Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0167-8655(00)00050-7
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dc.titleApplication of image and sound analysis techniques to monitor the condition of cutting tools
dc.contributor.authorMannan, M.A.
dc.contributor.authorKassim, A.A.
dc.contributor.authorJing, M.
dc.date.accessioned2014-06-17T05:08:54Z
dc.date.available2014-06-17T05:08:54Z
dc.date.issued2000-10
dc.identifier.citationMannan, M.A., Kassim, A.A., Jing, M. (2000-10). Application of image and sound analysis techniques to monitor the condition of cutting tools. Pattern Recognition Letters 21 (11) : 969-979. ScholarBank@NUS Repository. https://doi.org/10.1016/S0167-8655(00)00050-7
dc.identifier.issn01678655
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/57927
dc.description.abstractTool wear dramatically affects the texture of the machined surface and the sound generated by the cutting process. This paper discusses our work on texture analysis of machined surfaces and signal processing of sound generated by machining process and investigates the correlation between tool wear and quantities characterizing machined surfaces and sound pattern. Our results clearly indicate that tool condition monitoring which is defined as the ability to distinguish between a sharp, a semi-dull, or a dull tool can be successfully accomplished by combining sensory data from a CCD camera (image analysis) and a microphone (sound analysis).
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0167-8655(00)00050-7
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.contributor.departmentMECHANICAL & PRODUCTION ENGINEERING
dc.description.doi10.1016/S0167-8655(00)00050-7
dc.description.sourcetitlePattern Recognition Letters
dc.description.volume21
dc.description.issue11
dc.description.page969-979
dc.description.codenPRLED
dc.identifier.isiut000089614800002
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