• DocumentCode
    1776862
  • Title

    Efficient diagnostic condition monitoring for industrial wind turbines

  • Author

    Hajiabady, S. ; Kerkyras, S. ; Hillmansen, Stuart ; Tricoli, P. ; Papaelias, M.

  • Author_Institution
    Birmingham Centre for Railway Res. & Educ., Univ. of Birmingham, Birmingham, UK
  • fYear
    2014
  • fDate
    24-25 Sept. 2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The drive-train and power electronics are critical for the operation of industrial wind turbines. Faults developing in these components can result in long downtime and expensive repair costs, particularly when offshore wind farms are concerned. Effective condition monitoring (CM) of these components can result in significant savings for wind farm operators and contribute to a substantial improvement of the operational reliability of wind turbines. This paper considers a novel modular CM system capable of diagnosing faults in the gearbox. The data analysis methodology and the key results arising from measurements on actual industrial wind turbines are also presented.
  • Keywords
    condition monitoring; data analysis; offshore installations; power system faults; power system reliability; wind turbines; condition monitoring; data analysis methodology; drivetrain; gearbox; industrial wind turbines; offshore wind farms; power electronics; wind farm operators; condition monitoring; diagnosis; wind turbine;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Renewable Power Generation Conference (RPG 2014), 3rd
  • Conference_Location
    Naples
  • Type

    conf

  • DOI
    10.1049/cp.2014.0932
  • Filename
    6993325