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Author:

Xu, Yonggang (Xu, Yonggang.) | Meng, Zhipeng (Meng, Zhipeng.) | Lu, Ming (Lu, Ming.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

A new fault diagnosis method is proposed based on the dual-tree complex wavelet packet transform (DT-CWPT) and independent component analysis (ICA), aiming at separating fault information from the compound rolling bearing fault signal. First, the non-stationary and complex signal of the compound fault is decomposed into several different frequency band components through dual-tree complex wavelet packet decomposition. Then, ICA is used to separate the mixed signal consisting of each component to eliminate the frequency aliasing as much as possible. Finally, independent signal components separated from the mixed signal are processed by Hilbert demodulation. The results show that the fault feature of rolling bearing can be effectively separated and extracted, and the method's feasibility and effectiveness are verified. ©, 2015, Nanjing University of Aeronautics an Astronautics. All right reserved.

Keyword:

Partial discharges Wavelet decomposition Fault tree analysis Fault detection Blind source separation Roller bearings Independent component analysis Wavelet analysis

Author Community:

  • [ 1 ] [Xu, Yonggang]Beijing Engineering Research Center of Precision Measurement Technology and Instruments, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Meng, Zhipeng]Beijing Engineering Research Center of Precision Measurement Technology and Instruments, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Lu, Ming]Beijing Engineering Research Center of Precision Measurement Technology and Instruments, Beijing University of Technology, Beijing; 100124, China

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Source :

Journal of Vibration, Measurement and Diagnosis

ISSN: 1004-6801

Year: 2015

Issue: 3

Volume: 35

Page: 513-518

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 10

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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