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Author:

Gao, Lixin (Gao, Lixin.) | Han, Jinshun (Han, Jinshun.) | Zhang, Jianyu (Zhang, Jianyu.) | Ding, Qingxin (Ding, Qingxin.) | Zhuo, Li (Zhuo, Li.) | Cui, Lingli (Cui, Lingli.) (Scholars:崔玲丽)

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Abstract:

Aimed at the difficulty to extract the fault information of a low speed shaft in a large gearbox, wavelet analysis was used to realize the local analysis of signals in a time and frequency domain simultaneously. The signals were dissembled to a series of compactly supported wavelet bases non-redundantly and without leaking. The saltation coefficient of wavelet analysis was regarded as a characteristic value to predict a sudden accident and the changing trend of the coefficient was figured out. The results showed that wavelet transform could capture the characteristics in a time domain and the evolvement procedure of a fault. The trend graph of the coefficient could effectively predict the development trend of a fault and avoid a sudden accident.

Keyword:

Frequency domain analysis Fault tree analysis Feature extraction Gears Wavelet transforms Shafts (machine components) Graph theory

Author Community:

  • [ 1 ] [Gao, Lixin]Laboratory for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Han, Jinshun]Laboratory for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Zhang, Jianyu]Laboratory for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Ding, Qingxin]Beijing No. 1 Machine Tool Plant, Beijing 100022, China
  • [ 5 ] [Zhuo, Li]Laboratory for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China
  • [ 6 ] [Cui, Lingli]Laboratory for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China

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Source :

Journal of University of Science and Technology Beijing

ISSN: 1001-053X

Year: 2005

Issue: 3

Volume: 27

Page: 342-346

JCR Journal Grade:2

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: 4

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