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Author:

Zan, Tao (Zan, Tao.) | Wang, Min (Wang, Min.) (Scholars:王民) | Li, Gang (Li, Gang.) (Scholars:李港) | Fei, Ren-Yuan (Fei, Ren-Yuan.)

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Abstract:

In this paper wavelet packet technique is used to decompose the vibration signals of grinding process. Since these decomposed signals in every band have different energy, they can be used to represent the vibration exception with fuzzy ART neural network. The fuzzy ART neural network can generate a new clustering to give an alarm when vibration exception of unknown pattern appears. Compared with traditional methods this method can identify the known and unknown pattern exceptions of grinding process. The result of practical application shows that this method is very efficient.

Keyword:

Grinding (machining) Fuzzy inference Pattern recognition Fuzzy logic Fuzzy neural networks Wavelet analysis Packet networks Arts computing

Author Community:

  • [ 1 ] [Zan, Tao]Beijing Key Lab. for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Wang, Min]Beijing Key Lab. for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Li, Gang]Beijing Key Lab. for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Fei, Ren-Yuan]Beijing Key Lab. for Advanced Manufacturing Technology, Beijing University of Technology, Beijing 100022, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2008

Issue: 7

Volume: 34

Page: 678-681,707

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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