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Motor broken-bar fault diagnosis based on Park vector and wavelet neural network
Zhang QX(张庆新); Jin, Li; Li, Haibin; Liu, Chong
Department工业信息学研究室
Conference Name2011 International Conference on Advanced Research on Advanced Structure, Materials and Engineering, ASME 2011
Conference DateDecember 24-25, 2011
Conference PlaceBeijing, China
Author of SourceInternational Science and Education Researcher Association (ISER); Beijing Gireida Education Research Center; VIP-Information Conference Center
Source PublicationAdvanced Materials Research
PublisherTrans Tech Publications
Publication PlaceClausthal-Zellerfeld, Germany
2011
Pages163-166
Indexed ByEI
EI Accession number20115114617401
Contribution Rank1
ISSN1022-6680
ISBN978-3-03785-299-6
KeywordComputer Simulation Computer Software Electric Fault Currents Failure Analysis Matlab Natural Frequencies Parks Stators Vectors Wavelet Analysis Wavelet Decomposition
AbstractIn the technology of motor fault diagnosis, current monitoring methods have become a new trend in motor fault diagnosis. This paper presents a motor fault diagnosis method based on Park vector and wavelet neural network. This method uses the stator current as the object of study. Firstly, it uses Park vector to deal with the stator current and filter out fundamental frequency component, thus the characteristics component of motor broken-bar will be separated from fundamental frequency component; Secondly, it uses five layers wavelet packet decomposition to pick up fault characteristic signal; Finally, we distinguish the fault by BP neural network, and use the simulation software of MATLAB to realize it. The test results show that: This method can detect the existence of motor broken-bar fault, and has a good value in engineering.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/9884
Collection信息服务与智能控制技术研究室
Affiliation1.Automation Department, Shenyang Aerospace University, Shenyang, 110136, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
Recommended Citation
GB/T 7714
Zhang QX,Jin, Li,Li, Haibin,et al. Motor broken-bar fault diagnosis based on Park vector and wavelet neural network[C]//International Science and Education Researcher Association (ISER); Beijing Gireida Education Research Center; VIP-Information Conference Center. Clausthal-Zellerfeld, Germany:Trans Tech Publications,2011:163-166.
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