Volume 29 Issue 1
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XU Yong-gang, MENG Zhi-peng, LU Ming. Fault diagnosis method of rolling bearing based on dual-tree complex wavelet packet transform and SVM[J]. Journal of Aerospace Power, 2014, 29(1): 67-73. doi: 10.13224/j.cnki.jasp.2014.01.009
Citation: XU Yong-gang, MENG Zhi-peng, LU Ming. Fault diagnosis method of rolling bearing based on dual-tree complex wavelet packet transform and SVM[J]. Journal of Aerospace Power, 2014, 29(1): 67-73. doi: 10.13224/j.cnki.jasp.2014.01.009
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Fault diagnosis method of rolling bearing based on dual-tree complex wavelet packet transform and SVM

doi: 10.13224/j.cnki.jasp.2014.01.009

  • Key Laboratory of Advanced Manufacturing Technology of Beijing, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100124, China

  • Received Date: 2012-11-27
  • Publish Date: 2014-01-28
    Abstract
  • For the problem of non-stationary signals of rolling bearing and the difficulty to get a large number of typical fault samples in practice, a fault diagnosis method was proposed based on dual-tree complex wavelet packet transform and support vector machine (SVM). Firstly, the non-stationary fault vibration signal was decomposed into several different frequency band components through dual-tree complex wavelet packet transform; secondly, normalization processing was made from the energy of each component. Finally, the energy characteristics parameters of each frequency band component were taken as input of the SVM to identify the fault type of rolling bearing. The analog signals of experiments, containing normal condition of the rolling bearing, crack fault of bearing outer ring, crack fault of bearing inner ring and pitting fault of bearing rolling element, were analyzed and the fault recognition rate reaches 99.5%. The proposed method can identify the working state and fault type of rolling bearing accurately and effectively, as compared with the method of combining traditional wavelet packet transform with SVM.

     

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