• DocumentCode
    2953420
  • Title

    Operational Fault Feature Extraction of Blade Based on Vibration of Wind Turbine

  • Author

    Yan Jun ; Xu Yuxiu

  • Author_Institution
    Sch. of Mech. & Electr. Eng., Tianjin Polytech. Univ., Tianjin, China
  • fYear
    2011
  • fDate
    30-31 July 2011
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    By analyzing the acquisition data of the wind turbine, we calculate the correlation dimension of the vibration signals, and take it as the feature parameter which typifies the working state of blades. The calculation results indicated that the correlation dimension is effective to reflect the dynamic structure of chaotic attractor. Thus the correlation dimension of blades´ vibration signals can be used to classify the different working state of blades effectively. Experiments have also shown that this method is especially effective at working state monitoring and at fault diagnosis, and can achieve higher precision in these applications.
  • Keywords
    blades; condition monitoring; data acquisition; fault diagnosis; feature extraction; mechanical engineering computing; signal classification; vibrations; wind turbines; blades; chaotic attractor; data acquisition; fault diagnosis; feature parameters; operational fault feature extraction; vibration signal classification; wind turbines; Blades; Correlation; Fasteners; Feature extraction; Monitoring; Vibrations; Wind turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation and Systems Engineering (CASE), 2011 International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4577-0859-6
  • Type

    conf

  • DOI
    10.1109/ICCASE.2011.5997632
  • Filename
    5997632