Crack detection in a rotating shaft using artificial neural networks and PSD characterisation

dc.contributor.author	Mohamed, A. A.
dc.contributor.author	Neilson, R. D.
dc.contributor.author	Deans, W. F.
dc.contributor.author	MacConnell, P.
dc.contributor.institution	University of Aberdeen.Engineering	en
dc.contributor.institution	University of Aberdeen.COPS Administration	en
dc.contributor.institution	University of Aberdeen.Energy	en
dc.date.accessioned	2015-02-01T00:00:47Z
dc.date.available	2015-02-01T00:00:47Z
dc.date.embargoedUntil	2015-02-01
dc.date.issued	2014-02
dc.description.status	Peer reviewed	en
dc.format.extent	12
dc.format.extent	2442594
dc.identifier	25542555
dc.identifier	3e2bdfe8-9857-4689-acea-140e3b54d7b5
dc.identifier	84893902026
dc.identifier.citation	Mohamed, 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-z	en
dc.identifier.doi	10.1007/s11012-013-9790-z
dc.identifier.iss	2	en
dc.identifier.issn	0025-6455
dc.identifier.uri	http://hdl.handle.net/2164/4219
dc.identifier.vol	49	en
dc.language.iso	eng
dc.relation.ispartof	Meccanica	en
dc.subject	condition health monitoring	en
dc.subject	crack detection	en
dc.subject	statistical analysis	en
dc.subject	vibration	en
dc.subject	signal processing	en
dc.subject	neural network	en
dc.subject	TC Hydraulic engineering. Ocean engineering	en
dc.subject.lcc	TC	en
dc.title	Crack detection in a rotating shaft using artificial neural networks and PSD characterisation	en
dc.type	Journal article	en

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