The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Monitoring wind turbine gearboxes
Open accessAbstract
Concerns amongst wind turbine (WT) operators about gearbox reliability arise from complex repair procedures, high replacement costs and long downtimes leading to revenue losses. Therefore, reliable monitoring for the detection, diagnosis and prediction of such faults are of great concerns to the wind industry. Monitoring of WT gearboxes has gained importance as WTs become larger and move to more inaccessible locations. This paper summarizes typical WT gearbox failure modes and reviews supervisory control and data acquisition (SCADA) and condition monitoring system (CMS) approaches for monitoring them. It then presents two up‐to‐date monitoring case studies, from different manufacturers and types of WT, using SCADA and CMS signals. The first case study, applied to SCADA data, starts from basic laws of physics applied to the gearbox to derive robust relationships between temperature, efficiency, rotational speed and power output. The case study then applies an analysis, based on these simple principles, to working WTs using SCADA oil temperature rises to predict gearbox failure. The second case study focuses on CMS data and derives diagnostic information from gearbox vibration amplitudes and oil debris particle counts against energy production from working WTs. The results from the two case studies show how detection, diagnosis and prediction of incipient gearbox failures can be carried out using SCADA and CMS signals for monitoring although each technique has its particular strengths. It is proposed that in the future, the wind industry should consider integrating WT SCADA and CMS data to detect, diagnose and predict gearbox failures.Copyright © 2012 John Wiley & Sons, Ltd.
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Cites
Reliability of wind turbine subassemblies
Spinato, F., Tavner, P. J., van Bussel, G. J. W., & Koutoulakos, E. (2009) · IET Renewable Power Generation · doi:10.1049/iet-rpg.2008.0060 · Cited by 646
Self-citationReview of condition monitoring of rotating electrical machines
Tavner, P. J. (2008) · IET Electric Power Applications · doi:10.1049/iet-epa:20070280 · Cited by 531
Self-citationReliability analysis for wind turbines
Tavner, P. J., Xiang, J., & Spinato, F. (2007) · Wind Energy · doi:10.1002/we.204 · Cited by 494
Self-citationWind turbine condition monitoring: technical and commercial challenges
Yang, W., Tavner, P. J., Crabtree, C. J., Feng, Y., & Qiu, Y. (2014) · Wind Energy · doi:10.1002/we.1508 · Cited by 474
Self-citationOnline wind turbine fault detection through automated SCADA data analysis
Zaher, A., McArthur, S. D. J., Infield, D. G., & Patel, Y. (2009) · Wind Energy · doi:10.1002/we.319 · Cited by 464
Wind Turbine Generator Condition-Monitoring Using Temperature Trend Analysis
Guo, P., Infield, D., & Yang, X. (2012) · IEEE Transactions on Sustainable Energy · doi:10.1109/tste.2011.2163430 · Cited by 198
Condition monitoring and fault diagnosis of a wind turbine synchronous generator drive train
Yang, W., Tavner, P. J., & Wilkinson, M. R. (2009) · IET Renewable Power Generation · doi:10.1049/iet-rpg:20080006 · Cited by 192
Self-citationPhysics of Failure approach to wind turbine condition based maintenance
Gray, C. S., & Watson, S. J. (2009) · Wind Energy · doi:10.1002/we.360 · Cited by 150
Wind turbine SCADA alarm analysis for improving reliability
Qiu, Y., Feng, Y., Tavner, P., Richardson, P., Erdős, G., & Chen, B. (2011) · Wind Energy · doi:10.1002/we.513 · Cited by 123
Self-citationUse of SCADA and CMS signals for failure detection and diagnosis of a wind turbine gearbox
Feng, Y., Qiu, Y., Crabtree, C., Long, H., & Tavner, P. J. (2011) · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · Cited by 58
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Cited by
Igba, J., Alemzadeh, K., Durugbo, C., & Eiriksson, E. T. (2016) · Renewable Energy · doi:10.1016/j.renene.2016.01.006 · Cited by 177
Metadata
- Authors
- Feng, Y., Qiu, Y., Crabtree, C. J., Long, H., & Tavner, P. J.
- Venue
- Wind Energy
- Publisher
- Wiley
- Published
- 2012-07-17
- Volume
- 16
- Issue
- 5
- Pages
- 728-740
- ISSN
- 1095-4244 (ISSN-L)
- 1099-1824
- OpenAlex
- W1769140016
- Cited by
- 253
- References
- 13
- FWCI
- 16.23
- Type
- journal article
- Language
- en
- Open access
- green
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