Cookies

We use cookies to ensure that we give you the best experience on our website. You can change your cookie settings at any time. Otherwise, we'll assume you're OK to continue.

School of Engineering and Computing Sciences (ECS)

Profile

Publication details for Professor Peter Tavner

Yang, W., Tavner, P.J. & Wilkinson, M.R. (2009). Condition monitoring and fault diagnosis of a wind turbine synchronous generator drive train. IET Proceedings, Renewable Power Generation 3(1): 1-11.
  • Publication type: Journal papers: academic
  • ISSN/ISBN: 1752-1416, 1752-1424
  • DOI: 10.1049/iet-rpg:20080006
  • Keywords: Condition monitoring, Fault diagnosis, Synchronous generator drive train, Low-speed synchronous generator, Wind turbines, Electrical faults, Mechanical faults, Aerodynamic effects, Wavelet transforms, Spectral analysis, Stochastic effects.
  • View online: Online version
  • Durham research online: DRO record

Author(s) from Durham

Abstract

Some large grid connected wind turbines use a low-speed synchronous generator, directly coupled to the turbine, and a fully rated converter to transform power from the turbine to mains electricity. The condition monitoring and diagnosis of mechanical and electrical faults in such a machine are considered, bearing in mind that it has a slow variable speed and is subject to the stochastic, aerodynamic effects of the wind. The application of wavelet transforms is investigated in the light of the disadvantages of spectral analysis in processing signals subject to such stochastic effects. The technique can be used to monitor generator electrical and drive train mechanical faults. It is validated experimentally on a wind turbine condition monitoring test rig using a three-phase, permanent-magnet, slow-speed, synchronous generator, driven by a motor controlled by a model representing the aerodynamic forces from a wind turbine. The possibility of detecting mechanical and electrical faults in wind turbines by electrical signal and particularly power analysis is heralded.