New Approach for Prediction the DC Breakdown Voltage Using Fuzzy Logic Controller Abdelghani Rouini, Nabil Derbel, Ahmed Hafaifa, Abdellah Kouzou
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New approach for prediction the DC breakdown voltage using fuzzy logic controller Abdelghani Rouini, Nabil Derbel, Ahmed Hafaifa, Abdellah Kouzou To cite this version: Abdelghani Rouini, Nabil Derbel, Ahmed Hafaifa, Abdellah Kouzou. New approach for prediction the DC breakdown voltage using fuzzy logic controller. Diagnostyka , Polish Society of Technical Diagnostics (PSTD), 2018, 19 (3), pp.55-62. 10.29354/diag/92294. hal-02144345 HAL Id: hal-02144345 https://hal.archives-ouvertes.fr/hal-02144345 Submitted on 30 May 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Article citation info: 55 Rouini A, Derbel N, Hafaifa A, Kouzou A. New approach for prediction the DC breakdown voltage using fuzzy logic controller. Diagnostyka. 2018;19(3):55-62. https://doi.org/10.29354/diag/92294 ISSN 1641-6414 DIAGNOSTYKA, 2018, Vol. 19, No. 3 e-ISSN 2449-5220 DOI: 10.29354/diag/92294 NEW APPROACH FOR PREDICTION THE DC BREAKDOWN VOLTAGE USING FUZZY LOGIC CONTROLLER Abdelghani ROUINI1, Nabil DERBEL2, Ahmed HAFAIFA1, Abdellah KOUZOU1 1Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa 17000 DZ, Algeria. e-mails: [email protected]; [email protected], [email protected] 2 Control and Energy Management Laboratory (CEM Lab), National Engineering School of Sfax University of Sfax, Tunisia, e-mail: [email protected] Abstract High voltage device design needs predicting the withstanding voltage to assay conditions as pulses, surges and the DC voltage. There is a great designer needed to have reliable design requirements and well- defined simulation procedure for the development of the apparatus. In this paper, Fuzzy Logic (FL) method is used to model breakdown voltage, based on experimental data generated in the laboratory. Different models are proposed with different membership functions for the FL under both DC voltage conditions. The purpose of this article is to investigate the discharge phenomenon for an air gap-point plan at with insulation barrier between themselves. Obtained results are encouraging. Proving that fuzzy logic is a powerful tool that can be used in predicting the properties of the barrier. Keywords: Fuzzy logic Controller, Number of partitions, Breakdown voltage, Barrier, Point-Plane. 1. INTRODUCTION In this paper, details of a proposed method for the prediction of electric discharge in air using Barriers are used in largely several high- fuzzy logic. voltage devices. It has been known that the The use of the fuzzy logic technique allows us dielectric of the strength of the long gap is to have a numerical system that can predict the significantly increased by inserting an insulating electric discharge using the fuzzy reasoning. barrier. Each insulating structure gives particular The difficulty of obtaining a mathematical discharge phenomenon [1-4]. model which can reflects the evolution of the Knowing the ionization state and the spread of electric discharge in the field of high voltage has electric discharge are of great importance to fully obliged several researchers to introduce different understand the mechanism behind the breakdown analysis and methods to study such a subject [35- [5-9]. 36]. In this work, to use the fuzzy logic technique The insertion of the barrier near the sharp based on experimental data to predict the electrical electrode has a great influence on the dielectric discharge in a point-to-plane system. strength [10-15]. The used database are collected from tests The effectiveness of the barrier depends on the conducted at the high-voltage laboratory of the geometry and position and the physical nature of University of Biskra. the barrier. The survey has been simulated and conducted experimentally and to study the barrier 2. EXPERIMENTAL SETUP breakdown phenomenon [16-22]. As a result, three materials have the same effect The experimental set-up consists of a high- on the barrier. The breakdown voltage varies with the size of the barrier, and the maximum flashover voltage test transformer 100kV/5kVA/ 50Hz, a voltages is observed where the barrier is positioned capacitive