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

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journal contribution
posted on 02.04.2012, 13:34 by Simon Watson, Jianping Xiang, Wenxian Yang, Peter J. Tavner, Christopher J. Crabtree
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.

Funding

This work was funded in part by the European Commission under the CONMOW project, contract ENK5-CT- 2002-00659.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

WATSON, S.J. ... et al., 2010. Condition monitoring of the power output of wind turbine generators using wavelets. IEEE Transactions on Energy Conversion, 25 (3), pp. 715 - 721

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publication date

2010

Notes

This article was published in the journal, IEEE Transactions on Energy Conversion [© IEEE]. The definitive version is available at: http://dx.doi.org/10.1109/TEC.2010.2040083

ISSN

0885-8969

Language

en