Multivariate statistical methods for detection of spur gear faults

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dc.contributor.authorYuzukirmizi, Mustafa
dc.contributor.authorArslan, Hakan
dc.contributor.authorDuman, Oznur
dc.date.accessioned2020-06-25T18:12:48Z
dc.date.available2020-06-25T18:12:48Z
dc.date.issued2015
dc.departmentKırıkkale Üniversitesi
dc.descriptionArslan, Hakan/0000-0002-2019-1882;
dc.description.abstractIn this study, multivariate statistical techniques are experimented for a spur gear system and a methodology is proposed. The approach is based on the analysis of multidimensional gear vibration data without any feature extradiction and data transformation. The scheme is performed using the vibration signals acquired from a lab-scale single stage gearbox in three dimensions of x, y and z directions. As a groundwork, multi-normality assumptions are established using homogeneity, autocorrelation, and univariate normality tests. The bi-dimensional frequency histograms are also plotted to show bi-normality for experimental gear data. Then, mean vectors and covariance matrices of conditions of good, worn, 1-tooth broken from wheel gear and 1-tooth broken from each pinion and wheel gear are estimated. To compare gear conditions statistically, multivariate analysis of variance is proposed and applied. Moreover, the single metric of Mahalanobis distances are calculated to classify unknown test samples, utilizing the maximum likelihood estimates. The numerical results indicate that multivariate statistical analysis techniques can be applied in early detection of spur gear faults, in which univariate tests fail.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1177/0954406214561050
dc.identifier.endpage2598en_US
dc.identifier.issn0954-4062
dc.identifier.issn2041-2983
dc.identifier.issue14en_US
dc.identifier.scopus2-s2.0-84942134687
dc.identifier.scopusqualityQ2
dc.identifier.startpage2586en_US
dc.identifier.urihttps://doi.org/10.1177/0954406214561050
dc.identifier.urihttps://hdl.handle.net/20.500.12587/6048
dc.identifier.volume229en_US
dc.identifier.wosWOS:000361762000008
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSage Publications Ltden_US
dc.relation.ispartofProceedings Of The Institution Of Mechanical Engineers Part C-Journal Of Mechanical Engineering Science
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGear faultsen_US
dc.subjectvibration signalsen_US
dc.subjectsignal processingen_US
dc.subjectmultivariate statistical analysisen_US
dc.titleMultivariate statistical methods for detection of spur gear faultsen_US
dc.typeArticle

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