• DocumentCode
    2495045
  • Title

    Damage detection in wind turbine blades using time-frequency analysis of vibration signals

  • Author

    Fitzgerald, Breiffni ; Arrigan, John ; Basu, Biswajit

  • Author_Institution
    Trinity Coll. Dublin, Dublin, Ireland
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The dynamic behavior of modern multi-Megawatt wind turbines has become an important design consideration. One of the major aspects related to the reliability of operation of the turbines concerns the safe and adequate performance of the blades. The aim of this paper is to develop a time-frequency based algorithm to detect damage in wind turbine blades from blade vibration signals. It is important that damage to blades is detected before they fail or cause the turbine to fail. A wind turbine model was developed for this paper. The parameters considered were the rotational speed of the blades and the stiffness of the blades and the nacelle. The model derived considers the structural dynamics of the turbine and includes the dynamic coupling between the blades and the tower. The algorithm developed uses a frequency tracking technique. Numerical simulations have been carried out to study the effectiveness of the algorithm.
  • Keywords
    blades; poles and towers; time-frequency analysis; vibrations; wind turbines; damage detection; frequency tracking technique; multi-Megawatt wind turbines; nacelle; time-frequency analysis; tower; vibration signals; wind turbine blades; Blades; Equations; Load modeling; Mathematical model; Time frequency analysis; Vibrations; Wind turbines; Short Time Fourier Transform; Tower blade coupling; Wind turbine blades;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2010 International Joint Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-6916-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2010.5596790
  • Filename
    5596790