University of Isfahan Computational Intelligence in Electrical Engineering 2821-0689 2 2 2011 08 23 Determining Inter-Turn stator winding Fault Percent of Permanent Magnet Synchronous Motor Using Fuzzy Logic Determining Inter-Turn stator winding Fault Percent of Permanent Magnet Synchronous Motor Using Fuzzy Logic 12 24 15315 FA Mehran Taghipour Gorjikolaie Department of electrical engineering, Faculty of Engineering, University of Birjand, Birjand, Iran Mohammad Ali ShamsiNejad Department of electrical engineering, Faculty of Engineering, University of Birjand, Birjand, Iran Seyyed Mohammad Razavi Department of electrical engineering, Faculty of Engineering, University of Birjand, Birjand, Iran Mohsen Farshad Department of electrical engineering, Faculty of Engineering, University of Birjand, Birjand, Iran Iraj Faraji Department of electrical engineering, Faculty of Engineering, University of Birjand, Birjand, Iran Hassan Ghahramani Department of electrical engineering, Faculty of Engineering, University of Birjand, Birjand, Iran Journal Article 2016 06 14 Intelligent methods are widely used in fault detection and diagnosis in electrical machine, transformers and in general in all parts of industry. One of the most advanced methods in fault detection is fuzzy Inference system. Since, extraction of effective rules is so hard in complicated problems, using fuzzy Inference is impossible. In this paper, in order to determine the amount of inter-turn stator winding fault in Permanent Magnet Synchronous Motor (PMSM),the fuzzy logic set has been used. This research has been fulfilled in two steps. In first step, a mathematical model of PMSM under fault condition has been simulated in MATLAB/SIMULINK and required data; deferential current of each phase and speed of motor have been extracted, in second step, a fuzzy set has been created using Adaptive Neuro-Fuzzy Inference System (ANFIS) and this fuzzy set has been used in simulation for on-line test. Obtained results show that proposed method can follow fault in short time and can present amount of fault very precise.  Intelligent methods are widely used in fault detection and diagnosis in electrical machine, transformers and in general in all parts of industry. One of the most advanced methods in fault detection is fuzzy Inference system. Since, extraction of effective rules is so hard in complicated problems, using fuzzy Inference is impossible. In this paper, in order to determine the amount of inter-turn stator winding fault in Permanent Magnet Synchronous Motor (PMSM),the fuzzy logic set has been used. This research has been fulfilled in two steps. In first step, a mathematical model of PMSM under fault condition has been simulated in MATLAB/SIMULINK and required data; deferential current of each phase and speed of motor have been extracted, in second step, a fuzzy set has been created using Adaptive Neuro-Fuzzy Inference System (ANFIS) and this fuzzy set has been used in simulation for on-line test. Obtained results show that proposed method can follow fault in short time and can present amount of fault very precise.  https://isee.ui.ac.ir/article_15315_0c9418c37d5562469322fdadccb5b193.pdf