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Author:

Cui, Ling-Li (Cui, Ling-Li.) (Scholars:崔玲丽) | Zhang, Jian-Yu (Zhang, Jian-Yu.) | Gao, Li-Xin (Gao, Li-Xin.) | Ding, Fang (Ding, Fang.)

Indexed by:

EI Scopus PKU CSCD

Abstract:

To improve the comprehensive diagnosis ability and extract signal feature of the gear-box typical fault in the high speed wire rolling mill, this paper puts forward a comprehensive traditional-new (CTN) diagnosis method in which time domain wave analysis, frequency analysis, time-domain trend analysis and characteristic frequency amplitude trend analysis are used to judge the status of the machine and fault parts qualitatively, and then precision diagnosis of wavelet packet decomposition and reconstruction based on the multi-resolution analysis is used. The research results arrive at the exact judgment of the fault quality and fault position quantitatively, which indicates the validity and the practicability of the proposed method.

Keyword:

Speed Frequency domain analysis Reconstruction (structural) Failure analysis Feature extraction Gears Signal processing Wire mills Time domain analysis

Author Community:

  • [ 1 ] [Cui, Ling-Li]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Zhang, Jian-Yu]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Gao, Li-Xin]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Ding, Fang]Key Laboratory of Advanced Manufacturing Technology, College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100022, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2007

Issue: 3

Volume: 33

Page: 245-250

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: 5

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