Please use this identifier to cite or link to this item: https://doi.org/10.1007/s001380050109
DC FieldValue
dc.titleMachine tool condition monitoring using workpiece surface texture analysis
dc.contributor.authorKassim, A.A.
dc.contributor.authorMannan, M.A.
dc.contributor.authorJing, Ma.
dc.date.accessioned2014-10-07T03:00:19Z
dc.date.available2014-10-07T03:00:19Z
dc.date.issued2000-02
dc.identifier.citationKassim, A.A., Mannan, M.A., Jing, Ma. (2000-02). Machine tool condition monitoring using workpiece surface texture analysis. Machine Vision and Applications 11 (5) : 257-263. ScholarBank@NUS Repository. https://doi.org/10.1007/s001380050109
dc.identifier.issn09328092
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/80695
dc.description.abstractTool wear affects the surface roughness dramatically. There is a very close correspondence between the geometrical features imposed on the tool by wear and microfracture and the geometry imparted by the tool on to the workpiece surface. Since a machined surface is the negative replica of the shape of the cutting tool, and reflects the volumetric changes in cutting-edge shape, it is more suitable to analyze the machined surface than look at a certain portion of the cutting tool. This paper discusses our work that analyzes images of workpiece surfaces that have been subjected to machining operations and investigates the correlation between tool wear and quantities characterizing machined surfaces. Our results clearly indicate that tool condition monitoring (the distinction between a sharp, semi-dull, or a dull tool) can be successfully accomplished by analyzing surface image data.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s001380050109
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.contributor.departmentMECHANICAL & PRODUCTION ENGINEERING
dc.description.doi10.1007/s001380050109
dc.description.sourcetitleMachine Vision and Applications
dc.description.volume11
dc.description.issue5
dc.description.page257-263
dc.description.codenMVAPE
dc.identifier.isiut000086186800005
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