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Author:

Gao, Li-Xin (Gao, Li-Xin.) | Yin, Hai-Chen (Yin, Hai-Chen.) | Zhang, Jian-Yu (Zhang, Jian-Yu.) | Xu, Yong-Gang (Xu, Yong-Gang.)

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EI Scopus PKU CSCD

Abstract:

In dealing with the deficiency of traditional wavelet analysis in extracting fault feature of bearing, the second generation of wavelet transform (SGWT) is adopted in the fault diagnosis of bearing. The prediction operator and update operator of SGWT are constructed based on the interpolating subdivision principle. Furthermore, the first-order smoothing boundary constitution technology is used to solve the mutation problem in the calculating boundary. As a result, the reconstructed signal can be smoothed. The denoising technology based on SGWT can subtract the background noise to obtain the fault feature successfully, and the effect is much better than that of the traditional wavelet denoising. Finally, the incipient fault features have been extracted successfully by integrating the SWGT with correlation analysis and demodulation technology.

Keyword:

Fault detection Wavelet transforms Roller bearings Failure analysis

Author Community:

  • [ 1 ] [Gao, Li-Xin]Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Yin, Hai-Chen]Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Zhang, Jian-Yu]Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Xu, Yong-Gang]Key Laboratory of Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2009

Issue: 5

Volume: 35

Page: 577-581

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: 9

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