W. Yang
Cost-effective condition monitoring for wind turbines
Yang, W.; Tavner, P.J.; Crabtree, C.J.; Wilkinson, M.
Abstract
Cost-effective wind turbine (WT) condition monitoring assumes more importance as turbine sizes increase and they are placed in more remote locations, for example, offshore. Conventional condition monitoring techniques, such as vibration, lubrication oil, and generator current signal analysis, require the deployment of a variety of sensors and computationally intensive analysis techniques. This paper describes a WT condition monitoring technique that uses the generator output power and rotational speed to derive a fault detection signal. The detection algorithm uses a continuous-wavelet-transform-based adaptive filter to track the energy in the prescribed time-varying fault-related frequency bands in the power signal. The central frequency of the filter is controlled by the generator speed, and the filter bandwidth is adapted to the speed fluctuation. Using this technique, fault features can be extracted, with low calculation times, from direct- or indirect-drive fixed- or variable-speed WTs. The proposed technique has been validated experimentally on a WT drive train test rig. A synchronous or induction generator was successively installed on the test rig, and both mechanical and electrical fault like perturbations were successfully detected when applied to the test rig.
Citation
Yang, W., Tavner, P., Crabtree, C., & Wilkinson, M. (2010). Cost-effective condition monitoring for wind turbines. IEEE Transactions on Industrial Electronics, 57(1), 263-271. https://doi.org/10.1109/tie.2009.2032202
Journal Article Type | Article |
---|---|
Publication Date | Jan 1, 2010 |
Deposit Date | Apr 6, 2010 |
Publicly Available Date | Mar 28, 2024 |
Journal | IEEE Transactions on Industrial Electronics |
Print ISSN | 0278-0046 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 57 |
Issue | 1 |
Pages | 263-271 |
DOI | https://doi.org/10.1109/tie.2009.2032202 |
Keywords | Adaptive signal processing, Condition monitoring, Fault diagnosis, Induction generators, Signal processing, Synchronous generators, Time-frequency analysis, Wavelet transforms, Wind power generation. |
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