• DocumentCode
    2841419
  • Title

    Fault diagnosis algorithm based on artificial immune mechanism

  • Author

    Xinying, Xu ; Xiaoming, Han ; Jun, Xie ; Keming, Xie

  • Author_Institution
    Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China
  • fYear
    2009
  • fDate
    17-19 June 2009
  • Firstpage
    5314
  • Lastpage
    5317
  • Abstract
    In recent years, there has been a growth of investigation into the use of artificial immune system as a source of inspiration and metaphor for computational tasks. In this paper, we present a fault diagnosis algorithm based on artificial immune mechanism that can execute multi-point parallel search from local to global searching field and increase the diversity of antigen population and the ability of searching maximum. At last, we apply this algorithm to the fault diagnosis system. Simulation studies show that the proposed method is feasible and recognize the fault correctly.
  • Keywords
    artificial immune systems; artificial intelligence; fault diagnosis; genetic algorithms; query formulation; antigen population; artificial immune mechanism; fault diagnosis algorithm; maximum searching; multi-point parallel search; Artificial immune systems; Artificial intelligence; Artificial neural networks; Automatic control; Biological system modeling; Computer networks; Fault diagnosis; Immune system; Mathematical model; Mathematics; Artificial Immune Mechanism; Artificial Intelligence; Fault Diagnosis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2009. CCDC '09. Chinese
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4244-2722-2
  • Electronic_ISBN
    978-1-4244-2723-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2009.5195058
  • Filename
    5195058