The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
The prediction and diagnosis of wind turbine faults
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Citations
Cites
Condition monitoring and fault detection of wind turbines and related algorithms: A review
Hameed, Z., Hong, Y. S., Cho, Y. M., Ahn, S. H., & Song, C. K. (2009) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2007.05.008 · Cited by 995
Support vector machines for wind speed prediction
Mohandes, M. A., Halawani, T. O., Rehman, S., & Hussain, A. A. (2004) · Renewable Energy · doi:10.1016/j.renene.2003.11.009 · Cited by 755
A review of recent advances in wind turbine condition monitoring and fault diagnosis
Lu, B., Li, Y., Wu, X., & Yang, Z. (2009) · IEEE Power Electronics and Machines in Wind Applications (PEMWA) · doi:10.1109/pemwa.2009.5208325 · Cited by 584
Short-Term Prediction of Wind Farm Power: A Data Mining Approach
Kusiak, A., Zheng, H., & Song, Z. (2009) · IEEE Transactions on Energy Conversion · doi:10.1109/tec.2008.2006552 · Cited by 339
Self-citationSIMAP: Intelligent System for Predictive Maintenance
Garcia, M. C., Sanz-Bobi, M. A., & del Pico, J. (2006) · Computers in Industry · doi:10.1016/j.compind.2006.02.011 · Cited by 313
Wind turbine reliability :understanding and minimizing wind turbine operation and maintenance costs.
Walford, C. (2006) · doi:10.2172/882048 · Cited by 277
On-line monitoring of power curves
Kusiak, A., Zheng, H., & Song, Z. (2009) · Renewable Energy · doi:10.1016/j.renene.2008.10.022 · Cited by 233
Self-citationCondition monitoring and prognosis of utility scale wind turbines
Hyers, R. W., Mcgowan, J. G., Sullivan, K. L., Manwell, J. F., & Syrett, B. C. (2006) · Energy Materials · doi:10.1179/174892406x163397 · Cited by 191
Condition monitoring benefit for onshore wind turbines: sensitivity to operational parameters
McMillan, D., & Ault, G. W. (2008) · IET Renewable Power Generation · doi:10.1049/iet-rpg:20070064 · Cited by 161
Dynamic control of wind turbines
Kusiak, A., Li, W., & Song, Z. (2009) · Renewable Energy · doi:10.1016/j.renene.2009.05.022 · Cited by 84
Self-citation
Cited by
High-power wind energy conversion systems: State-of-the-art and emerging technologies
Yaramasu, V., Wu, B., Sen, P. C., Kouro, S., & Narimani, M. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2014.2378692 · Cited by 991
Machine learning methods for wind turbine condition monitoring: A review
Stetco, A., Dinmohammadi, F., Zhao, X., Robu, V., Flynn, D., Barnes, M., Keane, J., & Nenadic, G. (2019) · Renewable Energy · doi:10.1016/j.renene.2018.10.047 · Cited by 831
A survey on industrial applications of fuzzy control
Precup, R.-E., & Hellendoorn, H. (2011) · Computers in Industry · doi:10.1016/j.compind.2010.10.001 · Cited by 532
Using SCADA data for wind turbine condition monitoring – a review
Tautz‐Weinert, J., & Watson, S. J. (2017) · IET Renewable Power Generation · doi:10.1049/iet-rpg.2016.0248 · Cited by 458
Badihi, H., Zhang, Y., Jiang, B., Pillay, P., & Rakheja, S. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3171691 · Cited by 319
Metadata
- Authors
- Kusiak, A., & Li, W.
- Venue
- Renewable Energy
- Publisher
- Elsevier BV
- Published
- 2011-01
- Volume
- 36
- Issue
- 1
- Pages
- 16-23
- ISSN
- 0960-1481 (ISSN-L)
- OpenAlex
- W1964522863
- Cited by
- 454
- References
- 12
- FWCI
- 32.93
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Kusiak, A., & Li, W. (2011). The prediction and diagnosis of wind turbine faults. Renewable Energy. https://doi.org/10.1016/j.renene.2010.05.014
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
