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

fYear

2014

fDate

Aug. 31 2014-Sept. 3 2014

Firstpage

1

Lastpage

5

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014 IEEE Conference and Expo

Conference_Location

Beijing

Print_ISBN

978-1-4799-4240-4

Type

conf

DOI

10.1109/ITEC-AP.2014.6940870

Filename

6940870