Publication:

Wind Turbine Hybrid Physics-Based Deep Learning Model for a Health Monitoring Approach Considering Provision of Ancillary Services

 
dc.contributor.authorKayedpour, Nezmin
dc.contributor.authorQing, Jixiang
dc.contributor.authorWauters, Jolan
dc.contributor.authorDe Kooning, Jeroen D. M.
dc.contributor.authorCouckuyt, Ivo
dc.contributor.authorCrevecoeur, Guillaume
dc.contributor.imecauthorCouckuyt, Ivo
dc.contributor.imecauthorQing, Jixiang
dc.contributor.orcidimecCouckuyt, Ivo::0000-0002-9524-4205
dc.contributor.orcidimecQing, Jixiang::0000-0002-6446-6286
dc.date.accessioned2024-08-29T10:34:13Z
dc.date.available2024-04-20T18:27:13Z
dc.date.available2024-04-22T10:14:10Z
dc.date.available2024-08-29T10:34:13Z
dc.date.embargo9999-12-31
dc.date.issued2024
dc.description.wosFundingTextNo Statement Available
dc.identifier.doi10.1109/TIM.2024.3375416
dc.identifier.issn0018-9456
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/43857
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.source.beginpageArt. 2513814
dc.source.endpageN/A
dc.source.issue/
dc.source.journalIEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
dc.source.numberofpages14
dc.source.volume73
dc.subject.keywordsANOMALY DETECTION
dc.subject.keywordsPOWER
dc.subject.keywordsLSTM
dc.title

Wind Turbine Hybrid Physics-Based Deep Learning Model for a Health Monitoring Approach Considering Provision of Ancillary Services

dc.typeJournal article
dspace.entity.typePublication
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