A data-based technique for monitoring of wound rotor induction machines: A simulation study

Handle URI:
http://hdl.handle.net/10754/609006
Title:
A data-based technique for monitoring of wound rotor induction machines: A simulation study
Authors:
Harrou, Fouzi; Ramahaleomiarantsoa, Jacques F.; Nounou, Mohamed N.; Nounou, Hazem N.
Abstract:
Detecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM). The proposed fault detection approach is based on the use of principal components analysis (PCA). However, conventional PCA-based detection indices, such as the T2T2 and the Q statistics, are not well suited to detect small faults because these indices only use information from the most recent available samples. Detection of small faults is one of the most crucial and challenging tasks in the area of fault detection and diagnosis. In this paper, a new statistical system monitoring strategy is proposed for detecting changes resulting from small shifts in several variables associated with WRIM. The proposed approach combines modeling using PCA modeling with the exponentially weighted moving average (EWMA) control scheme. In the proposed approach, EWMA control scheme is applied on the ignored principal components to detect the presence of faults. The performance of the proposed method is compared with those of the traditional PCA-based fault detection indices. The simulation results clearly show the effectiveness of the proposed method over the conventional ones, especially in the presence of faults with small magnitudes.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
A data-based technique for monitoring of wound rotor induction machines: A simulation study 2016 Engineering Science and Technology, an International Journal
Publisher:
Elsevier BV
Journal:
Engineering Science and Technology, an International Journal
Issue Date:
9-May-2016
DOI:
10.1016/j.jestch.2016.04.008
Type:
Article
ISSN:
22150986
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S2215098615302020
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorHarrou, Fouzien
dc.contributor.authorRamahaleomiarantsoa, Jacques F.en
dc.contributor.authorNounou, Mohamed N.en
dc.contributor.authorNounou, Hazem N.en
dc.date.accessioned2016-05-11T07:39:29Zen
dc.date.available2016-05-11T07:39:29Zen
dc.date.issued2016-05-09en
dc.identifier.citationA data-based technique for monitoring of wound rotor induction machines: A simulation study 2016 Engineering Science and Technology, an International Journalen
dc.identifier.issn22150986en
dc.identifier.doi10.1016/j.jestch.2016.04.008en
dc.identifier.urihttp://hdl.handle.net/10754/609006en
dc.description.abstractDetecting faults induction machines is crucial for a safe operation of these machines. The aim of this paper is to present a statistical fault detection methodology for the detection of faults in three-phase wound rotor induction machines (WRIM). The proposed fault detection approach is based on the use of principal components analysis (PCA). However, conventional PCA-based detection indices, such as the T2T2 and the Q statistics, are not well suited to detect small faults because these indices only use information from the most recent available samples. Detection of small faults is one of the most crucial and challenging tasks in the area of fault detection and diagnosis. In this paper, a new statistical system monitoring strategy is proposed for detecting changes resulting from small shifts in several variables associated with WRIM. The proposed approach combines modeling using PCA modeling with the exponentially weighted moving average (EWMA) control scheme. In the proposed approach, EWMA control scheme is applied on the ignored principal components to detect the presence of faults. The performance of the proposed method is compared with those of the traditional PCA-based fault detection indices. The simulation results clearly show the effectiveness of the proposed method over the conventional ones, especially in the presence of faults with small magnitudes.en
dc.language.isoenen
dc.publisherElsevier BVen
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S2215098615302020en
dc.rightsArchived with thanks to Engineering Science and Technology, an International Journal. Under a Creative Commons license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectFault detectionen
dc.subjectWound rotor induction machinesen
dc.subjectPrincipal components analysisen
dc.subjectEWMA control schemeen
dc.subjectHotelling T2T2 statisticen
dc.subjectQ statisticen
dc.titleA data-based technique for monitoring of wound rotor induction machines: A simulation studyen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalEngineering Science and Technology, an International Journalen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionUniversité de Corse, U.M.R. CNRS 6134 SPE, BP 52, Corte, Franceen
dc.contributor.institutionChemical Engineering Program, Texas A&M University at Qatar, Doha, Qataren
dc.contributor.institutionElectrical and Computer Engineering Program, Texas A&M University at Qatar, Doha, Qataren
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorHarrou, Fouzien
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