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Condition Monitoring and Diagnostics of Wind Turbines: A Survey

[+] Author Affiliations
Paolo Pennacchi, Steven Chatterton, Candas Gultekin

Politecnico di Milano, Milan, Italy

Pietro Borghesani

Queensland University of Technology, Brisbane, QLD, Australia

Paper No. DETC2014-35352, pp. V008T11A070; 14 pages
  • ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 8: 26th Conference on Mechanical Vibration and Noise
  • Buffalo, New York, USA, August 17–20, 2014
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4641-4
  • Copyright © 2014 by ASME


Wind energy conversion is the fastest growing source of electricity generation in the world among the other renewable energy production technologies. Whereas investment costs have decreased over years, operational and maintenance costs of wind turbines are still high, thus attracting the focus of researchers and industrial operators.

Classical maintenance techniques, i.e.: run-to-failure and scheduled-preventive maintenance, are still dominant in this sector; however, condition monitoring has gained space in the wind turbine market and new diagnostic methods and techniques are continuously being proposed. Condition monitoring techniques seem the most effective tools to minimize operational and maintenance costs and reduce downtimes by early detection of faults.

This paper is aimed at reviewing the state of the art of condition monitoring for horizontal axis wind turbines. After a brief introduction presenting the current trends in the market of wind energy, the paper reviews the most common failure modes of wind turbines and the traditional approach to maintenance. The core of this study details the state of the art in the field of system architectures, sensors and signal processing techniques for the diagnostic of faults in wind turbine components. Finally, some general conclusions are drawn on the overall trends in the field of condition monitoring of wind turbines.

Copyright © 2014 by ASME



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