Title :
A review of Permanent Magnet Synchronous Motor fault diagnosis
Author :
Zhifu Wang ; Jingzhe Yang ; Ye Huiping ; Wei Zhou
Author_Institution :
Nat. Eng. Lab. for Electr. Vehicle, Beijing Inst. of Technol., Beijing, China
fDate :
Aug. 31 2014-Sept. 3 2014
Abstract :
This paper presents a review of Permanent Magnet Synchronous Motor (PMSM) fault diagnosis methods. Firstly, PMSM usual faults including electrical, mechanical, and magnetic faults are listed. In the third part, the various signal processing methods for PMSM are summarized. Finally, the artificial intelligence methods for PMSM fault diagnosis are reviewed, such as artificial neural network, fuzzy logic.
Keywords :
electrical faults; fault diagnosis; fuzzy logic; maintenance engineering; neural nets; permanent magnet motors; power engineering computing; reliability; synchronous motors; PMSM fault diagnosis method; artificial neural network; electrical faults; fuzzy logic; magnetic faults; mechanical faults; permanent magnet synchronous motor; Circuit faults; Computational modeling; Demagnetization; Integrated circuit modeling; Maintenance engineering; Signal resolution; Windings; Artificial Neural Network (ANN); Finite Element Analysis (FEA); PMSM; Short-time Fourier transform (STFT); Wavelet Analysis; diagnosis; fault;
Conference_Titel :
Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-4240-4
DOI :
10.1109/ITEC-AP.2014.6940870
