Condition monitoring of the power output of wind turbine generators using wavelets

Watson, S.J.; Xiang, J.P.; Yang, W.; Tavner, P.J.; Crabtree, C.J.

Abstract

With an increasing number of wind turbines being erected offshore, there is a need for cost-effective, predictive, and proactive maintenance. A large fraction of wind turbine downtime is due to bearing failures, particularly in the generator and gearbox. One way of assessing impending problems is to install vibration sensors in key positions on these subassemblies. Such equipment can be costly and requires sophisticated software for analysis of the data. An alternative approach, which does not require extra sensors, is investigated in this paper. This involves monitoring the power output of a variable-speed wind turbine generator and processing the data using a wavelet in order to extract the strength of particular frequency components, characteristic of faults. This has been done for doubly fed induction generators (DFIGs), commonly used in modern variable-speed wind turbines. The technique is first validated on a test rig under controlled fault conditions and then is applied to two operational wind turbine DFIGs where generator shaft misalignment was detected. For one of these turbines, the technique detected a problem 3 months before a bearing failure was recorded.

Citation

Watson, S., Xiang, J., Yang, W., Tavner, P., & Crabtree, C. (2010). Condition monitoring of the power output of wind turbine generators using wavelets. IEEE Transactions on Energy Conversion, 25(3), 715-721. https://doi.org/10.1109/tec.2010.2040083

• Journal Article Type: Article
• Publication Date: Sep 1, 2010
• Deposit Date: Apr 6, 2010
• Publicly Available Date: Aug 31, 2010
• Journal: IEEE Transactions on Energy Conversion
• Print ISSN: 0885-8969
• Electronic ISSN: 1558-0059
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 25
• Issue: 3
• Pages: 715-721
• DOI: https://doi.org/10.1109/tec.2010.2040083
• Keywords: Condition monitoring, Electrical generator, Signal processing, Wind energy, Wind turbines.
• Public URL: https://durham-repository.worktribe.com/output/1522676