal sensor used in this study has a vertical typically less than 1 mm. The Keyence LT9011 laser confocal sensor used in this study has a vertical sensing range of 0.6 mm. When measuring rough surfaces with significant curvature, the measurement sensing range of 0.6 mm. When measuring rough surfaces with significant curvature, the is very likely to fail due to insufficient sensing range, as shown in Figure4a. In order to ensure surface measurement is very likely to fail due to insufficient sensing range, as shown in Figure 4a. In order information was always captured within the sensing range, an adaptive surface tracing algorithm to ensure surface information was always captured within the sensing range, an adaptive surface was developed. tracing algorithm was developed. The methodology is illustrated in Figure4b. The sensor moved in piece-wise mode. Each unit The methodology is illustrated in Figure 4b. The sensor moved in piece-wise mode. Each unit travel length was 1 mm. Since the oscillating unit inside the senor was able to generate a local scan travel length was 1 mm. Since the oscillating unit inside the senor was able to generate a local scan length of 1.1 mm, the scanning range of the neighboring scans had an overlapping section of 0.1 mm. length of 1.1 mm, the scanning range of the neighboring scans had an overlapping section of 0.1 mm. This overlapping section was used for profile reconstruction based on the best fitting algorithm [25]. This overlapping section was used for profile reconstruction based on the best fitting algorithm [25]. In this system, a vertical positioner (LS-110, Physik Instrumente GmbH & Co. KG, Karlsruhe, In this system, a vertical positioner (LS-110, Physik Instrumente GmbH & Co. KG, Karlsruhe, Germany) was used to position the sensor to ensure that at each lateral scanning location, the data Germany) was used to position the sensor to ensure that at each lateral scanning location, the data capture was within the sensing range. The positioner LS-110 was able to achieve a maximum speed capture was within the sensing range. The positioner LS-110 was able to achieve a maximum speed of 90 mm/s and a positioning resolution of 50 nm in a range of 26 mm. The actual speed needed in of 90 mm/s and a positioning resolution of 50 nm in a range of 26 mm. The actual speed needed in this study depends on the lateral movement speed and the height variation of the measured surface. this study depends on the lateral movement speed and the height variation of the measured surface. Since the lateral scanning speed generated by the internal positioner was 2 mm/s, this vertical positioner Since the lateral scanning speed generated by the internal positioner was 2mm/s, this vertical LS-110 had sufficient capability for most use cases. positioner LS-110 had sufficient capability for most use cases. At each location, the sensor LT9011 collected height information over a scan length of 1.1 mm. At each location, the sensor LT9011 collected height information over a scan length of 1.1 mm. With the lateral position information determined by the sampling spacing and sequence number, With the lateral position information determined by the sampling spacing and sequence number, a a second-order polynomial f (x) was obtained based on least-squares fitting. Then, the height to second-order polynomial was obtained based on least-squares fitting. Then, the height to position the sensor for the next scan was determined as position the sensor for the next scan was determined as 1 hj+1 ==+1 f 0,(xn) + f (xn). (2) hfxfx+ 2 () (). (2) jnn1 2 where f (x) is the first derivate of f (x), l is the lateral positioning increment and n is the number of where 0 is the first derivate of , is the lateral positioning increment and is the number data points acquired in l. In this study, l and n were set as 1.1 mm and 551, respectively. of data points acquired in . In this study, and were set as 1.1 mm and 551, respectively.

(a)

Figure 4. Cont. Appl. Sci. 2020, 10, 8418 6 of 13

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(b)

Figure 4. Surface tracing strategy to extend the measurement range: ( a) measurement out of sensingsensing range; (b)) surfacesurface tracing.tracing.

