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dc.contributor.authorBustillo Iglesias, Andrés 
dc.contributor.authorCorrea, Maritza
dc.contributor.authorReñones, Anibal
dc.date.accessioned2016-11-09T09:32:14Z
dc.date.available2016-11-09T09:32:14Z
dc.date.issued2011-03
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10259/4263
dc.description.abstractThe installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a Bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases.en
dc.description.sponsorshipRed de Supervision y Diagnosis de Sistemas Complejos (DPI2009-06124-E) of the Spanish Ministry of Science and Innovationen
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherMDPIen
dc.relation.ispartofSensors, 2011, V. 11, n. 3, p. 2282-3400en
dc.rightsAttribution 3.0 Unported
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/
dc.subjectvirtual sensoren
dc.subjectBayesian classifieren
dc.subjectindustrial applicationsen
dc.subjecttool condition monitoringen
dc.subjectmultitooth-toolsen
dc.subject.otherInformáticaes
dc.subject.otherComputer scienceen
dc.titleA vrtual sensor for online fault detection of multitooth-toolsen
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.relation.publisherversionhttp://dx.doi.org/10.3390/s110302773
dc.identifier.doi10.3390/s110302773
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN/DPI2009-06124-E
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionen


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