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1、ARTICLEINPRESSEngineeringApplicationsofArtificialIntelligence23(2010)950–960ContentslistsavailableatScienceDirectEngineeringApplicationsofArtificialIntelligencejournalhomepage:www.elsevier.com/locate/engappai$Aframeworkforon-linetrendextractionandfaultdiagnosisa
2、,bcManoRamMaurya,PraveenK.Paritosh,RaghunathanRengaswamy,aVenkatVenkatasubramanianaLaboratoryforIntelligentProcessSystems,SchoolofChemicalEngineering,PurdueUniversity,WestLafayette,IN47907,USAbMetawebTechnologies,Inc.,SanFrancisco,CA94105,USAcDepartmentofChem
3、icalEngineering,TexasTechUniversity,6thandCanton,MailStop3121,Lubbock,TX79409-3121,USAarticleinfoabstractArticlehistory:Qualitativetrendanalysis(QTA)isaprocess-history-baseddata-driventechniquethatworksbyReceived17April2009extractingimportantfeatures(trends)fr
4、omthemeasuredsignalsandevaluatingthetrends.QTAhasReceivedinrevisedformbeenwidelyusedforprocessfaultdetectionanddiagnosis.Recently,Dashetal.[2004.Anovelinterval-17January2010halvingframeworkforautomatedidentificationofprocesstrends.AIChEJournal50(1),149–162]Acce
5、pted18January2010presentedaninterval-halving-basedalgorithmforoff-lineautomatictrendextractionfromarecordofAvailableonline6March2010data,afuzzy-logicbasedmethodologyfortrend-matchingandafuzzy-rule-basedframeworkforfaultKeywords:diagnosis(FD).Inthisarticle,anal
6、gorithmforon-lineextractionofqualitativetrendsisproposed.AQualitativetrendanalysisframeworkforon-linefaultdiagnosisusingQTAalsohasbeenpresented.SomeoftheissuesaddressedOn-lineare:(i)developmentofarobustandcomputationallyefficientQTA-knowledge-base,(ii)faultdete
7、ction,Faultdetection(iii)estimationofthefaultoccurrencetime,(iv)on-linetrend-matching,and(v)updatingtheQTA-Faultdiagnosisknowledge-basewhenanovelfaultisdiagnosedmanually.AprototypeQTA-baseddiagnosticsystemTennesseeEastmanprocessshasbeendevelopedinMatlab.Result
8、sforfaultdiagnosisoftheTennesseeEastmanprocessusingthedevelopedframeworkarepresented.&2010ElsevierLtd.Allrightsreserved.1.Introductionextraction,namely,interval-halving(Dashetal.,2
