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Condition monitoring of wind turbines: Techniques and methods

EC| NIMO
Authors:
Fausto Pedro García Márquez;
Andrew M. Tobias;
Jesús María Pinar Pérez;
Mayorkinos Papaelias;

Fausto Pedro García Márquez
Fausto Pedro García Márquez in OpenAIRE

Jesús María Pinar Pérez
Jesús María Pinar Pérez in OpenAIRE

Mayorkinos Papaelias
Mayorkinos Papaelias in OpenAIRE
Abstract
Wind Turbines (WT) are one of the fastest growing sources of power production in the world today and there is a constant need to reduce the costs of operating and maintaining them. Condition monitoring (CM) is a tool commonly employed for the early detection of faults/failures so as to minimise downtime and maximize productivity. This paper provides a review of the state-of-the-art in the CM of wind turbines, describing the different maintenance strategies, CM techniques and methods, and highlighting in a table the various combinations of these that have been reported in the literature. Future research opportunities in fault diagnostics are identified using a qualitative fault tree analysis.
Related Organizations
- University of Birmingham United Kingdom
- University of Castile-La Mancha Spain
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).717 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 0.1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 0.1%

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citations
Citations provided by BIP!
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
popularity
Popularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
717
Top 0.1%
Top 0.1%
Top 0.1%
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Beta
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