Please use this identifier to cite or link to this item: https://doi.org/10.1504/IJCAT.2012.050707
DC FieldValue
dc.titleFeature analysis in tool condition monitoring: A case study in titanium machining
dc.contributor.authorSun, J.
dc.contributor.authorWong, Y.S.
dc.contributor.authorHong, G.S.
dc.contributor.authorRahman, M.
dc.date.accessioned2014-10-07T05:24:25Z
dc.date.available2014-10-07T05:24:25Z
dc.date.issued2012
dc.identifier.citationSun, J.,Wong, Y.S.,Hong, G.S.,Rahman, M. (2012). Feature analysis in tool condition monitoring: A case study in titanium machining. International Journal of Computer Applications in Technology 45 (2-3) : 177-185. ScholarBank@NUS Repository. <a href="https://doi.org/10.1504/IJCAT.2012.050707" target="_blank">https://doi.org/10.1504/IJCAT.2012.050707</a>
dc.identifier.issn09528091
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/84444
dc.description.abstractDue to the rapid wear of the cutting tools when machining titanium alloy, tool condition monitoring (TCM) is most useful to avoid workpiece damage and maximise machining productivity. This paper uses sensor signals and feature analysis to identify a feature set for effective TCM. Firstly, basic requirements of sensor signals in tool condition identification are discussed, and the suitability of two candidate signals (acoustic emission and cutting force) commonly employed for machining monitoring are critically analysed. Their effectiveness in TCM is investigated based on extracted features of these signals, singly or in combination. Experimental results based on titanium machining, which is an expensive process with high tool wear, indicate that this proposed method is capable to determine a suitable sensing method and an effective feature set to identify tool condition. Copyright © 2012 Inderscience Enterprises Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1504/IJCAT.2012.050707
dc.sourceScopus
dc.subjectFeature selection
dc.subjectSensor fusion
dc.subjectTCM
dc.subjectTool condition monitoring
dc.typeArticle
dc.contributor.departmentMECHANICAL ENGINEERING
dc.contributor.departmentDEAN'S OFFICE (ENGINEERING)
dc.description.doi10.1504/IJCAT.2012.050707
dc.description.sourcetitleInternational Journal of Computer Applications in Technology
dc.description.volume45
dc.description.issue2-3
dc.description.page177-185
dc.description.codenIJCTE
dc.identifier.isiutNOT_IN_WOS
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