Oils quality and performance analysis of vehicle's engines using radial basis neural networks

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dc.authorid0000-0001-6130-505X
dc.contributor.authorKalkat, Menderes
dc.contributor.authorYildirim, Sahin
dc.contributor.authorErkaya, Selcuk
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2009
dc.departmentNiğde ÖHÜ
dc.description.abstractPurpose - The purpose of this paper is to improve the application of neural networks on vehicle engine systems for fault detecting and analysing engine oils. Design/methodology/approach - Three types of neural networks are employed to find exact neural network predictor of vehicle engine oil performance and quality. Nevertheless, two oil types are analysed for predicting performance in the engine. These oils are used and unused oils. In experimental work, two accelerometers are located at the bottom of the car engine to measure related vibrations for analysing oil quality of both cases. Findings - The results of both computer simulation and experimental work show that the radial basis neural network predictor gives good performance at adapting different cases. Research limitations/implications - The results of the proposed neural network analyser follow the desired results of the vehicle engine's vibration variation. However, this kind of neural network scheme can be used to analyse oil quality of the car in experimental applications. Practical implications - As theoretical and practical studies are evaluated together, it is hoped that oil analysers and interested researchers will obtain significant results in this application area. Originality/value - This paper is an original contribution on vehicle oil quality analysis using a proposed artificial neural network and it should be helpful for industrial applications of vehicle oil quality analysis and fault detection.
dc.identifier.doi10.1108/00368790910988417
dc.identifier.endpage310
dc.identifier.issn0036-8792
dc.identifier.issn1758-5775
dc.identifier.issue6
dc.identifier.scopus2-s2.0-70350150450
dc.identifier.scopusqualityQ3
dc.identifier.startpage301
dc.identifier.urihttps://dx.doi.org/10.1108/00368790910988417
dc.identifier.urihttps://hdl.handle.net/11480/5141
dc.identifier.volume61
dc.identifier.wosWOS:000271209200003
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherEMERALD GROUP PUBLISHING LTD
dc.relation.ispartofINDUSTRIAL LUBRICATION AND TRIBOLOGY
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectNeural nets
dc.subjectEngine components
dc.subjectLubricating oils
dc.subjectRoad vehicle engineering
dc.titleOils quality and performance analysis of vehicle's engines using radial basis neural networks
dc.typeArticle

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