voltage divider. Fig 1 and Fig 2 (the at the closest point the electrode [23-31]. experiences have been performed in the laboratory The small size of barrier becomes effective in of high voltage University of Biskra). very small air spaces. Shows the arrangement of electrodes and Based experimental results, a Sugeno fuzzy insulating barrier it contains a point–plan electrode logic system is modelled to predict DC breakdown arrangement mounted vertical. The HV electrodes voltage, in terms of the relative position of the barrier, the hole, the width of the barrier, and the consist a steel needlepoint on copper of conical in nature of the barrier. In fact, the breakdown shape 30°. The grounded plan electrode is a phenomenon depends on this variable [32-34]. circular steel plate of 30 cm long, 2.8 cm diameter. 56 DIAGNOSTYKA, Vol. 19, No. 3 (2018) Rouini A, Derbel N, Hafaifa A, Kouzou A.: New approach for prediction the DC breakdown voltage using … The plexiglas barriers (휺풓=3.3), the second type of barrier used is bakelite (휺풓=5.82), and The third type of barrier used is Glass barriers (휺풓=6), are squares of different widths (5 cm, 10 cm, 15 cm) and different holes (4mm, 8mm and 12mm) and its thicknesses is 1mm, an aluminium plan grounded. Fig. 3. Fuzzy logic system To change the positions for several barriers, carriers Bakelite are used. Each input variable (R or W) is quantified into their fuzzy subsets: small S, medium M and large L. Memberships of these subsets have triangular shapes (Fig. 4 and 5). Fig. 1. Circuit probationary industrial realizes a frequency Fig. 4. Function of membership of the width W (cm) of the barrier Fig. 5. Function membership of the distance R (cm) Tab.1. Rule base of the fuzzy systems FLSkj W(mm) S M L R(cm) Fig. 2. View of real test cell S 푉 푉 푉 11 12 13 M The barrier is mounted vertically between the 푉21 푉22 푉23 L electrodes Fig 2. Its surfaces are checked after each 푉31 푉32 푉33 breakdown. The position of the barrier is defined by the ratio (a /d), where (a) is the point–barrier Where: Vij are values of the output of the fuzzy distance and dis the point–plan electrode gap. rules, for 휀푟 = 휀푘 and 퐻 = 퐻푗 The expression of the output of the value fuzzy 3. DESIGN OF A FUZZY SYSTEM FOR system is PREDICTION ∑ ( ) ( ) In this paper a hierarchical structure of Sugeno 휇푗 푅 훾푙 푊 푉푗푙 (푘푗) 푉퐶(푘푗) = (1) model was adopted to predict the breakdown ∑ 휇푗 (푅)훾푙(푊) voltage in terms of the relative position R and the Width of the barrier, for two values of relative Membership function as a function of distance: 푅−1 permittivity and the hole Fig. 3 (Fuzzy logic 3 − 푅 −( )2 휇 (푅) = max ( ,0 ) → 푒 휎 system). 1 2 푅−3 2 푅−1 5−푅 −( ) 휇2(푅) = max [ min ( , ( )) , 0 ] → 푒 휎 2 2 (2) 푅−5 푅 − 3 −( )2 휇 (푅) = max ( ,0 ) → 푒 휎 3 2 Membership function as a function of Width DIAGNOSTYKA, Vol. 19, No. 3 (2018) 57 Rouini A, Derbel N, Hafaifa A, Kouzou A.: New approach for prediction the DC breakdown voltage using … 푊−5 15 − 푊 −( )2 훾 (푊) = max ( ,0 ) → 푒 휎 1 10 푤−5 25−푤 훾 (푊) = max [ 0, min ( , ( )) ] → 2 10 10 푤−15 −( )2 푒 휎 (3) 푤−25 푤 − 15 −( )2 훾3(푊) = max (0, ) → 푒 휎 10 The relative permittivity 휀푟 has been quantified Fig. 7. Membership function of the hole H (mm) into two fuzzy values (3.3 and 6). The hole H has been quantified into two values Rule of inferences of the fuzzy system FLC (4mm and 12 mm). control: Their membership function are presented in Fig FLCi 1 ≤ 푖 ≤ ℎ 6 and 7). IF(R and S) and (W and M) so 푉퐶 = (R=1, W=15) ⟹ 푆 IF(R and S) and (W and H) so 푉퐶 = (R=1, W=25) ⟹ 푆 IF(R and S) and (W and S) so 푉퐶 = (R=3, W=5) ⟹ 푀 IF(R and S) and (W and S) so 푉퐶 = (R=3, W=15) ⟹ 푀 IF(R and S) and (W and t S) so 푉퐶 = (R=3, W=5) ⟹ 푀 IF(R and S) and (W and S) so 푉퐶 = (R=5, W=25) ⟹ 퐻 IF(R and S) and (W and S) so 푉퐶 = (R=5, W=15) ⟹ 퐻 IF(R and S) and (W and S) so 푉퐶 = (R=5, W=25) ⟹ 퐻 The whole fuzzy system can be presented by Fig 8. Tab. 2. Inference of the Sugeno Fig. 6. Membership function of the nature W of the barrier material S H M R S 푉퐶푚(1,5) 푉퐶푚(1,15) 푉퐶푚(1,25) H 푉퐶푚(3,5 푉퐶푚(3,15) 푉퐶푚(3,25) M 푉퐶푚(3,5) 푉퐶푚(3,15) 푉퐶푚(3,25) Fuzzy Controller (FLC) 휀푟 = 3.3 h=4 FLS11 푉11 W 휀 = 3.3 h=12 푟 푉 12 FLS12 Supervisor Fuzzy 푉21 휀푟 = 6 h=4 R FLS21 푉22 휀푟 = 6 h=12 FLS22 Fig. 8. Supervisor fuzzy 58 DIAGNOSTYKA, Vol.