• DocumentCode
    498645
  • Title

    Research upon Fault Diagnosis Expert System Based on Fuzzy Neural Network

  • Author

    Kun, Yang ; Guangyao, Ouyang ; Lina, Ye

  • Author_Institution
    Power Eng. Dept., Naval Univ. of Eng., Wuhan, China
  • Volume
    1
  • fYear
    2009
  • fDate
    10-11 July 2009
  • Firstpage
    410
  • Lastpage
    413
  • Abstract
    The traditional Expert System has many shortcomings, for instance, its weak knowledge acquisition capability and empirical knowledgepsilas expression uncertainty. To solve these bottleneck problems, A strategy on fault diagnosis expert system which is based upon fuzzy theory and ANN(ANN:artificial neural network) technique is put forward in this paper, as also its principle, construction, algorithm are all presented. Its performance has been proved to be very excellent when used upon the diesel fuel system classified fault diagnosis.
  • Keywords
    expert systems; fault diagnosis; fuzzy set theory; neural nets; artificial neural network; expert system; fault diagnosis; fuzzy neural network; fuzzy theory; knowledge acquisition; Artificial neural networks; Diagnostic expert systems; Electronic mail; Fault diagnosis; Fuzzy neural networks; Fuzzy systems; Humans; Knowledge acquisition; Knowledge engineering; Power engineering and energy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering, 2009. ICIE '09. WASE International Conference on
  • Conference_Location
    Taiyuan, Shanxi
  • Print_ISBN
    978-0-7695-3679-8
  • Type

    conf

  • DOI
    10.1109/ICIE.2009.136
  • Filename
    5211246