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Author:

Cui, Lingli (Cui, Lingli.) (Scholars:崔玲丽) | Mo, Daiyi (Mo, Daiyi.) | Wu, Na (Wu, Na.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

In order to extract the early weak impact fault information in gearbox vibration signal submerged in strong background noise, a new sparse signal decomposition method using dual-BP is proposed. Firstly, the short-time Fourier transform using the window functions with different lengths is adopted to perform the signal sparse decomposition, and the initial decomposition coefficients are obtained; secondly, the dual-BP is used to optimize the obtained decomposition coefficients; lastly, the obtained coefficients are reconstructed, and the sustained oscillation component and the failure impact component of the signal are obtained; further, the failure impact component is analyzed and the diagnose result is obtained. The analysis results of simulation signal and application examples confirm the feasibility and validity of this method, which provides a new idea for the mechanical fault signal extraction in strong noise environment. ©, 2014, Science Press. All right reserved.

Keyword:

Signal processing Signal distortion

Author Community:

  • [ 1 ] [Cui, Lingli]College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing ; 100124, China
  • [ 2 ] [Mo, Daiyi]College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing ; 100124, China
  • [ 3 ] [Wu, Na]College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing ; 100124, China

Reprint Author's Address:

  • 崔玲丽

    [cui, lingli]college of mechanical engineering and applied electronics technology, beijing university of technology, beijing ; 100124, china

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Source :

Chinese Journal of Scientific Instrument

ISSN: 0254-3087

Year: 2014

Issue: 11

Volume: 35

Page: 2633-2640

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

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