About: Testing of Sensor Condition Using Gaussian Mixture Model

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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
Description	The paper describes a method of sensor condition testing based on processing of data measured by the sensor using a Gaussian mixture model with dynamic weights. The procedure is composed of two steps, off-line and on-line. In off-line stage, fault-free learning data are processed and described by a probabilistic mixture of regressive models (mixture components) including a transition table between active components. It is assumed that each component characterises one property of data dynamics and just one component is active in each time instant. In on-line stage, tested data are used for transition table estimation compared with the fault-free transition table. The crossing of given level of difference announces a possible fault. The paper describes a method of sensor condition testing based on processing of data measured by the sensor using a Gaussian mixture model with dynamic weights. The procedure is composed of two steps, off-line and on-line. In off-line stage, fault-free learning data are processed and described by a probabilistic mixture of regressive models (mixture components) including a transition table between active components. It is assumed that each component characterises one property of data dynamics and just one component is active in each time instant. In on-line stage, tested data are used for transition table estimation compared with the fault-free transition table. The crossing of given level of difference announces a possible fault. (en)
Title	Testing of Sensor Condition Using Gaussian Mixture Model Testing of Sensor Condition Using Gaussian Mixture Model (en)
skos:prefLabel	Testing of Sensor Condition Using Gaussian Mixture Model Testing of Sensor Condition Using Gaussian Mixture Model (en)
skos:notation	RIV/67985556:_____/14:00431247!RIV15-AV0-67985556
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(7D12004)
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Jirsa, Ladislav Pavelková, Lenka
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	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	50068
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/14:00431247
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Sensor Faults; Bayesian Statistics; Gaussian Mixture (en)
http://linked.open.../riv/klicoveSlovo	Bayesian Statistics Sensor Faults Gaussian Mixture
http://linked.open...ontrolniKodProRIV	[CA655F2DDB5B]
http://linked.open...v/mistoKonaniAkce	Vien
http://linked.open...i/riv/mistoVydani	Portugal
http://linked.open...i/riv/nazevZdroje	Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics
http://linked.open...in/vavai/riv/obor	BC
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Probabilistic distributed industrial system monitor
http://linked.open...UplatneniVysledku	2014
http://linked.open...iv/tvurceVysledku	Pavelková, Lenka Jirsa, Ladislav
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2014-09-01 (xsd:date)
number of pages	9 (xsd:int)
http://purl.org/ne...btex#hasPublisher	SCITEPRESS – Science and Technology Publications
https://schema.org/isbn	978-989-758-039-0

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