Fault diagnosis based on Hermitian time-wavelet energy spectrum for rolling bearings - 文章详情页

作者：

Ma, C.-Y. (Ma, C.-Y..) | Wang, K. (Wang, K..) | Meng, Z.-P. (Meng, Z.-P..) | Duan, J.-M. (Duan, J.-M..) (学者：段建民)

收录：

Scopus PKU CSCD

摘要：

Aiming　at　the　difficulty　of　weak　fault　feature　extraction　for　rolling　bearing　early　fault,　a　fault　diagnosis　method　based　on　Hermitian　time-wavelet　energy　spectrum　was　proposed　for　rolling　bearing　fault　diagnosis.　First,　the　Hermitian　wavelet　to　original　signal　was　applied　to　acquire　the　continues　wavelet　transformation.　Then　the　signal　energy　distribution　along　the　time　axis　was　calculated　according　to　the　wavelet　transform　results.　The　spectrum　kurtosis　was　used　as　the　selection　criterion　of　optimal　cumulation　scale　to　obtain　the　time-wavelet　energy　distribution.　Finally,　the　spectrum　of　time-energy　distribution　was　calculated　to　obtain　the　time-energy　spectrum　and　extract　the　fault　feature.　The　results　of　the　simulation　signal　and　vibration　signals　of　outer　and　inner　rings　pitting　fault　show　that　this　method　can　effectively　extract　weak　fault　feature　in　strong　noise　background,　and　is　superior　compared　with　ordinary　time-wavelet　energy　spectrum;　therefore,　it　is　suitable　for　early　fault　feature　extraction　of　bearings.

关键词：

Fault diagnosis; Hermitian wavelet; Kurtosis; Time-wavelet energy spectrum

作者机构：

[ 1 ] [Ma, C.-Y.]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China
[ 2 ] [Ma, C.-Y.]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 3 ] [Wang, K.]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China
[ 4 ] [Meng, Z.-P.]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China
[ 5 ] [Duan, J.-M.]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

通讯作者信息：

[Ma, C.-Y.]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China

电子邮件地址：

machaoyong@bjut.edu.cn

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