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A text-mining approach to assess the failure condition of wind turbines using maintenance service history

Author
Blanco, A.; Marti, P.; Gibert, Karina; Cusido, J.; Sole, J.
Type of activity
Journal article
Journal
Energies
Date of publication
2019-05-23
Volume
12
Number
10
First page
1
Last page
20
DOI
10.3390/en12101982
Repository
http://hdl.handle.net/2117/165840 Open in new window
URL
https://www.mdpi.com/1996-1073/12/10/1982 Open in new window
Abstract
Detecting and determining which systems or subsystems of a wind turbine have more failures is essential to improve their design, which will reduce the costs of generating wind power. Two of the most critical failures, the generator and gearbox, are analyzed and characterized with four metrics. This failure analysis usually begins with the identification of the turbine’s condition, a process normally performed by an expert examining the wind turbine’s service history. This is a time-consuming...
Citation
Blanco, A. [et al.]. A text-mining approach to assess the failure condition of wind turbines using maintenance service history. "Energies", 23 Maig 2019, vol. 12, núm. 10, p. 1-20.
Keywords
classification, fault diagnosis, renewable energy, service history, text mining, wind turbine
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
KEMLG - Knowledge Engineering and Machine Learning Group

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