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dc.contributor.authorKhan, M. A.
dc.contributor.authorStarr, A. G.
dc.contributor.authorCooper, D.
dc.date.accessioned2011-10-18T14:01:05Z
dc.date.available2011-10-18T14:01:05Z
dc.date.issued2008-11
dc.identifier.citationKhan , M A , Starr , A G & Cooper , D 2008 , ' A methodology for online wear debris morphology and composition analysis ' , Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology , vol. 222 , no. 7 , pp. 785-796 . https://doi.org/10.1243/13506501JET449
dc.identifier.issn1350-6501
dc.identifier.otherPURE: 409996
dc.identifier.otherPURE UUID: 62bbbac4-59e3-4baa-9180-12b740b76c11
dc.identifier.otherWOS: 000261774300002
dc.identifier.otherScopus: 57949089918
dc.identifier.urihttp://hdl.handle.net/2299/6707
dc.descriptionOriginal article can be found at: http://www.pepublishing.com/ Copyright Professional Engineering Publishing [Full text of this article is not available in the UHRA]
dc.description.abstractOnline or inline detection of basic debris features, i.e. size, quantity, size distribution, shape, and compositions simultaneously With real time diagnostics is one of the possible ways to perform Wear debris analysis with high reliability. At present many techniques and sensors are available that can perform near real time detection and diagnostics for debris quantitative features. But to perform real time detection and diagnostics for features like shape and composition still requires a reliable technical concept. In this article a new technique for online wear debris shape and composition analysis is described. The developed technique is a combination of hardware and software based oil imaging technology for shape and composition detection. Rule-based algorithms are used to perform near real time debris analysis diagnostics. An experimental study is also presented that shows the possible potential of the developed technique on real applications.en
dc.format.extent12
dc.language.isoeng
dc.relation.ispartofProceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology
dc.subjectwear debris
dc.subjectdebris basic features
dc.subjectimage processing and real time diagnostics
dc.titleA methodology for online wear debris morphology and composition analysisen
dc.contributor.institutionOffice of the Vice-Chancellor
dc.description.statusPeer reviewed
rioxxterms.versionofrecordhttps://doi.org/10.1243/13506501JET449
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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