Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/76241
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Campo DCValorIdioma
dc.contributor.authorVairinhos, Valter-
dc.contributor.authorParreira, Rui-
dc.contributor.authorLampreia, Suzana-
dc.contributor.authorLobo, Vítor-
dc.contributor.authorGalindo, Purificación-
dc.date.accessioned2019-07-22T22:46:17Z-
dc.date.available2019-07-22T22:46:17Z-
dc.date.issued2018-01-01-
dc.identifier.issn2153-2648-
dc.identifier.otherPURE: 14188471-
dc.identifier.otherPURE UUID: c0cd3184-3dec-4d58-8485-d292b93fbd6c-
dc.identifier.otherScopus: 85068446463-
dc.identifier.otherORCID: /0000-0002-0149-3367/work/63927715-
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85068446463&partnerID=8YFLogxK-
dc.descriptionVairinhos, V., Parreira, R., Lampreia, S., Lobo, V., & Galindo, P. (2018). Vibration analysis based on HJ-biplots. International Journal of Prognostics and Health Management, 9(2), [030].-
dc.description.abstractVibration Analysis (VA) is now routinely used for condition monitoring and failure diagnosis in Condition Based Maintenance (CBM). In the context of VA, a methodology is proposed, based on biplots, to simultaneously display both vibration frequencies and their measurement points, in support of monitoring and diagnostics tasks. In this research, real observational data obtained measuring mechanical vibrations on four generators aboard a Portuguese Navy Ship in real operating conditions is used. A portable vibration collector was employed, and the measurements were taken at 13 measurement points in each one of four generators, using the same collector settings. Spectrograms resulting from vibration measurements were transformed into biplots and used for decision support according to the proposed methodology. Data analysis showed a robust stability in the macrostructure of biplots when observations resulting from different generators of the same model and at the same assumed conditions was analyzed. This invariance allows the specification of reference conditions, rules to detect changes of operating conditions and the emergence of failures. The proposed methodology, once embedded in dedicated software, will reduce the interpretation error in diagnosis and prognosis associated to variability in personnel training and experience. Consequently, it will increase the safe use of VA in an increasing number of situations.en
dc.format.extent10-
dc.language.isoeng-
dc.rightsopenAccess-
dc.subjectCBM-
dc.subjectVibration analysis-
dc.subjectInterpretation-
dc.subjectsensor-
dc.subjectBiplot-
dc.subjectperiodogram-
dc.subjectobservational data-
dc.subjectComputer Science (miscellaneous)-
dc.subjectCivil and Structural Engineering-
dc.subjectSafety, Risk, Reliability and Quality-
dc.subjectEnergy Engineering and Power Technology-
dc.subjectMechanical Engineering-
dc.titleVibration analysis based on HJ-biplots-
dc.typearticle-
degois.publication.issue2-
degois.publication.titleInternational Journal of Prognostics and Health Management-
degois.publication.volume9-
dc.peerreviewedyes-
dc.identifier.doihttps://doi.org/10.36001/ijphm.2018.v9i2.2739-
dc.description.versionpublishersversion-
dc.description.versionpublished-
dc.contributor.institutionNOVA Information Management School (NOVA IMS)-
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School-
Aparece nas colecções:NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)

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