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dc.contributor.authorRastegaev, I. A.
dc.contributor.authorMerson, D. L.
dc.contributor.authorDanyuk, A. V.
dc.contributor.authorAfanasyev, M.A.
dc.contributor.authorVinogradov, Alexey
dc.date.accessioned2022-04-19T07:59:20Z
dc.date.available2022-04-19T07:59:20Z
dc.date.created2019-01-10T14:08:44Z
dc.date.issued2018
dc.identifier.citationWear. 2018, 410–411 83-92.en_US
dc.identifier.issn0043-1648
dc.identifier.urihttps://hdl.handle.net/11250/2991229
dc.description.abstractThe purpose of this work is to demonstrate how a new acoustic emission (AE) technique can be used to monitor friction surface degradation in a four-ball tribosystem under different types of lubrication. The AE method is based on a novel signal spectral categorization technique, and it was used to identify concurrent degradation processes in bearing steel. The correlation of AE features with the development of specific microstructural features on the contact surfaces has been used to identify the AE "signature" of specific damage mechanisms, and thus to monitor the progression of wear. The proposed approach enables the construction of a chronology of lubricant and/or contacting material degradation during tribological testing with a high degree of confidence. Furthermore, it provides an efficient means for automated wear monitoring and for real-time, non-supervised interpretation of the state of wear in a given tribosystem.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleUsing acoustic emission signal categorization for reconstruction of wear development timeline in tribosystems: Case studies and application examplesen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holderThis manuscript version is made available under the CC-BY-NC-ND 4.0 licenseen_US
dc.source.pagenumber83-92en_US
dc.source.volume410–411en_US
dc.source.journalWearen_US
dc.identifier.doi10.1016/j.wear.2018.06.006
dc.identifier.cristin1654218
cristin.unitcode194,64,92,0
cristin.unitnameInstitutt for maskinteknikk og produksjon
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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