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1、基了二解析模型與灰色時(shí)序模型的化工設(shè)備故障預(yù)診斷方法研究關(guān)鍵詞：解析模型、灰色模型、日寸‘間序列模型、建模青島科技大學(xué)研究生學(xué)位論文ANALYTICALANDGM—ARMODELSBASEDFAULTPRE—DIAGNOSTICMETHoDFORCHEMICALEQUIPPMENTSABSTRACTThepetrochemicalindustryismoredangerousthanotherindustries，anditsaccidentimpactisalsomoresevereduetoitsattributeinnature．Thefaultdiagnosisandp
2、redictiontechnologyarethemainmethodstoimprovethesafetyessenceofpetrochemicalindustry．Becausethetwomethodsdealwiththeproblemsfromdifferentviews，theyhavetheirownadvantagesanddisadvantages．Inactualproduction，ifoperatorscanknowthetrendofequipmentconditioninadvance，anddetectandseparatethefaultswh
3、ichmaycausetheequipmentdeviatefromitsnormalstate，theycanwellensurethesafetyoftheequipmentandavoidtheoccurrenceofmajoraccidents．Theanalyticalmodelcanefficientlydetectfaultsandisolatethefaultsource．However,itcan’tdetectandexcludethesystempotentialfault．Thepredictionmodelsummarizesandanalyzesth
4、edatatogetthetrend．Mostofdevicesbelongtothegraysystem，SOthispaperchoosesthegraypredictionmodeltostudy．Thegraymodelreauiresasmallamountofdataandpredictsthemacrotrendsverywell，butlacksadaptabilitytothedatafluctuation．Thegraymodelcannotobtainthecausesandconsequencesmerelyfromthedatachanging．Int
5、hispaper,thegraymodelisimprovedbycombiningitwithtime—seriesmodelinseries．Theresidualsofthegraymodelarecorrectedtoenhancetheadaptabilitytothedataoscillations．Onefusionmethodaboutdiagnosisandpredictionmethodsisstudiedandthehybridpre．diagnosismodelisbuiltinthepaper．Thegraypredictionmodelcanampl
6、ifytheearlydataandtheanalyticalmodelcanperformfaultdetectionandisolationusingthepredictedvalues．Thepre—diagnosismodelcannotonlyqualitativelydetectfault，butalsoquantitativelyanalyzethedevelopinglevelandspeedofthefault．Therearetwowaystocombinethegraymodelwithanalytical基于解析模型與灰色時(shí)序模型的化工設(shè)備故障預(yù)診斷方法
7、研究model：1)Predictiveandanalyticalmodel．Firstly,thepredictionmodelpredictsthevariablesrelatedwiththefaultparameteEThentheanalyticalmodeldealswiththepredictionvaluesandobtainsthefaultparameter．2)Analyticalandpredictivemodel．Firstly,theanalyticalmodel
