Composite fault diagnosis of rolling bearings based on EMD and ICA algorithm - 文章详情页

作者：

Cui, L.-L. (Cui, L.-L..) (学者：崔玲丽) | Wu, C.-G. (Wu, C.-G..) | Wu, N. (Wu, N..)

收录：

Scopus PKU CSCD

摘要：

Aiming　at　the　difficulty　of　separating　rolling　bearing　composite　faults　in　the　case　of　single　channel　signal,　a　new　algorithm　based　on　empirical　mode　decomposition　(EMD)　and　independent　component　analysis　(ICA)　was　proposed　in　this　paper.　First,　the　composite　bearing　fault　signals　collected　for　a　single　channel　were　decomposed　by　EMD　to　obtain　some　intrinsic　mode　function　(IMF).　Then,　main　components　were　confirmed　by　calculating　the　correlation　coefficient　of　every　IMF　and　original　composite　signal　and　kurtosis　value　of　every　IMF.　At　the　same　time,　main　components　with　original　signal　were　processed　by　ICA　to　realize　the　separation　of　composite　fault　of　rolling　bearings.　Experimental　results　show　that　this　method　can　effectively　separate　early　rolling　bearings　composite　fault.

关键词：

Composite fault diagnosis of rolling bearings; Empirical mode decomposition (EMD); Independent component analysis (ICA); Kurtosis

作者机构：

[ 1 ] [Cui, L.-L.]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Wu, C.-G.]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China
[ 3 ] [Wu, N.]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing, 100124, China

通讯作者信息：

崔玲丽
[Cui, L.-L.]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of TechnologyChina

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