• DocumentCode
    3233442
  • Title

    Application of a wavelet-based MRA for diagnosing disturbances in a three-phase induction motor

  • Author

    Saleh, S.A. ; Khan, M. Abdesh ; Rahman, M.A.

  • Author_Institution
    Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland, St. John´´s, NL
  • fYear
    2005
  • fDate
    7-9 Sept. 2005
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a new technique for detecting and diagnosing various disturbances occurring in three-phase induction motors. The proposed technique is based on a wavelet-based multiresolution analysis (MRA), where samples of three-phase stator current are analyzed using wavelet-based MRA. Different disturbances have been created in both stator and rotor windings of a wound rotor induction motor. Stator currents data have been collected for processing using a wavelet-based MRA. The application of the wavelet packet transform has shown that all fault conditions have non-zero second level high frequency subband coefficients, while normal and starting currents have zero values for the same coefficients. This property can be used as a main diagnosis tool for induction machine protection.
  • Keywords
    fault diagnosis; induction motor protection; machine testing; rotors; stators; wavelet transforms; diagnosis tool; fault conditions; induction machine protection; non-zero second level high frequency subband coefficients; rotor windings; stator currents data; stator windings; three-phase induction motor; three-phase stator current; wavelet packet transform; wavelet-based MRA; wavelet-based multiresolution analysis; wound rotor induction motor; Frequency; Induction machines; Induction motors; Multiresolution analysis; Rotors; Stator windings; Wavelet analysis; Wavelet packets; Wavelet transforms; Wounds;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Diagnostics for Electric Machines, Power Electronics and Drives, 2005. SDEMPED 2005. 5th IEEE International Symposium on
  • Conference_Location
    Vienna
  • Print_ISBN
    978-0-7803-9124-6
  • Electronic_ISBN
    978-0-7803-9125-3
  • Type

    conf

  • DOI
    10.1109/DEMPED.2005.4662523
  • Filename
    4662523