About: Fault Detection Based on Gaussian Process Models: an Application to the Rolling Mill

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://www.scitepress.org/DigitalLibrary/
Description	In this paper a fault detection approach based on Gaussian process model is proposed. The problem we raise is how to deal with insufficiently validated models during surveillance of nonlinear plants given the fact that tentative model-plant miss-match in such a case can cause false alarms. To avoid the risk, a novel model validity index is suggested in order to quantify the level of confidence associated to the detection results. This index is based on estimated distance between the current process data from data employed in the learning set. The effectiveness of the test is demonstrated on data records obtained from operating cold rolling mill. In this paper a fault detection approach based on Gaussian process model is proposed. The problem we raise is how to deal with insufficiently validated models during surveillance of nonlinear plants given the fact that tentative model-plant miss-match in such a case can cause false alarms. To avoid the risk, a novel model validity index is suggested in order to quantify the level of confidence associated to the detection results. This index is based on estimated distance between the current process data from data employed in the learning set. The effectiveness of the test is demonstrated on data records obtained from operating cold rolling mill. (en)
Title	Fault Detection Based on Gaussian Process Models: an Application to the Rolling Mill Fault Detection Based on Gaussian Process Models: an Application to the Rolling Mill (en)
skos:prefLabel	Fault Detection Based on Gaussian Process Models: an Application to the Rolling Mill Fault Detection Based on Gaussian Process Models: an Application to the Rolling Mill (en)
skos:notation	RIV/48361143:_____/11:#0000007!RIV12-MSM-48361143
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(7D09008)
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Ettler, Pavel
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	COMPUREG Plzeň, s.r.o.
http://linked.open...dnocenehoVysledku	199423
http://linked.open...ai/riv/idVysledku	RIV/48361143:_____/11:#0000007
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Gaussian process model; fault detection; statistical hypothesis test; cold rolling mill (en)
http://linked.open.../riv/klicoveSlovo	Gaussian process model cold rolling mill fault detection statistical hypothesis test
http://linked.open...ontrolniKodProRIV	[125DF2F24FDA]
http://linked.open...v/mistoKonaniAkce	Noordwijkerhout, The Netherlands
http://linked.open...i/riv/mistoVydani	Portugalsko
http://linked.open...i/riv/nazevZdroje	8th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2011
http://linked.open...in/vavai/riv/obor	BC
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Probabilistic Bayesian soft sensor - a tool for on-line estimation of the key process variable in cold rolling mills
http://linked.open...UplatneniVysledku	2011
http://linked.open...iv/tvurceVysledku	Ettler, Pavel Juricic, Dani Kocijan, Jus
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2011-01-01 (xsd:date)
number of pages	4 (xsd:int)
http://purl.org/ne...btex#hasPublisher	SciTePress – Science and Technology Publications
https://schema.org/isbn	978-989-8425-74-4

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