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Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICARCV.2010.5707866
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dc.titleContinuous health assessment using a single Hidden Markov model
dc.contributor.authorGeramifard, O.
dc.contributor.authorXu, J.-X.
dc.contributor.authorZhou, J.H.
dc.contributor.authorLi, X.
dc.date.accessioned2014-06-19T03:03:53Z
dc.date.available2014-06-19T03:03:53Z
dc.date.issued2010
dc.identifier.citationGeramifard, O.,Xu, J.-X.,Zhou, J.H.,Li, X. (2010). Continuous health assessment using a single Hidden Markov model. 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 : 1347-1352. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICARCV.2010.5707866" target="_blank">https://doi.org/10.1109/ICARCV.2010.5707866</a>
dc.identifier.isbn9781424478132
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/69720
dc.description.abstractIn this paper, two temporal models, Hidden Markov Model and Auto Regressive Moving Average model with exogenous inputs (ARMAX), are used for health condition monitoring of the cutter in a milling machine. Dataset is acquired through real time force signal sensing. A heuristic statistical approach is used to select dominant features, leading to the selection of 3 dominant features from the 16-dimensional feature space. Subsequently Hidden Markov Model and ARMAX model have been trained to predict the wearing status of the cutter in the milling machine. Suitability of these approaches are investigated and compared. ©2010 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICARCV.2010.5707866
dc.sourceScopus
dc.subjectARMAX
dc.subjectHealth condition monitoring
dc.subjectHidden Markov model
dc.subjectSingular value decomposition
dc.subjectVariance inflation factor
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/ICARCV.2010.5707866
dc.description.sourcetitle11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
dc.description.page1347-1352
dc.identifier.isiutNOT_IN_WOS
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