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Side-band algorithm for automatic wind turbine gearbox fault detection and diagnosis

Zappalá, D.; Tavner, P.J.; Crabtree, C.J.; Sheng, S.

Side-band algorithm for automatic wind turbine gearbox fault detection and diagnosis Thumbnail


D. Zappalá

P.J. Tavner

S. Sheng


Improving the availability of wind turbines is critical for minimising the cost of wind energy, especially offshore. The development of reliable and cost-effective gearbox condition monitoring systems (CMSs) is of concern to the wind industry, because the gearbox downtime has a significant effect on the wind turbine availabilities. Timely detection and diagnosis of developing gear defects is essential for minimising an unplanned downtime. One of the main limitations of most current CMSs is the time consuming and costly manual handling of large amounts of monitoring data, therefore automated algorithms would be welcome. This study presents a fault detection algorithm for incorporation into a commercial CMS for automatic gear fault detection and diagnosis. Based on the experimental evidence from the Durham Condition Monitoring Test Rig, a gear condition indicator was proposed to evaluate the gear damage during non-stationary load and speed operating conditions. The performance of the proposed technique was then successfully tested on signals from a full-size wind turbine gearbox that had sustained gear damage, and had been studied in a National Renewable Energy Laboratory's (NREL) programme. The results show that the proposed technique proves efficient and reliable for detecting gear damage. Once implemented into the wind turbine CMSs, this algorithm can automate the data interpretation, thus reducing the quantity of the information that the wind turbine operators must handle.


Zappalá, D., Tavner, P., Crabtree, C., & Sheng, S. (2014). Side-band algorithm for automatic wind turbine gearbox fault detection and diagnosis. IET Renewable Power Generation, 8(4), 380-389.

Journal Article Type Article
Acceptance Date Nov 28, 2013
Online Publication Date Apr 10, 2014
Publication Date May 1, 2014
Deposit Date May 7, 2014
Publicly Available Date May 9, 2014
Journal IET Renewable Power Generation
Print ISSN 1752-1416
Electronic ISSN 1752-1424
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
Volume 8
Issue 4
Pages 380-389


Accepted Journal Article (1.4 Mb)

Copyright Statement
This paper is a postprint of a paper submitted to and accepted for publication in IET renewable power generation and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.

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