• DocumentCode
    1608110
  • Title

    Fault Diagnosis of Induction Motor Based on Artificial Immune System

  • Author

    Yuan, Gui-li ; Qin, Shi-wei ; Zhang, Jian

  • Author_Institution
    Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
  • fYear
    2012
  • Firstpage
    166
  • Lastpage
    170
  • Abstract
    Based on principles of artificial immune systems, this paper put forward a fault diagnosis method for induction motor. Compared to the traditional negative selection algorithm, this method is added dynamic detector radius variation and immune memory cells, and improved the fault diagnosis detection rate for induction motor. Through simulation and testing, the validity of this method is proved.
  • Keywords
    artificial immune systems; fault diagnosis; induction motors; artificial immune system; dynamic detector radius variation; fault diagnosis detection rate; immune memory cells; induction motor fault diagnosis; negative selection algorithm; Detectors; Fault detection; Fault diagnosis; Heuristic algorithms; Immune system; Induction motors; Vectors; Artificial immune system; fault diagnosis; induction motor; negative selection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4673-1450-3
  • Type

    conf

  • DOI
    10.1109/ICICEE.2012.51
  • Filename
    6322340