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Condition 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

Abstract

The state of the art in condition monitoring in wind turbines, and related technologies currently applied in practice and under development for aerospace applications, are reviewed. Condition monitoring systems estimate the current condition of a machine from sensor measurements, whereas prognosis systems give a probabilistic forecast of the future condition of the machine under the projected usage conditions. Current condition monitoring practice in wind turbine rotors involves tracking rotor imbalance, aerodynamic asymmetry, surface roughness and overall performance and offline and online measurements of stress and strain. Related technologies for monitoring of load history and fatigue crack growth in aircraft structures are evaluated for their applicability to wind turbine blades. Similarly, condition monitoring practice in wind turbines is compared with monitoring and prognosis in helicopter gearboxes. The state of the art in condition monitoring of electronic controls, power electronics and towers is also evaluated and compared with the state of the art in aerospace. Based on these comparisons, technology needs and future challenges for the development of condition monitoring and prognosis for large wind machines, both onshore and offshore, are summarised.

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Metadata

Authors
Hyers, R. W., Mcgowan, J. G., Sullivan, K. L., Manwell, J. F., & Syrett, B. C.
Venue
Energy Materials
Published
2006-09
Volume
1
Issue
3
Pages
187-203
ISSN
  • 1748-9237 (ISSN-L)
  • 1748-9245
OpenAlex
W2029783486
Cited by
191
References
0
FWCI
3.00
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Condition monitoring and prognosis of utility scale wind turbines. https://app.cochat.ai/papers/10.1179/174892406x163397
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Hyers, R. W., Mcgowan, J. G., Sullivan, K. L., Manwell, J. F., & Syrett, B. C. (2006). Condition monitoring and prognosis of utility scale wind turbines. Energy Materials. https://doi.org/10.1179/174892406x163397

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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.