The vertical positioner positioner has has an an embedded embedded optical optical encoder encoder to record to record the theposition. position. Therefore, Therefore, the theheight height z i measured,j measured by by the the system system included included two two portions: portions: the the height height measured measured by by the the senor senor LT9011 LT9011 height , measured by the system included two portions: the height measured by the senor LT9011 and the height read fromfrom thethe opticaloptical encoder.encoder. Figure5 5aa showsshows thethe setupsetup forfor measuringmeasuring a a free-formfree-form surface. surface. TheThe samplesample waswas carriedcarried byby aa linearlinear stage (TSA100-B,(TSA100-B, Zolix Zolix Instruments Instruments Co., Co., Ltd., Ltd., Beijing, Beijing, China), China), the displacement the displacement of which of was which measured was bymeasured an in-house by an developed in-house developed image grating image system grating [26 sy,27stem]. Using [26,27]. this Using integrated this integrated system, the system, scanning the rangescanning can range be expanded can be expanded to 100 mm. to In100 this mm. study, In this at eachstudy, location, at each timelocation, taken time for positioningtaken for positioning and local scanand local was 1scan s. was 1 s. Figure5 5bb showsshows thethe scanningscanning result.result. TheThe verticalvertical measurementmeasurement rangerange cancan bebe expandedexpanded usingusing thethe proposed surfacesurface tracingtracing algorithm.algorithm.

(a)

(b)

Figure 5. Free-form surface measurement: ( a) system configuration; conﬁguration; (b) scan data.

4.2. Correction of Misalignment The misalignment of the internal and external scan needed to be calibrated. Instead of physically parallelizing the two moving axes, a pre-test on an optical flat (Figure 6a) was conducted to determine Appl. Sci. 2020, 10, 8418 7 of 13

4.2. Correction of Misalignment

Appl. Sci.The 2020 misalignment, 10, x FOR PEER of REVIEW the internal and external scan needed to be calibrated. Instead of physically7 of 13 parallelizing the two moving axes, a pre-test on an optical ﬂat (Figure6a) was conducted to determine thethe misalignment. With With the the data data collected collected from from all all sections sections plotted plotted into into one one coordinate coordinate system, system, the themeasured measured profile proﬁle is illustrated is illustrated in Figure in Figure 6b.6 b.

(a) (b)

Figure 6. ProfileProfile data misalignment illustration: ( a) optical flat;flat; (b) measured surfacesurface profile.profile.

Discontinuity betweenbetween neighboringneighboring sections sections can can be be corrected corrected by by introducing introducing a verticala vertical shift shift∆d ∆to compensateto compensate for for the the misalignment. misalignment. The The corrected corrected height height values values can can be be expressed expressed as as

 zz,==++ 0;  zi0,0 i,0zi,0 i,0 0;   ,  z zz==+Δz + ∆d d;;  i0,1 i,1i,1 i,1   , =+Δ  z0 zzi=,2zi,2 i,2+ 22;∆d d; (3)(3)  i,2     ......  ,  z0 ==+Δzi,m 1 + m∆d. i,mzzmdim,11−− i,1 m . − − wherewhere mm isis thethe numbernumber ofof datadata sections.sections. TheseThese equationsequations cancan bebe generalizedgeneralized asas

, =+⋅Δ zzzjd0 ij,,= z ij+ j ∆d.(4) (4) i,j i,j · where , is the height value captured by the LT9011 at the ith position in the jth section, and , is where zi,j is the height value captured by the LT9011 at the ith position in the jth section, and zi0,j is thethe valuevalue afterafter misalignmentmisalignment correction.correction. When the section length was set as 1.11.1 mmmm withwith aa samplingsampling spacing of 2 µµm,m, andand thethe externalexternal positioningpositioning interval was set as 1 mm, there waswas anan overlappingoverlapping ofof 0.1 mm with 50 sampling points between neighboring sections. 0.1 mm with 50 sampling points between neighboring sections. The least-squares principle can be applied to determine the value of ∆d. The optimal ∆d should The least-squares principle can be applied to determine the value of ∆. The optimal ∆ should minimize the residual sum of squares (RSS) of the deviation between the neighboring overlaps: minimize the residual sum of squares (RSS) of the deviation between the neighboring overlaps:

