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时间:2019-03-03
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1、ComputersandChemicalEngineering28(2004)21312140Atwo-stepsupervisoryfaultdiagnosisframeworkYvonnePower,ParisaA.Bahri∗SchoolofEngineeringScienceandA.J.ParkerCooperativeCentreforHydrometallurgy,MurdochUniversity(RockinghamCampus),Murdoch,WA6150,AustraliaReceived5Decembe
2、r2002;receivedinrevisedform21December2003;accepted20January2004Availableonline4June2004AbstractTechniquesenablingearlydetectionanddiagnosisoffaultsareimportantintheprocessingindustries.Thispaperemphasisesatechniqueforearlyfaultdetectionanddiagnosisbasedondynamicfault
3、dataandatwo-stepfaultdetectionanddiagnosisframework.Theapproachshowsvariousadvantagesoveralternativemethodsincludingpromptfaultdetectionandlocalisation,applicabilitytolarge-scalesystemswithouttheneedforexcessivecomputingresources,andamodulararchitecturethatallowsplan
4、tsectionstobetreatedindividually.Intheproposedmethod,thelarge-scaleplantisbrokenupintosectionsandaPetrinetbasedonrealtimedataisusedtolocatetheparticularsectionoftheplantinwhichthefaultoriginates.ThisPetrinetthenactivatessecondaryneuralnetworks,whichdiagnosetheexactlo
5、cationofthefaultinthatparticularplantsection.Applicabilityoftheproposedtechniqueisdemonstratedthroughapilotplantcasestudy.©2004ElsevierLtd.Allrightsreserved.Keywords:Faultdetectionanddiagnosis;Petrinets;Neuralnetworks1.Introductiondiagnosistrainedondynamicfaultdataan
6、dtheuseofaPetrinetforfaultdetectioninlarge-scalesystems.FaultdetectionanddiagnosisisanessentialpartoftheInthepast,Petrinetshavecommonlybeenusedtomodeloperationofanyprocessingplant.Earlydetectionanddiag-discreteeventsystemssuchasbatchprocesses,wherethenosisoffaultsisi
7、mportantinprocessingindustrysincealotmaterialisoperatedinfinitequantities(orbatches),ratherofdamageandlosscanresultbeforeafaultpresentinthethanforfaultdetectionbasedoncontinuoustimedata.How-systemisdetected.Inaddition,itbecomeshardertodistin-ever,evenwithacontinuouspr
8、ocess,dataiscollectedfromguishtherootcauseofthefaultoncethefaultpropagatesthedistributedcontrolsystem(DCS)atdiscretetimein-throught
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