• DocumentCode
    2792669
  • Title

    Advanced signal processing techniques for fault detection and diagnosis in a wind turbine induction generator drive train: A comparative study

  • Author

    Ahmar, E. Al ; Choqueuse, V. ; Benbouzid, M.E.H. ; Amirat, Y. ; El Assad, J. ; Karam, R. ; Farah, S.

  • Author_Institution
    Lab. Brestois de Mcanique et des Systmes (LBMS EA 4325), Univ. of Brest, Brest, France
  • fYear
    2010
  • fDate
    12-16 Sept. 2010
  • Firstpage
    3576
  • Lastpage
    3581
  • Abstract
    This paper deals with the diagnosis of Wind Turbines based on generator current analysis. It provides a comparative study between traditional signal processing methods, such as periodograms, with more sophisticated approaches. Performances of these techniques are assessed through simulation experiments and compared for several types of fault, including air-gap eccentricities, broken rotor bars and bearing damages.
  • Keywords
    asynchronous generators; fault location; signal processing; wind turbines; fault detection; fault diagnosis; generator current analysis; induction generator drive; signal processing; wind turbine; Bars; Monitoring; Rotors; Signal resolution; Spectrogram; Time frequency analysis; Wind turbines; failure diagnosis; motor current signature analysis; time-frequency signal processing methods; wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy Conversion Congress and Exposition (ECCE), 2010 IEEE
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4244-5286-6
  • Electronic_ISBN
    978-1-4244-5287-3
  • Type

    conf

  • DOI
    10.1109/ECCE.2010.5617707
  • Filename
    5617707