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Author:

Fu, Sheng (Fu, Sheng.) | Li, Hai-Tao (Li, Hai-Tao.) | Zhu, Quan (Zhu, Quan.)

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EI Scopus PKU CSCD

Abstract:

In order to exactly determine the fault of the ventilator and realize the early warning of it, the warning principle of the ventilator failure is proposed. The fault early warning software based on the information fusion technology is developed using VC++ 6.0 combined with Matcom 4.5. Information fusion technology and BP neural networks and evidence theory are adopted in the software, in which non-linearity mapping between the fault style and the diagnostic frequency is accomplished by the BP neural network and multichannels signal fusing and analyzing is carried out using the theory of evidence. Data acquisition and conclusion return are realized by using the OPC mode communication between the King View running system and the developed software.

Keyword:

Software engineering Data acquisition Neural networks Information fusion Mine ventilation Failure analysis Mergers and acquisitions

Author Community:

  • [ 1 ] [Fu, Sheng]College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Li, Hai-Tao]College of Mechanical Engineering and Applied Electronics Technology, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Zhu, Quan]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: 8

Volume: 33

Page: 809-812

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 0

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