m 1 − n P−mnP1 2 RSS RSS= =−(z(); z0 ,,2 zz0 ) ;  i+(inNj+−(),,1n N),j − iji +,j+1 j=0ji==i00=0 − m 1 n P− P 2 = mn−1 [z + j ∆d z + (j + 1)∆d] ; i+(n N),j i,j 1 2 (5) j=+⋅Δ−−+Δ=0 i=0 − · − − [(1)];zjdzjdinNj+−(), ij ,1 + (5) mP1ji==00Pn = − [z z ∆d]2. − i+(n N),j i,j+1 j=0mni=1 0 − − − =−−Δ2 [].zzdinNj+−(),,1 ij + == where m, n and N represent the numberji00 of sections, the number of data points in each section and the numberwhere m of, n theand data N represent points in the each number overlap. of sections, In order the toobtain number the of minimum data points value in each of RSS section, ∆d andshould the complynumber withof the the data following points in condition: each overlap. In order to obtain the minimum value of RSS, ∆ should ∂RSS comply with the following condition: = 0. (6) ∂∆d ∂RSS With Equation (5) taken into Equation (6): = 0. (6) ∂Δd With Equation (5) taken into Equation (6):

mN−1 −−−Δ= 2( zzdinNj+−(),,1 ij + )0. (7) ji==00 Appl. Sci. 2020, 10, 8418 8 of 13

m 1 N X− X 2 (zi+(n N),j zi,j+1 ∆d) = 0. (7) − − − − Appl. Sci. 2020, 10, x FOR PEER REVIEW j=0 i=0 8 of 13

mXmN1−X1N Δ=− − − ∆d =dzzNm [ [((ziinNj+(+−(),,1n N),j ijz +i,j )]/[/(1)].+1)]/[N/(m 1)].(8) (8) ji==00 − − − j=0 i=0

4.3.4.3. ProﬁleProfile RestorationRestoration UsingUsing EquationsEquations (2) and(2) (6),and linear (6), misalignmentlinear misalignment can be well can compensated. be well compensated. However, misalignment However, couldmisalignment be eliminated could only be wheneliminated the linear only guide when had the perfect linear straightness guide had and perfect repeatability. straightness In practical and tests,repeatability. further compensation In practical tests, on the further residual compensa mismatchtion was on still the needed. residual Figure mismatch7 shows was the still concept needed. of compensatingFigure 7 shows the the residual concept mismatch, of compensating demonstrated the byresidual simulation mismatch, data.The demonstrated residual mismatches by simulation were compensateddata. The residual by adjusting mismatches every alternate were compensate data section.d Assumingby adjustingk is anevery odd number,alternate the data mismatches section. between the kth, (k 1)th and (k 1)th sections are Assuming k is an odd− number, the± mismatches between the kth, (k-1)th and (k ± 1)th sections are

 N N   1 P1 ,,  ∆d Δ==dzz0 −z z0 ;;  k kinNkikN i+(n+−(),1,N),k 1 − i,k   i=N0 i=0 − − −   N (9)(9)  1 P N  ∆dΔ=+ = 1 z ,, −z .  k dzz1 +++−N i0,k+1 i0+(n N),.k  kikinNk1,1(),i=0 −  N i=0 −

Then,Then, thethe furtherfurther correctedcorrected heightheight valuesvalues areare i ,,=+Δ+ , i Δ −Δ z00 zz= z0 + ∆d dk + (().∆d dk++ 1 ∆ ddk) .(10) (10) k kkk kNN k1 − k

FigureFigure 7.7. CompensationCompensation ofof residualresidual mismatch.mismatch.

Considering the redundant data in the overlapping area, in each adjusted section {z00 }, the first N Considering the redundant data in the overlapping area, in each adjusted section k{ }, the first data points and the last N data points were removed to connect with the neighboring sections. N data points and the last N data points were removed to connect with the neighboring sections. 4.4. Dual-Scan Positioning Control for Surface Profiling 4.4. Dual-Scan Positioning Control for Surface Profiling In the above sections, development of enabling technologies for surface profiling was discussed. In the above sections, development of enabling technologies for surface profiling was discussed. As a summary, in this section the algorithm of dual-scan positioning control and surface reconstruction As a summary, in this section the algorithm of dual-scan positioning control and surface is presented. reconstruction is presented. In practical measurements, if the surface is relatively flat, the system will scan the surface without In practical measurements, if the surface is relatively flat, the system will scan the surface vertical positioning control. Misalignment between the internal and external positioning was corrected, without vertical positioning control. Misalignment between the internal and external positioning was as discussed in Section 4.2, and residual mismatch was eliminated as discussed in Section 4.3. corrected, as discussed in Section 4.2, and residual mismatch was eliminated as discussed in Section For free-form surface measurements, the system followed the process shown in Figure8. 4.3. For free-form surface measurements, the system followed the process shown in Figure 8. Appl. Sci. 2020, 10, x FOR PEER REVIEW 9 of 13

