A data-driven algorithm for online detection of component and system faults in modern wind turbines at different operating zones

Simple item page
dc.contributor.authorBakdi, Azzeddine
dc.contributor.authorKouadri, Abdelmalek
dc.contributor.authorMekhilef, Saad
dc.date.accessioned2019-02-12T08:31:36Z
dc.date.available2019-02-12T08:31:36Z
dc.date.issued2019
dc.identifier.issn1364-0321
dc.identifier.urihttps://dspace.univ-boumerdes.dz/handle/123456789/5395
dc.identifier.urihttps://doi.org/10.1016/j.rser.2019.01.013
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofseriesRenewable and Sustainable Energy Reviews/ Vol.103 (2019);pp. 546-555
dc.subjectWind turbine benchmarken_US
dc.subjectData-driven fault detectionen_US
dc.subjectDrivetrain vibrationen_US
dc.subjectHydraulic blade pitch faulten_US
dc.subjectSpeed/position sensor faulten_US
dc.subjectPump/torque controller faulten_US
dc.titleA data-driven algorithm for online detection of component and system faults in modern wind turbines at different operating zonesen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Azzeddine Bakdi, résumé.pdf
Size:
33.92 KB
Format:
Adobe Portable Document Format
Download

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Publications Internationales