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RISS 인기검색어
- 검색키워드
- 저자 : Bourek, Yacine (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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Study of Discharge in Point-Plane Air Interval Using Fuzzy Logic
Bourek, Yacine,Mokhnache, Leila,Nait Said, Nacereddine,Kattan, Rafik The Korean Institute of Electrical Engineers 2009 Journal of Electrical Engineering & Technology Vol.4 No.3
The objective of this paper is to study the discharge phenomenon for a point-plane air interval using an original fuzzy logic system. Firstly, a physical model based on streamer theory with consideration of the space charge fields due to electrons and positive ions is proposed. To test this model we have calculated the breakdown threshold voltage for a point-plane air interval. The same model is used to determine the discharge steps for different configurations as an inference data base. Secondly, using results obtained by the numerical simulation of the previous model, we have introduced the fuzzy logic technique to predict the breakdown threshold voltage of the same configurations used in the numerical model and make estimation on the insulating state of the air interval. From the comparison of obtained results, we can conclude that they are in accordance with the experimental ones obtained for breakdown discharges in different point-plane air gaps collected from the literature. The proposed study using fuzzy logic technique shows a good performance in the analysis of different discharge steps of the air interval.
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Study of Discharge in Point-Plane Air Interval Using Fuzzy Logic
Yacine Bourek,Leila Mokhnache,Nacereddine Nait Said,Rafik Kattan 대한전기학회 2009 Journal of Electrical Engineering & Technology Vol.4 No.3
The objective of this paper is to study the discharge phenomenon for a point-plane air interval using an original fuzzy logic system. Firstly, a physical model based on streamer theory with consideration of the space charge fields due to electrons and positive ions is proposed. To test this model we have calculated the breakdown threshold voltage for a point-plane air interval. The same model is used to determine the discharge steps for different configurations as an inference data base. Secondly, using results obtained by the numerical simulation of the previous model, we have introduced the fuzzy logic technique to predict the breakdown threshold voltage of the same configurations used in the numerical model and make estimation on the insulating state of the air interval. From the comparison of obtained results, we can conclude that they are in accordance with the experimental ones obtained for breakdown discharges in different point-plane air gaps collected from the literature. The proposed study using fuzzy logic technique shows a good performance in the analysis of different discharge steps of the air interval.
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Prediction of Flashover Voltage of High-Voltage Polluted Insulator Using Artifi cial Intelligence
Yacine Bourek,Nassima M’Ziou,Hani Benguesmia 한국전기전자재료학회 2018 Transactions on Electrical and Electronic Material Vol.19 No.1
The objective of this study is to predict the flashover voltage of a high-voltage insulator artificially contaminated usingartificial intelligence (AI). First, practical tests were performed on a high-voltage insulator to collect a database used in theimplementation of the artificial intelligence concept. These tests were realized for different levels of artificial pollution(saline distilled water). Each pollution level presented an amount of artificial pollution, in milliliters, in each petticoat(zone) of the insulator. The collecting database gives flashover voltage values corresponding to different amounts ofartificial pollution in each insulator zone and its conductivity. Second, we have introduced fuzzy logic (FL) and artificialneural networks (ANN) as two AI techniques to predict the flashover voltage of the high-voltage insulator and to estimatethe insulating state of artificial pollution. The proposed prediction concepts based on FL and ANN are implemented usingMATLAB’s graphical user interface. Finally, a comparison was made between the results obtained by AI and practicalones. The database used in this comparison is different from that used in concepts based on FL and ANN implementation. The obtained results show a high efficacy of FL and ANN techniques in predicting the flashover voltage of high-voltageinsulators compared with those obtained by practical tests.
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Belkebir Amel,Bourek Yacine,Benguesmia Hani 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.6
The paper proposes an adaptive neuro-fuzzy inference system called ANFIS for predicting the fl ashover voltage of external insulators. High voltage insulators were the subject of actual testing, which produced a database for the application of artifi cial intelligence ideas. The experiments were conducted using diff erent concentrations of synthetic pollution (distilled brine), with each concentration denoting the amount of contamination per milliliter of area. The database off ered fl ashover voltage values for various pollution levels and electrical conductivity levels in each isolation zone. Adaptive neuro-fuzzy inference employed a hybrid learning algorithm to determine suitable membership functions, minimizing the root mean square error as the performance criterion. The primary parameters aff ecting fl ashover voltage were identifi ed: applied high voltage, conductivity of the artifi cial impurity, and amount of impurity in the insulation. For both training and test data, precise predictions were obtained by using membership functions in the shape of a triangle with three fuzzy sets. During testing, the technique demonstrated a low mean absolute percentage error (0.027011) and a high coeffi cient of determination (0.999997049). Comparison with practical tests yielded a root mean square error of 0.0128623, confi rming the eff ectiveness of the Adaptive Neuro-Fuzzy Inference System in estimating the critical fl ashover voltage for newly designed insulators under diff erent operating conditions.
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