Electrical & mechanical diagnostic indicators of wind turbine induction generator rotor faults

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dc.contributor.authorZappala, Donatella
dc.contributor.authorSarma, Nur
dc.contributor.authorDjurovic, Sinisa
dc.contributor.authorCrabtree, Cristopher J.
dc.contributor.authorMohammad, Anees
dc.contributor.authorTavner, P.J.
dc.date.accessioned2020-05-01T09:12:11Z
dc.date.available2020-05-01T09:12:11Z
dc.date.issued2019
dc.departmentDÜ, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.descriptionMohammed, Anees/0000-0003-3281-7878; Zappala', Donatella/0000-0002-8283-5102; Crabtree, Christopher/0000-0003-0109-5323en_US
dc.descriptionWOS: 000449892600002en_US
dc.description.abstractIn MW-sized wind turbines, the most widely-used generator is the wound rotor induction machine, with a partially-rated voltage source converter connected to the rotor. This generator is a significant cause of wind turbine fault modes. In this paper, a harmonic time-stepped generator model is applied to derive wound rotor induction generator electrical & mechanical signals for fault measurement, and propose simple closed-form analytical expressions to describe them. Predictions are then validated with tests on a 30 kW induction generator test rig. Results show that generator rotor unbalance produces substantial increases in the side-bands of supply frequency and slotting harmonic frequencies in the spectra of current, power, speed, mechanical torque and vibration measurements. It is believed that this is the first occasion in which such comprehensive approach has been presented for this type of machine, with healthy & faulty conditions at varying loads and rotor faults. Clear recommendations of the relative merits of various electrical & mechanical signals for detecting rotor faults are given, and reliable fault indicators are identified for incorporation into wind turbine condition monitoring systems. Finally, the paper proposes that fault detectability and reliability could be improved by data fusion of some of these electrical & mechanical signals. (C) 2018 The Authors. Published by Elsevier Ltd.en_US
dc.description.sponsorshipUK EPSRC SUPERGEN Wind HubEngineering & Physical Sciences Research Council (EPSRC) [EP/L014106/1]en_US
dc.description.sponsorshipThis work was funded as part of the UK EPSRC SUPERGEN Wind Hub, EP/L014106/1. The data presented in this paper are available from the Durham Research Online Data Depository at https://doi.org/10.15128/r28049g5063.en_US
dc.identifier.doi10.1016/j.renene.2018.06.098en_US
dc.identifier.endpage24en_US
dc.identifier.issn0960-1481
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage14en_US
dc.identifier.urihttps://doi.org/10.1016/j.renene.2018.06.098
dc.identifier.urihttps://hdl.handle.net/20.500.12684/5900
dc.identifier.volume131en_US
dc.identifier.wosWOS:000449892600002en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofRenewable Energyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectWind turbineen_US
dc.subjectCondition monitoringen_US
dc.subjectDoubly-fed induction generator (DFIG)en_US
dc.subjectElectrical & mechanical signature analysisen_US
dc.subjectRotor electrical unbalanceen_US
dc.subjectFault indicatoren_US
dc.titleElectrical & mechanical diagnostic indicators of wind turbine induction generator rotor faultsen_US
dc.typeArticleen_US

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