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[会议论文]

Adaptively pattern recognition in statistical process control using fuzzy ART neural network

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Author:

Wang, Min (Wang, Min.) (Scholars:王民) | Zan, Tao (Zan, Tao.)

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EI Scopus

Abstract:

This paper presents a statistical Process Control (SPC) method based on Fuzzy ART (adaptive Resonance Theory) neural network. The Fuzzy ART neural network is applied to recognize the special disturbance of the manufacturing processes based on the classification on the histograms. It is shown that the Fuzzy ART neural network can adaptively learn the features of the histograms of the quality parameters in manufacturing processes. As a result, the special disturbance can be automatically detected when a feature of the special disturbance starts to appear in the histograms. © 2010 IEEE.

Keyword:

Pattern recognition Graphic methods Fuzzy logic Fuzzy neural networks Arts computing Statistical process control Adaptive control systems Statistical methods Fuzzy inference

Author Community:

  • [ 1 ] [Wang, Min]Key Lab. of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Zan, Tao]Key Lab. of Advanced Manufacturing Technology, Beijing University of Technology, Beijing, 100124, China

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Source :

Year: 2010

Volume: 1

Page: 160-163

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

30 Days PV: 6

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