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Condition monitoring of wind turbines: Techniques and methods

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  • García Márquez, Fausto Pedro
  • Tobias, Andrew Mark
  • Pinar Pérez, Jesús María
  • Papaelias, Mayorkinos

Abstract

Wind Turbines (WT) are one of the fastest growing sources of power production in the world today and there is a constant need to reduce the costs of operating and maintaining them. Condition monitoring (CM) is a tool commonly employed for the early detection of faults/failures so as to minimise downtime and maximize productivity. This paper provides a review of the state-of-the-art in the CM of wind turbines, describing the different maintenance strategies, CM techniques and methods, and highlighting in a table the various combinations of these that have been reported in the literature. Future research opportunities in fault diagnostics are identified using a qualitative fault tree analysis.

Suggested Citation

  • García Márquez, Fausto Pedro & Tobias, Andrew Mark & Pinar Pérez, Jesús María & Papaelias, Mayorkinos, 2012. "Condition monitoring of wind turbines: Techniques and methods," Renewable Energy, Elsevier, vol. 46(C), pages 169-178.
    • Handle: RePEc:eee:renene:v:46:y:2012:i:c:p:169-178
    DOI: 10.1016/j.renene.2012.03.003
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    References listed on IDEAS

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    1. Garcia Marquez, Fausto Pedro & Pedregal Tercero, Diego Jose & Schmid, Felix, 2007. "Unobserved Component models applied to the assessment of wear in railway points: A case study," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1703-1712, February.
    2. Hameed, Z. & Hong, Y.S. & Cho, Y.M. & Ahn, S.H. & Song, C.K., 2009. "Condition monitoring and fault detection of wind turbines and related algorithms: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(1), pages 1-39, January.
    3. Zhen, Li & Zhengjia, He & Yanyang, Zi & Xuefeng, Chen, 2008. "Bearing condition monitoring based on shock pulse method and improved redundant lifting scheme," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 318-338.
    4. García, Fausto P. & Pedregal, Diego J. & Roberts, Clive, 2010. "Time series methods applied to failure prediction and detection," Reliability Engineering and System Safety, Elsevier, vol. 95(6), pages 698-703.
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