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题名: Motor broken-bar fault diagnosis based on Park vector and wavelet neural network
作者: Zhang QX(张庆新) ; Jin, Li ; Li, Haibin ; Liu, Chong
作者部门: 信息服务与智能控制技术研究室
会议名称: 2011 International Conference on Advanced Research on Advanced Structure, Materials and Engineering, ASME 2011
会议日期: December 24-25, 2011
会议地点: Beijing, China
会议主办者: International Science and Education Researcher Association (ISER); Beijing Gireida Education Research Center; VIP-Information Conference Center
会议录: Advanced Materials Research
会议录出版者: Trans Tech Publications
会议录出版地: Clausthal-Zellerfeld, Germany
出版日期: 2011
页码: 163-166
收录类别: EI
ISSN号: 1022-6680
ISBN号: 978-3037852996
关键词: Computer simulation ; Computer software ; Electric fault currents ; Failure analysis ; MATLAB ; Natural frequencies ; Parks ; Stators ; Vectors ; Wavelet analysis ; Wavelet decomposition
摘要: In 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.
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/9884
Appears in Collections:信息服务与智能控制技术研究室_会议论文

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