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Determining Inter-Turn stator winding Fault Percent of Permanent Magnet Synchronous Motor Using Fuzzy Logic

Author(s): Mehran Taghipour | Mohammad Aali ShamsiNejad | Seyed Mohammad Razavi | Mohsen Farshad | Iraj Faraji | HassanGhahramani

Journal: Intelligent Systems in Electrical Engineering
ISSN 2251-6530

Volume: 2;
Issue: 2;
Start page: 2;
Date: 2011;
Original page

Keywords: Adaptive Neuro-Fuzzy Inference System (ANFIS) | Fuzzy logic | Inter-Turn stator winding Fault | Permanent Magnet Synchronous Motor (PMSM).

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.
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