• DocumentCode
    3349835
  • Title

    Research on rotary dump health monitoring expert system based on causality diagram theory

  • Author

    Quan, Liu ; Jingsong, Li

  • Author_Institution
    Sch. of Inf. Eng., Wuhan Univ. of Technol., Wuhan
  • fYear
    2008
  • fDate
    21-24 Sept. 2008
  • Firstpage
    296
  • Lastpage
    299
  • Abstract
    Causality diagram theory is a kind of uncertainty reasoning theory based on the belief network. It expresses the knowledge and causality relationship by diagrammatic form and direct causality intensity. Furthermore, it resolves the shortages of the belief network, and realizes a hybrid model which can process discrete and continuous variations. The theory of causality diagram model and the steps of causality diagram reasoning methodology are studied in this paper, and a model of rotary dump health monitoring expert system is proposed. In addition, this paper establishes the causality diagram of rotary dump and converts it to the causality tree. According to the causality tree of rotary dump, the causality diagram reasoning methodology composed of four steps is described. Finally, an application of rotary dump health monitoring expert system is shown, and the system performance analysis is discussed.
  • Keywords
    belief networks; causality; condition monitoring; diagnostic expert systems; fault diagnosis; inference mechanisms; mechanical engineering computing; belief network; causality diagram reasoning methodology; causality diagram theory; rotary dump health monitoring expert system; uncertainty reasoning theory; Application software; Artificial intelligence; Couplings; Diagnostic expert systems; Expert systems; Knowledge representation; Monitoring; Probability distribution; System performance; Uncertainty; Causality Diagram; Expert System; Fault Diagnosis; Reasoning on Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cybernetics and Intelligent Systems, 2008 IEEE Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-1673-8
  • Electronic_ISBN
    978-1-4244-1674-5
  • Type

    conf

  • DOI
    10.1109/ICCIS.2008.4670773
  • Filename
    4670773