Appl. Sci. 2020, 10, 8418 9 of 13 Figure 8. Surface measurement workflow.

Figure 8. Surface measurement workflow. With the surface tracing algorithm discussed in Section 4.1, the system was able to capture the surfaceWith data the by surface combining tracing the algorithm height information discussed captured in Section by 4.1 LT9011, the system and the was vertical able to positioner. capture the However,surface data since by the combining data captured the height in informationeach section capturedwere from by LT9011the internal and thescan vertical of the positioner. LT9011, misalignmentHowever, since between the data the captured internal in scan each sectionand external werefrom lateral the positioning internal scan was of thenot LT9011, considered. misalignment betweenWith thethe internal misalignment scan and correction external lateral algorithm positioning discussed was notin Sectionconsidered. 4.2, the non-parallelism betweenWith the the moving misalignment axes of internal correction scan algorithm and exte discussedrnal lateral in positioning Section 4.2, thecan non-parallelism be compensated. between After thisthe misalignment moving axes ofcorrection, internal the scan profile and external may still lateral show positioningmismatches canbetween be compensated. neighboring Aftersections. this Thismisalignment mainly is due correction, to the vertical the profile positioning may error still show and straightness mismatches of betweenthe lateral neighboring movement. sections. ThisWith mainly the is profile due to therestoration vertical positioningalgorithm errordiscussed and straightness in Section of4.3, the the lateral mismatches movement. between neighboringWith the sections profile restorationcan be compensated algorithm discussedby adjusting in Section data sections 4.3, the mismatcheswith even sequence between numbers. neighboring sections can be compensated by adjusting data sections with even sequence numbers.

5. Experimental Verification Experiments were conducted to verify the measurement performance of the proposed dual-scan scanning method. Because temperature-induced deformation of the measurement modules may affect measurement accuracy [28], the measurement tests were performed in an air-conditioned workshop, with temperature controlled at 20 2 C. The reference systems were also working in a laboratory with ± ◦ the temperature controlled at 20 1 C. In order to minimize the influence of temperature variation, ± ◦ the data capture processes were completed within 3 min. An area of 1 mm 1 mm on an additive manufacturing sample was scanned to verify the areal × measurement method as discussed in Section3. A line scan of 25 mm was conducted to verify the long-travel surface tracing strategy discussed in Section4.

5.1. Robotic Vibration Test Since the proposed systems were portable and reconfigurable, the proposed methodology has the potential to be utilized for in situ measurement [29]. Figure9 shows the robotic application. Vibration tests were conducted on a collaborative robot (UR5, Universal Robots, Odense, Denmark) to address the concern of measurement stability. The measurements were conducted at five different timings and repeated fifty times on the same spot at each timing. The test results (mean st. dev) are ± Appl. Sci. 2020, 10, 8418 10 of 13 presented in Table2. It can be concluded that robotic vibration in standby mode has minimum e ffects

Appl.forAppl. roughness Sci.Sci. 20202020,, 10, measurementx FOR PEER REVIEWREVIEW on the micron to sub-micron level. 1010 of of 13 13

