The DOI matches its Crossref record; 224 of the 224 references it cites were found in a registry or an index.
A Comprehensive Review on Signal-Based and Model-Based Condition Monitoring of Wind Turbines: Fault Diagnosis and Lifetime Prognosis
Open accessAbstract
Wind turbines play an increasingly important role in renewable power generation. To ensure the efficient production and financial viability of wind power, it is crucial to maintain wind turbines’ reliability and availability (uptime) through advanced real-time condition monitoring technologies. Given their plurality and evolution, this article provides an updated comprehensive review of the state-of-the-art condition monitoring technologies used for fault diagnosis and lifetime prognosis in wind turbines. Specifically, this article presents the major fault and failure modes observed in wind turbines along with their root causes, and thoroughly reviews the techniques and strategies available for wind turbine condition monitoring from signal-based to model-based perspectives. In total, more than 390 references, mostly selected from recent journal articles, theses, and reports in the open literature, are compiled to assess as exhaustively as possible the past, current, and future research and development trends in this substantial and active investigation area.
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Cites
1 retracted
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Beyond the Kalman filter particle filters for tracking applications
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Bibliographical review on reconfigurable fault-tolerant control systems
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Metadata
- Authors
- Badihi, H., Zhang, Y., Jiang, B., Pillay, P., & Rakheja, S.
- Venue
- Proceedings of the IEEE
- Published
- 2022-06
- Volume
- 110
- Issue
- 6
- Pages
- 754-806
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W4285306189
- Cited by
- 319
- References
- 224
- FWCI
- 23.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- The paper
- Badihi, H., Zhang, Y., Jiang, B., Pillay, P., & Rakheja, S. (2022). A Comprehensive Review on Signal-Based and Model-Based Condition Monitoring of Wind Turbines: Fault Diagnosis and Lifetime Prognosis. Proceedings of the IEEE. https://doi.org/10.1109/jproc.2022.3171691
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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