Determination of friction coefficient at journal bearings by experimental and by means of artificial neural networks method

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dc.contributor.authorÜnlü B.S.
dc.contributor.authorDurmuş H.
dc.contributor.authorMeriç C.
dc.contributor.authorAtik E.
dc.date.accessioned2024-07-22T08:24:34Z
dc.date.available2024-07-22T08:24:34Z
dc.date.issued2004
dc.description.abstractKnowing friction coefficient is important for determination of wear loss conditions at journal bearings. Tribological events that influence wear and its variations affect experimental results. In this study, friction coefficient at CuSn10 Bronze radial bearings has been determined by a new approach as experimental and artificial neural networks method. In experiments, effects of bearings have been examined at dry and lubricated conditions and at different loads and velocities.
dc.identifier.DOI-ID10.3390/mca9030399
dc.identifier.issn1300686X
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/20039
dc.language.isoEnglish
dc.publisherAssociation for Scientific Research
dc.rightsAll Open Access; Gold Open Access
dc.subjectAdhesion
dc.subjectBearings (machine parts)
dc.subjectBronze
dc.subjectCopper compounds
dc.subjectLubrication
dc.subjectNeural networks
dc.subjectTribology
dc.subjectVelocity measurement
dc.subjectFriction coefficients
dc.subjectFrictional force
dc.subjectLaws of friction
dc.subjectWear loss
dc.subjectFriction
dc.titleDetermination of friction coefficient at journal bearings by experimental and by means of artificial neural networks method
dc.typeArticle

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