Fault Detection and Diagnosis of PMSM under Unsteady State with Variable Speed and Load Conditions

被引：0
|
作者：
Wang, Zhifu [1 ]
Cao, Chuang [1 ]
Song, Qiang [1 ]
Li, Wenjiang [2 ]
机构：
[1] Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing,100081, China
[2] Advanced Manufacture Technology Center of CAM, Beijing,100044, China
来源：
Journal of Beijing Institute of Technology (English Edition) | 2017年 / 26卷
基金：
中国国家自然科学基金;
关键词：
Signal processing - Synchronous motors - Permanent magnets - Stators - Fast Fourier transforms - MATLAB - Failure analysis;
D O I：
10.15918/j.jbit1004-0579.201726.S105
中图分类号：
学科分类号：
摘要：
An integrated fault diagnosis method for stator winding faults is proposed. Based on the abc coordinate mathematical model, the fault model of permanent magnet synchronous motor was defined. Drive control system model was established in Matlab/Simulink after that. The spectrum of three-phase stator current was analyzed by fast-Fourier transform (FFT) signal processing. Harmonic component was extracted as the fault feature vector. To achieve accurate diagnosis under unsteady conditions, the three-layer feed-forward artificial neural network (ANN) and the diagnosis swarm was proposed. The diagnosis method was validated by simulation and experimentation. According to the diagnosis result, a very keen degree of recognition for three type short circuits faults was showed. The accuracy rate is over 87%. © 2017 Editorial Department of Journal of Beijing Institute of Technology.
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页码：28 / 34
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