Thermographical investigation of crack initiation using artificial neural networks

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dc.contributor.authorSelek, M.
dc.contributor.authorSahin, Oe S.
dc.contributor.authorKahramanli, S.
dc.date.accessioned2020-03-26T17:18:39Z
dc.date.available2020-03-26T17:18:39Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.descriptionInternational Conference on Computer as a Tool (EUROCON 2007) -- SEP 09-12, 2007 -- Warsaw, POLANDen_US
dc.description.abstractIn this study, a thermographic infrared imaging system was used to detect the temperature rise of AISI37 steel specimen under reverse bending fatigue. Fatigue behavior of metals shows temperature profiles with three stages: an initial increase of the specimen mean temperature region, a constant (equilibrium) temperature region, an abrupt temperature increase region at end of which the specimen fails and its temperature falls instantly. In order to recognize critical third region, it is necessary to observe endurance state of the specimen being tested. In this study, the temperature profiles of the specimen under testing are recorded by thermal camera and transferred to the image processing program. The artificial neural networks obtain spot temperatures of the inspected specimen by using its temperature profiles. By analyzing the values of obtained data, we detect spots of highest temperatures as ones that are exposed to most intensive deformation. These regions considered to be probable crack initiation sites.en_US
dc.identifier.endpage778en_US
dc.identifier.isbn978-1-4244-0812-2
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage773en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21710
dc.identifier.wosWOS:000257261900131en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofEUROCON 2007: THE INTERNATIONAL CONFERENCE ON COMPUTER AS A TOOL, VOLS 1-6en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectimage processingen_US
dc.subjectinfrared thermographyen_US
dc.subjectneural networksen_US
dc.subjectfatigueen_US
dc.titleThermographical investigation of crack initiation using artificial neural networksen_US
dc.typeConference Objecten_US

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