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dc.contributor.authorKabir, Sohag
dc.contributor.authorAslansefat, K.
dc.contributor.authorGope, P.
dc.contributor.authorCampean, Felician
dc.contributor.authorPapadopoulos, Y.
dc.date.accessioned2022-09-01T07:34:18Z
dc.date.accessioned2022-09-21T10:08:54Z
dc.date.available2022-09-01T07:34:18Z
dc.date.available2022-09-21T10:08:54Z
dc.date.issued2022-08
dc.identifier.citationKabir S, Aslansefat K. Gope P et al (2022) Combining Drone-based Monitoring and Machine Learning for Online Reliability Evaluation of Wind Turbines. IEEE International Conference on Computing, Electronics & Communications Engineering. 17-18 Aug 2022. Southend, UK.en_US
dc.identifier.urihttp://hdl.handle.net/10454/19141
dc.descriptionYesen_US
dc.description.abstractThe 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.en_US
dc.description.sponsorshipSURE Grant scheme. SESAME H2020 Project under Grant 101017258.en_US
dc.language.isoenen_US
dc.publisherIEEE
dc.rights(c) 2022 IEEE. Full-text reproduced in accordance with the publisher's self-archiving policy.en_US
dc.subjectBayesian networken_US
dc.subjectMachine learningen_US
dc.subjectOffshore wind industryen_US
dc.subjectReliabilityen_US
dc.subjectUAVen_US
dc.titleCombining Drone-based Monitoring and Machine Learning for Online Reliability Evaluation of Wind Turbinesen_US
dc.status.refereedYesen_US
dc.typeConference paperen_US
dc.type.versionAccepted manuscripten_US
dc.identifier.doihttps://doi.org/10.1109/iCCECE55162.2022.9875095
dc.rights.licenseUnspecifieden_US
dc.date.updated2022-09-01T07:34:20Z
refterms.dateFOA2022-09-21T10:09:16Z
dc.openaccess.statusembargoedAccessen_US


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