The Diagnosis Method of Stator Winding Faults in PMSMs Based on SOM Neural Networks

In this paper, the diagnosis method based on wavelet and neural network is proposed. This method needs not to collect a large number of data, but simplifies the diagnostic process while ensuring the accuracy of diagnostic result. The three-phase stator current data were decomposed by db6 wavelet fun...

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Bibliographic Details
Published in:Energy procedia 2017-01, Vol.105, p.2295-2301
Main Authors: Chuang, Cao, Wei, Zhang, Zhifu, Wang, Zhi, Li
Format: Article
Language:English
Subjects:
artificial intelligence
fault diagnosis
Self-organizing feature map
wavelet transform
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Summary:In this paper, the diagnosis method based on wavelet and neural network is proposed. This method needs not to collect a large number of data, but simplifies the diagnostic process while ensuring the accuracy of diagnostic result. The three-phase stator current data were decomposed by db6 wavelet function. It does not require the introduction of additional detection equipment, but also avoid the intrusion detection that may destruct the motor. This study has significance in engineering application to the development of on-line diagnosis system. The research on fault diagnosis system will promote the development of electric vehicle industry. As the improvement of safety control, it will accelerate the popularization of electric vehicles.
ISSN:1876-6102
1876-6102
DOI:10.1016/j.egypro.2017.03.663