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| Fault Identification of Permanent Magnet Synchronous Motor System Driving under Chaotic State |
| WU Zhong-qiang,WU Chang-han,JIA Wen-jing,ZHAO Li-ru |
| Key Lab of Industrial Computer Control Engineering of Hebei Province, College of Electric Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract A research on fault identification of the permanent magnet synchronous motors driving under chaotic state is carried out, a fault identifier based on the wavelet support vector machine is established. After the empirical mode decomposition of the restored fault signals, serial stationary intrinsic mode functions are obtained, and their energy characteristics are used as inputs to establish a fault identifier based on the wavelet support vector machine. After training, the structure of the wavelet support vector machine and its internal parameters are fixed. The white noises usually simulate the unknown disturbances in practice. As the test inputs, the fault signals are mixed with white noises, and are identified by the fault identifier. The simulation results show that the fault identifier based on the wavelet support vector machine can identify the fault signals well, the fitting error is less than 1%.
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Received: 28 October 2014
Published: 27 January 2016
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2016, Vol. 37 
