• DocumentCode
    2306929
  • Title

    Fault Diagnosis Algorithm Based on Artificial Immunity System

  • Author

    Aydin, Ilhan ; Karakose, Mehmet ; Akin, Erhan

  • Author_Institution
    Firat Univ., Elazig
  • fYear
    2006
  • fDate
    17-19 April 2006
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Artificial immunity systems have been emerged as simulation of human immunity. The negative selection algorithm which is most important component of artificial immunity system can determine undesired condition, easily. In this study, motor current signature analysis and negative selection algorithm have been used for broken rotor bar faults. Current signal obtained from motor has been transformed to current spectrum by using motor current signature analysis. The side bands extracted from this spectrum have been taken as input to negative selection algorithm, and broken rotor bar faults have been diagnosed. The application of developed fault diagnosis algorithm has been demonstrated by diagnosing faults in induction motor real time. Furthermore, proposed fault diagnosis approach is adapted for diagnosing other faults
  • Keywords
    fault location; induction motors; rotors; signal processing; artificial immunity system; broken rotor bar fault; current signature analysis; current spectrum; fault diagnosis algorithm; induction motor; negative selection algorithm; side band extraction; Algorithm design and analysis; Fault diagnosis; Humans; Immune system; Induction motors; Rotors; Stators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications, 2006 IEEE 14th
  • Conference_Location
    Antalya
  • Print_ISBN
    1-4244-0238-7
  • Type

    conf

  • DOI
    10.1109/SIU.2006.1659876
  • Filename
    1659876