Figure 9. Robotic setup for in situ measurement [25]. Figure 9. RoboticRobotic setup setup for for in in situ situ measurement measurement [25]. [25]. Table 2. Measurement results of robotic system vibration. TableTable 2. MeasurementMeasurement results of robotic system vibration. Timing No. 1 2 3 4 5 TimingTiming No. No. 1 1 2 33 44 55 Test Result (µm) 63.38 ± 0.02 63.33 ± 0.02 63.30 ± 0.01 63.13 ± 0.02 62.62 ± 0.03 TestTest Result Result (µm) (µm) 63.3863.38 ± 0.02 63.33 63.33 ± 0.02 63.30 ± 0.010.01 63.13 63.13 ±0.02 0.02 62.62 62.62 ±0.03 0.03 ± ± ± ± ± 5.2. Area Scan 5.2. Area Area Scan Scan An external positioner was installed with the moving axis perpendicular to the internal scan of the laserAn external confocal positionerpositioner sensor LT9011. waswas installed installedThe system with with was the the intr moving movioducedng axis axis in perpendicular Section perpendicular 3. As a to representative theto the internal internal scan surface scan of the of thelaserwith laser confocalirregular confocal sensorpatterns, sensor LT9011. anLT9011. additive The The system manufacturing system was was introduced intr (AM)oduced in sample Section in Section was3. As selected 3. a As representative a representativefor measurement. surface surface with A withirregularcoherence irregular patterns, scanning patterns, an microscope additive an additive manufacturing (Talysurf manufacturing CCI (AM) HD, AMETEK sample (AM) wassample Inc., selected Berwyn, was forselected PA, measurement. USA) for andmeasurement. a Aspinning- coherence A coherencescanningdisk confocal microscope scanning microscope microscope (Talysurf (Smartproof CCI (Talysurf HD, 5, AMETEK CCICarl HD,Zeis Inc., AMETEKs AG, Berwyn, Oberkochen, Inc., PA, Berwyn, USA) Germany) and PA, a spinning-diskUSA) were and used a spinning- confocalas the diskmicroscopereference confocal systems (Smartproof microscope for the 5, comparison Carl(Smartproof Zeiss AG, study. 5, Oberkochen, Carl The Zeis surfaces AG, Germany) topography Oberkochen, were of used the Germany) AM as the sample reference were measured used systems as by the for referencethedifferent comparison instrumentssystems study. for theis The shown comparison surface in Figure topography study. 10. It The ca ofn surface thebe observed AM topography sample that measured the of measurement the byAM di sampleﬀerent resultsinstruments measured showed by is differentshownconsistent in instruments Figure surface 10 patterns.. It is can shown be observed in Figure that 10. the It measurementcan be observed results that showed the measurement consistent surfaceresults patterns.showed consistent surface patterns.

(a) (b) (c) (a) (b) (c) Figure 10. SurfaceSurface topography topography measurement measurement of of an an additive additive manufacturing manufacturing (AM) (AM) sample: sample: (a) ( aby) by CCI; CCI; Figure(b) by Smartproof10. Surface 5; topography ( c)) by by the the prop proposedmeasurementosed system. system. of an additive manufacturing (AM) sample: (a) by CCI; (b) by Smartproof 5; (c) by the proposed system. For quantitative evaluation, evaluation, height height parameters parameters Sa, Sa, Sq Sq and and S10z, S10z, statistical statistical parameters parameters Ssk Ssk and and Sku, For and quantitative surface isotropy evaluation, parameters parameters height Str Strparameters and and St Stdd wereSa, were Sq employed employedand S10z, to tostatistical evaluate evaluate parametersthe the measurement measurement Ssk and Sku,performance.performance. and surface Comparison isotropy resultsparameters areare shownshown Str and inin Table TableStd 3were ,3, with with employed the the standard standard to deviationevaluate deviation the of of ﬁve measurementfive repeats repeats for performance.eachfor each measurement. measurement. Comparison results are shown in Table 3, with the standard deviation of five repeats for each measurement. Table 3. Measurement results of area scans.

Taylor HobsonTable 3. MeasurementCCI Carl Zeiss results Smartproof of area scans. 5 Proposed System Sa (µm) Taylor2.50 Hobson ± 0.10 CCI Carl Zeiss 2.42 ±Smartproof 0.13 5 Proposed 2.41 ± 0.12 System SaSq (µm) 3.262.50 ±± 0.160.10 3.09 2.42 ± ± 0.19 0.13 3.04 2.41 ± ±0.17 0.12 Sq (µm) 3.26 ± 0.16 3.09 ± 0.19 3.04 ± 0.17 Appl. Sci. 2020, 10, 8418 11 of 13

Table 3. Measurement results of area scans.

