• DocumentCode
    1388750
  • Title

    Fault Diagnosis in Industrial Induction Machines Through Discrete Wavelet Transform

  • Author

    Bouzida, A. ; Touhami, O. ; Ibtiouen, R. ; Belouchrani, A. ; Fadel, M. ; Rezzoug, A.

  • Author_Institution
    Ecole Nat. Polytech., Algiers, Algeria
  • Volume
    58
  • Issue
    9
  • fYear
    2011
  • Firstpage
    4385
  • Lastpage
    4395
  • Abstract
    This paper deals with fault diagnosis of induction machines based on the discrete wavelet transform. By using the wavelet decomposition, the information on the health of a system can be extracted from a signal over a wide range of frequencies. This analysis is performed in both time and frequency domains. The Daubechies wavelet is selected for the analysis of the stator current. Wavelet components appear to be useful for detecting different electrical faults. In this paper, we will study the problem of broken rotor bars, end-ring segment, and loss of stator phase during operation.
  • Keywords
    asynchronous machines; discrete wavelet transforms; fault diagnosis; frequency-domain analysis; rotors; stators; time-domain analysis; Daubechies wavelet; discrete wavelet transform; fault diagnosis; frequency domains; industrial induction machines; rotor bars; stator current; time domains; wavelet components; wavelet decomposition; Approximation methods; Induction machines; Rotors; Stator windings; Wavelet transforms; Broken rotor bars; data-dependent selection (DDS) and data-independent selection (DIS) of the decomposition level; fault diagnosis; induction machines (IMs); motor-current signature analysis (MCSA); wavelet transform;
  • fLanguage
    English
  • Journal_Title
    Industrial Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0046
  • Type

    jour

  • DOI
    10.1109/TIE.2010.2095391
  • Filename
    5645682