• DocumentCode
    3525935
  • Title

    Diagnosis of electrical and mechanical faults of induction motor

  • Author

    Nakamura, H. ; Yamamoto, Y. ; Mizuno, Y.

  • Author_Institution
    TOENEC Corp., Nagoya
  • fYear
    2006
  • fDate
    15-18 Oct. 2006
  • Firstpage
    521
  • Lastpage
    524
  • Abstract
    This paper proposes a new method for fault diagnosis of induction motors based on Hidden Markov Model, which is widely used in the field of speech recognition. In order to carry out pattern recognition, current waveforms running in stator winding are analyzed for motors with short circuit fault in stator windings or with broken rotor bars. Frequency spectrum of current are also investigated. The usefulness of the proposed diagnosis method is verified through pattern recognitions for arbitrary current waveforms obtained by experiments.
  • Keywords
    fault diagnosis; hidden Markov models; induction motors; pattern recognition; stators; current waveforms; electrical fault diagnosis; hidden Markov model; induction motor; mechanical fault diagnosis; pattern recognition; rotor bars; short circuit fault; stator winding; stator windings; Bars; Circuit faults; Fault diagnosis; Hidden Markov models; Induction motors; Pattern analysis; Pattern recognition; Rotors; Speech recognition; Stator windings;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Insulation and Dielectric Phenomena, 2006 IEEE Conference on
  • Conference_Location
    Kansas City, MO
  • Print_ISBN
    1-4244-0547-5
  • Electronic_ISBN
    1-4244-0547-5
  • Type

    conf

  • DOI
    10.1109/CEIDP.2006.311984
  • Filename
    4105485