DFIG current and controller signals' angular shaft misalignment signature' an experimental case study

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dc.authorscopusid57203749642
dc.authorscopusid57189095244
dc.authorscopusid57191381233
dc.authorscopusid26430653900
dc.contributor.authorWang, Y.
dc.contributor.authorSarma, N.
dc.contributor.authorMohammed, A.
dc.contributor.authorDjurovic, S.
dc.date.accessioned2021-12-01T18:39:00Z
dc.date.available2021-12-01T18:39:00Z
dc.date.issued2020
dc.department[Belirlenecek]en_US
dc.descriptionIEEE Industrial Electronics Society (IES);The Institute of Electrical and Electronics Engineers (IEEE)en_US
dc.description2020 International Conference on Electrical Machines, ICEM 2020 -- 23 August 2020 through 26 August 2020 -- -- 165584en_US
dc.description.abstractwith the continuous increase in wind turbine generator size the monitoring and diagnosis of drive train shaft misalignment is of growing importance, as this condition contributes to as much as 30% of turbine's downtime. Machine current signature analysis has been widely investigated in conventional machinery as a non-invasive diagnostic tool for shaft misalignment, via spectrum analysis of the stator current signal. This paper reports a practical case study of misalignment fault signature manifestation in the doubly-fed induction generator (DFIG) controller signals spectra, with a view to assessing the feasibility of low cost and non-invasive controller signal analysis based misalignment diagnosis. The study employs a laboratory test rig to undertake a series of tests to analyze the sensitivity of controller signals to a specific angular misalignment condition, and hence evaluate and characterize the manifestation of its spectral signatures. © 2020 IEEE.en_US
dc.description.sponsorshipEP/P009743/1; Engineering and Physical Sciences Research Council, EPSRCen_US
dc.description.sponsorship?This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) HOME-Offshore: Holistic Operation and Maintenance for Energy from Offshore Wind Farms Consortium under grant EP/P009743/1.) Y. Wang, A. Mohammed and S. Djurovi are with University of Manchester, School of Electrical and Electronic Engineering, Manchester, U.K. (email: yingzhao.wang@manchester.ac.uk) N .Sarma is with Duzce University, Department of Electrical and Electronic Engineering, Duzce, Turkey.en_US
dc.identifier.doi10.1109/ICEM49940.2020.9271062
dc.identifier.endpage1327en_US
dc.identifier.isbn9781728199450
dc.identifier.scopus2-s2.0-85098643569en_US
dc.identifier.startpage1321en_US
dc.identifier.urihttps://doi.org/10.1109/ICEM49940.2020.9271062
dc.identifier.urihttps://hdl.handle.net/20.500.12684/9958
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 2020 International Conference on Electrical Machines, ICEM 2020en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAngular misalignmenten_US
dc.subjectCondition monitoringen_US
dc.subjectControl signals signature analysisen_US
dc.subjectDFIG shaft misalignmenten_US
dc.subjectMotor current signature analysis (MCSA)en_US
dc.titleDFIG current and controller signals' angular shaft misalignment signature' an experimental case studyen_US
dc.typeConference Objecten_US

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