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

Content Provider	IET Digital Library
Author	Zappalá, Donatella Tavner, Peter J. Crabtree, Christopher J. Sheng, Shuangwen
Abstract	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.
Starting Page	380
Ending Page	389
Page Count	10
ISSN	17521416
Volume Number	8
e-ISSN	17521424
Issue Number	Issue 4, May (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/8/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2013.0177
Journal	IET Renewable Power Generation
Publisher Date	2014-04-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automatic Wind Turbine Gearbox Fault Detection CMS Condition Monitoring Cost Minimisation Cost Reduction Data Monitoring Durham Condition Monitoring Test Rig Fault Diagnosis Gear Damage Detection Gear Damage Evaluation Gearbox Condition Monitoring System Gears National Renewable Energy Laboratory Programme Offshore Installation Offshore Installations Power Generation Economics Power Generation Fault Power Generation Reliability Power System Measurement Power System Measurement And Metering Reliability Side-band Algorithm Wind Energy Wind Industry Wind Power Plant Wind Turbine WT
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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