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dc.contributor.authorMohamed, A. A.
dc.contributor.authorNeilson, R. D.
dc.contributor.authorDeans, W. F.
dc.contributor.authorMacConnell, P.
dc.date.accessioned2015-02-01T00:00:47Z
dc.date.available2015-02-01T00:00:47Z
dc.date.issued2014-02
dc.identifier.citationMohamed , A A , Neilson , R D , Deans , W F & MacConnell , P 2014 , ' Crack detection in a rotating shaft using artificial neural networks and PSD characterisation ' , Meccanica , vol. 49 , no. 2 , pp. 255-266 . https://doi.org/10.1007/s11012-013-9790-zen
dc.identifier.issn0025-6455
dc.identifier.otherPURE: 25542555
dc.identifier.otherPURE UUID: 3e2bdfe8-9857-4689-acea-140e3b54d7b5
dc.identifier.otherScopus: 84893902026
dc.identifier.urihttp://hdl.handle.net/2164/4219
dc.format.extent12
dc.language.isoeng
dc.relation.ispartofMeccanicaen
dc.rightsThe final publication is available at Springer via http://dx.doi.org/10.1007/s11012-013-9790-zen
dc.subjectcondition health monitoringen
dc.subjectcrack detectionen
dc.subjectstatistical analysisen
dc.subjectvibrationen
dc.subjectsignal processingen
dc.subjectneural networken
dc.subjectTC Hydraulic engineering. Ocean engineeringen
dc.subject.lccTCen
dc.titleCrack detection in a rotating shaft using artificial neural networks and PSD characterisationen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Engineeringen
dc.contributor.institutionUniversity of Aberdeen.COPS Administrationen
dc.contributor.institutionUniversity of Aberdeen.Energyen
dc.contributor.institutionUniversity of Aberdeen.Engineering (Research Theme)en
dc.description.statusPeer revieweden
dc.description.versionPostprinten
dc.identifier.doihttps://doi.org/10.1007/s11012-013-9790-z
dc.date.embargoedUntil2015-02-01


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