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Combining Drone-based Monitoring and Machine Learning for Online Reliability Evaluation of Wind Turbines

Yes / The offshore wind energy is increasingly becoming an attractive source of energy due to having lower environmental impact. Effective operation and maintenance that ensures the maximum availability of the energy generation process using offshore facilities and minimal production cost are two key factors to improve the competitiveness of this energy source over other traditional sources of energy. Condition monitoring systems are widely used for health management of offshore wind farms to have improved operation and maintenance. Reliability of the wind farms are increasingly being evaluated to aid in the maintenance process and thereby to improve the availability of the farms. However, much of the reliability analysis is performed offline based on statistical data. In this article, we propose a drone-assisted monitoring based method for online reliability evaluation of wind turbines. A blade system of a wind turbine is used as an illustrative example to demonstrate the proposed approach. / SURE Grant scheme. SESAME H2020 Project under Grant 101017258.

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/19141
Date01 September 2022
CreatorsKabir, Sohag, Aslansefat, K., Gope, P., Campean, Felician, Papadopoulos, Y.
PublisherIEEE
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeConference paper, Accepted manuscript
Rights(c) 2022 IEEE. Full-text reproduced in accordance with the publisher's self-archiving policy., Unspecified

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