• DocumentCode
    3122638
  • Title

    An enhanced inference strategy for machine fault diagnosis system using hill-climbing approach

  • Author

    Liu, Shih-Yaug ; Chi, Sheng-Chai

  • Author_Institution
    Dept. of Ind. Manage., Kaohsiung Polytech. Inst., Taiwan
  • Volume
    3
  • fYear
    1995
  • fDate
    22-25 Oct 1995
  • Firstpage
    2633
  • Abstract
    Most fault diagnosis systems in mechanic domain usually emphasize on the correctness of the hypothesized result. In time constrained situations, the efficiency of the diagnostic process becomes more important and should not be overlooked. This paper proposes a new inference strategy that can enhance the efficiency of the diagnostic process. Specifically, the proposed inference strategy attempts to find out the most efficient diagnostic process for detecting the cause of machine malfunction by the aid of multi-attribute decision making (MADM) method and hill-climbing search method. To verify the performance of the proposed inference strategy, two VCR diagnosis expert systems have been generated. One is developed by applying the proposed approach, and the other one is an ordinary expert system. The evaluation result indicates that the former system requests less diagnosis time than the latter system does when forty real repair records are employed
  • Keywords
    diagnostic expert systems; inference mechanisms; VCR diagnosis expert systems; enhanced inference strategy; hill-climbing approach; hill-climbing search method; machine fault diagnosis system; machine malfunction; multi-attribute decision making; Costs; Decision making; Diagnostic expert systems; Engines; Fault diagnosis; Humans; Search methods; Time factors; Tree data structures; Video recording;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-2559-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1995.538180
  • Filename
    538180