• DocumentCode
    2303492
  • Title

    Cooperative maintenance decision system for power plant based on swarm intelligence

  • Author

    Guo, Jiang ; Gu, Kai-kai ; Liu, Ya-jin ; Wang, Yi-xin ; Zhao, Xiang-ping

  • Author_Institution
    Scholl of Power & Mech. Eng., Wuhan Univ., Wuhan, China
  • Volume
    6
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    2903
  • Lastpage
    2907
  • Abstract
    Maintenance is one of the important research subjects of the electric power system. In order to realize cooperative maintenance decision, the system framework of multi-knowledge, multi-method, multi-resource, multi-information based on swarm intelligence is constructed, the method of knowledge modeling is studied. Swarm intelligence is a quality that many individuals can behave intelligently through interaction. The individuals are open to each other, sharing the resource information, managing and dispatching are unified with the platform based on knowledge grid, the serving information is offered for different power plants, manufactures and research units. That is beneficial to enhancing the diagnosis and management of the maintenance decision support system, reducing its costs, and improving its efficiency, thus providing a feasible approach for the realization of condition-based maintenance gradually.
  • Keywords
    decision support systems; maintenance engineering; power system management; cooperative maintenance decision system; electric power system; knowledge grid; maintenance decision support system; power plants; resource information; serving information; swarm intelligence; system framework; Companies; Generators; Knowledge based systems; Knowledge engineering; Maintenance engineering; Power generation; Security; Knowledge Grid; Swarm Intelligence; component; condition-based maintenance; maintenance decision; power engineering; power plant;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5584110
  • Filename
    5584110