Taylor Hobson CCI Carl Zeiss Smartproof 5 Proposed System Sa (µm) 2.50 0.10 2.42 0.13 2.41 0.12 ± ± ± Sq (µm) 3.26 0.16 3.09 0.19 3.04 0.17 ± ± ± S10z (µm) 24.95 0.16 23.02 0.27 22.09 0.17 ± ± ± Ssk 0.18 0.01 0.14 0.01 0.17 0.02 − ± − ± − ± Sku 3.40 0.04 3.58 0.04 3.37 0.08 ± ± ± Str 0.19 0.01 0.21 0.00 0.18 0.02 ± ± ± Std ( ) 69.97 0.14 71.04 0.10 70.58 0.13 ◦ ± ± ±

5.3. Long-Travel Line Scan A free-form sample was fabricated to verify the long-travel measurement capability of the proposed dual-scan surface tracing system. The system setup is shown in Figure5a. Areas with different roughness were intentionally made on the sample surface. The surface roughness measurement results are shown in Table4, with a standard deviation of five repeats for each measurement. A stylus profilometer (Talysurf PGI 800, AMETEK Inc., Berwyn, PA, USA) was used as the reference system.

Table 4. Long-travel roughness measurement results.

PGI 800 Proposed System Absolute Error Relative Error Ra (µm) 0.56 0.01 0.58 0.02 0.02 3.6% Zone 1 ± ± Rq (µm) 0.69 0.01 0.72 0.03 0.03 4.3% ± ± Ra (µm) 0.93 0.02 0.97 0.05 0.04 4.3% Zone 2 ± ± Rq (µm) 1.14 0.02 1.19 0.07 0.05 4.4% ± ± Ra (µm) 1.36 0.01 1.42 0.04 0.06 4.4% Zone 3 ± ± Rq (µm) 1.70 0.01 1.78 0.06 0.08 4.7% ± ±

6. Conclusions and Future Work In this paper, surface texture measurement methodology based on a dual-scan scanning mechanism has been proposed for surface texture measurement. The motivation for this study was to address the challenges of measuring surfaces with geometric complexity and irregular surface pattern. By setting the internal and external scanning in perpendicular directions, the system was able to perform area measurements. Areal parameters to evaluate the surface quality were obtained, including height parameters Sa, Sq and S10z, statistic parameters Ssk and Sku, and surface isotropy parameters Str and Std. By setting the internal and external scanning in parallel directions, the system was able to perform line measurements over long travels. A misalignment compensation algorithm was developed to reduce the measurement error due to non-parallelism and straightness errors. Commercial 3D microscopes (Talysurf CCI and Zeiss Smartproof 5) and a tactile stylus profilometer (Talysurf PGI 800) were employed to evaluate the measurement performance of the proposed methodology. For area measurement in a range of 1 mm by 1 mm, and for line measurement in a scan length up to 100 mm, experimental results showed that the proposed systems were able to achieve comparable accuracy with the commercial systems. Future work will focus on further analyzing the effects of robotic vibration and environmental temperature variation and on developing advanced noise filtering and error compensation algorithms. In addition, the developed in situ measuring system will be fully integrated into a robotic polishing cell to conduct in situ measurements as a tool of quality verification. Appl. Sci. 2020, 10, 8418 12 of 13

Author Contributions: Conceptualization, F.C. and S.F.; methodology, F.C. and S.F.; software, S.F.; validation, S.F.; formal analysis, S.F.; investigation, S.F.; resources, F.C. and Z.C.; data curation, S.F.; writing—original draft preparation, F.C.; writing—review and editing, F.C. and S.F.; visualization, F.C. and S.F.; supervision, F.C.; project administration, F.C. and S.F.; funding acquisition, Z.C. All authors have read and agreed to the published version of the manuscript. Funding: This work was funded by the National Natural Science Foundation of China (Grant No. 51775075, 51935004). Conﬂicts of Interest: The authors declare no conﬂict of interest.

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