電氣專業(yè)英文文獻(xiàn)

AnExpertSystemforTransformerFaultDiagnosisUsingDissolvedGasAnalysisINTRODUCTIONThepowertransformerisamajorapparatusinapowersystem,anditscorrectfunctioningitsvitaltominimizesystemoutages,manydeviceshaveevolvedtomonitortheserviceabilityofpowertransformers.Thesedevices,suchas,Buchholzrelaysordifferentialrelays,respondonlytoaseverepowerfailurerequiringimmediateremovalofthetransformerfromservice,inwhichcase,outagesareinevitable.Thus,preventivetechniquesforearlydetectionfaultstoavoidoutageswouldbevaluable.Inthisway,analysisofthemixtureofthefaultygasesdissolvedininsulationoilofpowertransformerhasreceivedworldwiderecognitionasaneffectivemethodforthedetectionofoncipientfaults.ManyresearchersandelectricalutilitieshavereportedontheirexperienceanddevelopedinterpretativecriteriaonthebasisofDGA.However,criteriatendtovaryfromutilitytoutility.Therefore,transformerdiagnosisisstillintheheuristicstage.Forthisreason,knowledge-basedprogrammingisasuitableapproachtoimplementinsuchadiagnosticproblem.BasedontheinterpretationofDGA,aprototypeofanexpertsystemfordiagnosisofsuspectedtransformerfaultsandtheirmaintenanceproceduresisproposed.Thesignificantsourceinthisknowledgebaseisthegasratiomethod.Somelimitationsofthisapproachareovercomebyincorporatingthediagnosticprocedureandthesyntheticexpertisemethod.Furthermore,databasesadoptedfromTPC'Sgasrecordsoftransformersareincorporatedintotheexpertsystemtoincreasethepracticalperformance.Uncertaintyofdiagnosisismanagedbyusingfuzzysetconcepts.Thisexpertsystemisconstructedwithrulebasedknowledgerepresentation,sinceitcanbeexpressedbyexperts.Theexpertsystembuildingtool,knowledgeEngineeringSystem(KES),isusedinthedevelopmentoftheknowledgesystembecause,ithasexcellentman-machineinterfacethatprovidessuggestions.Moreover,itsinferencestrategyissimilartotheMYCIN.Afamousrule-basedexpertsystemusedformedicaldiagnosis.Theuncertaintyofhumanqualitativediagnosticexpertise,e.g.,keygasanalysis,andanotherquantitativeimprecision,suchas,normsthresholdandgasratioboundariesetc.,aresmoothedbyappropriatefuzzymodels.Withtheresultsofsuchimplementation,differentcertaintyfactorswillbeassignedtothecorrespondingexpertisevariables.Bothevent-driven(forwardchaining)andgoal-driven(backwardchaining)inferencesareusedintheinferenceenginetoimprovetheinferenceefficiency.Todemonstratethefeasibilityoftheproposedexpertsystem,aroundhundredsofTPChistoricalgasrecordshavebeentested.Itisfoundthatmoreappropriatefaultytypesandmaintenancesuggestionscansupportthemaintenancepersonalstoincreasetheperformanceoftransformerdiagnosis.DEVELOPMENTOFDIAGNOSISANDINTERPRETATIONLikemanydiagnosticproblems,diagnosisofoil-immersedpowertransformerisaskilledtask.Atransformermayfunctionwellexternallywithmonitors,whilesomeincipientdeteriorationmayoccurinternallytocauseafatalprobleminthelatterdevelopment.AccordingtoaJapaneseexperience,nearly80%ofallfaultsresultfromincipientdeteriorations.Therefore,faultsshouldbeidentifiedandavoidedattheearliestpossiblestagebysomepredictivemaintenancetechnique.DGAisoneofthemostpopulartechniquesforthisproblem.Faultgasesintransformersaregenerallyproducedbyoildegradationandotherinsulatingmaterial,e.g.,celluloseandpaper.Theoretically,ifanincipientoractivefaultispresent,theindividualdissolvedgasconcentration,gassingrate,totalcombustiblegas(TCG)andcellulosedegradationareallsignificantlyincreased.Byusinggaschromatographytoanalysethegasdissolvedinatransformer'sinsulatingoil,itbecomesfeasibletojudgetheincipientfaulttypes.Thisstudyisconcernedwiththefollowingrepresentativecombustiblegases;hydrogen(H2),methane(C2H2),ethane(C2H6),ethylene(C2H2)andcarbonmonoxide(C0).ManyinterpretativemethodsbasedonDGAtothenatureofincipientdeteriorationhavebeenreported.Evenundernormaltransformeroperationalconditions,someofthesegasesmaybeformedinside.Thus,itisnecessarytobuildconcentrationnormsfromasufficientlylargesamplingtoassessthestatistics.TPCinvestigatedgasdatafrompowertransformerstoconstructitscriteria.Thedevelopedknowledgebaseinthispaperispartiallybasedonthesedata.Onthehand,Dornerburgdevelopedamethodtojudgedifferentfaultsbyratingpairsofconcentrationsofgases,e.g.,CH/H,GH/C3H4,withapproximatelyequalsolubilityandfusioncoefficients.Rogersestablishedmarecomprehensiveratiocodestointerpretthethermalfaulttypeswiththeoreticalthermodynamicassessments.Thisgasratiomethodwaspromisingbecauseiteliminatedtheeffectofoilvolumeandsimplifiedthechoiceofunits.Moreover,itsystematicallyclassifiedthediagnosisexpertiseinatableform.Table1displaystheratiomethodasproposedbyRogers.Thedissolvedgasmayvarywiththenatureandseverityofdifferentfaults.Byanalyzingtheenergydensityoffaults,it'spossibletodistinguishthreebasicfaultprocesses:overheating(pyrolysis),corona(partialdischatge)andarcingdischarge.Coronaandarcingarisefromelectricalfaults,whileoverheatingisathermalfault.Bothtypesoffaultsmyleadtodeterioration,whiledamagefromoverheatingistypicallylessthanthatfromelectricalstress.Infect,differentgastrendsleadtodifferentfaultytypes,thekeygasmethodisidentified.Forexample,largeamountsofCHandHareproducedwithminorarcingfault4quantitiesofCH2aidC2H2maybeasymptomofanarcingfault.THEPROPOSEDDIAGNOSTICEXPERTSYSTEMThisstudyisaimedatdevelopingarule-basedexpertsystemtoperformtransformerdiagnosissimilartoahumanexpert.Thedetailsofsystemprocessingaredescribedbelow.TheProposedDiagnosticMethodDiagnosisisataskthatrequiresexperience.Itisunwisetodetermineanapproachfromonlyafewinvestigations.Therefore,thisstudyusesthesyntheticexpertisemethodwiththeexperiencedproceduretoassistthepopulargasratiomethodandcompletepracticalperformance.ExperiencedDiagnosticProcedureTheoverallprocedureofroutinemaintenancefortransformersislisted.ThecoreofthisprocedureisbasedontheimplementationoftheDGAtechnique.Thegasratiomethodisthesignificantknowledgesource.Someoperationallimitationsofthegasratiomethodexist.Theratiotableisunabletocoverallpossiblecases.Minimumlevelsofgasesmustbepresent.ThesolidinsulationinvolvingCOandCOarehandledseparatelyandthegasratiocodeshavebeendevelopedmainlyfromafree-breathingtransformer.Otherdiagnosticexpertiseshouldbeusedtoassistthismethod.Norms,syntheticexpertisemethodanddatabaserecordshavebeenincorporatedtocompletetheselimitations.ThefirststepofthisdiagnosticprocedurebeginsbyaskingDGAforanoilsampletobetested.Moreimportantrelevantinformationaboutthetransformer'scondition,suchasthevoltagelevel,thepreservativetype,theon-line-tap-changer(OLTC)state,theoperatingperiodanddegassedtimemustbeknownforfurtherinference.Norms(criteria)SetupbyTPCpowertransformers'gascharacteristicdataarethenusedtojudgethetransformers'condition.Fortheabnormalcases,thegasratiomethodisusedtodiagnosetransformerfaulttype.Ifdifferentorunknowndiagnosisresultsarefoundfromtheseratiomethods,afurthersyntheticexpertisemethodisadopted.Aftertheseprocedures,differentseveritydegreesareassignedtoallowappropriatecorrespondingmaintenancesuggestions.SyntheticExpertiseMethodTheratiotrend,normsthreshold,keygasanalysisandsomeexpertiseareconsideredasdifferentevidencestoconfirmsomespecialfaulttypes.Inotherwords,moresignificantevidenceshavebeencollectedforsomespecialfaulttype,betterassessmentofthetransformerstatusisobtained.Theratiotrendcanbeseenasamodificationoftheconventionalgasratioandkeygasmethod.Obviously,theabovegastrendsshouldbeincorporatedwithotherevidencesundertheexperiencedprocedureforpracticaluse.Normsthreshold,thegassingrate,thequantityoftotalcombustiblegas(TCG),theTPCmaintenanceexpertiseandthefuzzysetassignmentareallimportantevidencesconsideredinthesyntheticdiagnosis.Otherexpertisebasedonatransformerhistoricaldatabaseisalsousedtoanalysethecharacteristicsofacasetransformer.Section3.4givessomedetailsoftheserules.ExpertSystemStructureTheproposeddiagnosticexpertsystemiscomposedofcomponents,workingmemory,aknowledgebase,aninferenceengineandaman-machineinterface.Workingmemory(globaldatabase)containsthecurrentdatarelevanttosolvethepresentproblem.Inthisstudy,mostofthediagnosticvariablesstoredinthedatabasearecurrentgasconcentration,somearefromtheuser,othersareretrievedfromthetransformer'shistoricaldatabase.Notethatthefuzzysetconceptisincorporatedtocreatefuzzyvariablesontherequestofsystemreasoning.Aknowledgerelationship,whichusesthesefacts,asthebasisfordecisionmaking.TheproductionruleusedinthissystemisexpressedinIF-THENforms.Asuccessfulexpertsystemdependsonahighqualityknowledgebase.Forthistransformerdiagnosticsystem,theknowledgebaseincorporatessomepopularinterpretativemethodsofDGA,syntheticexpertisemethodandheuristicmaintenancerules.Section3.4willdescribethisknowledgebase.Anotherspecialconsiderationintheexpertsystemisitsinferenceengine.Theinferenceenginecontrolsthestrategiesofreasoningandsearchingforappropriateknowledge.Thereasoningstrategyemploysbothforwardchaining(data-driven)andbackwardchaining(goal-driven).Fuzzyrules,normsrules,gasratiorules,syntheticexpertiserulesandsomeofthemaintenancerulesandsomemaintenancerules,useforwardchaining.AsforthesearchingstrategyinKES,thedepthfirstsearchingandshort-circuitevaluationareadopted.Theformercanimprovethesearchefficiencybyproperlyarrangingthelocationofsignificantrulesintheinferenceprocedures.Thelatterstrategyonlysearchesthekeyconditionalstatementsintheantecedentthatareresponsibleforestablishingwhethertheentireruleistrueorfalse.Takingtheadvantagesofthesetwoapproachesinthebuildingandstructuringofaknowledgebaseimprovesinferenceefficiencysignificantly.Asforman-machineinterface.KEShasaneffectiveinterfacewhichisbetterthantypicalknowledgeprogramminglanguages,suchas,PROLOGorLISP.Withthehelpofthisinterface,thecapabilityoftracing,explainingandtraininginanexpertsystemisgreatlysimplified.IMPLEMENTATIONOFTHEPROPOSEDEXPERTSYSTEMAnexpertsystemisdevelopedbasedontheproposedinterpretativerulesanddiagnosticproceduresoftheoverallsystem.Todemonstratethefeasibilityofthisexpertsystemindiagnosis,thegasdatasupportedbyMTLofTPChavebeentested.InTaiwan,theMTLofTPCperformstheDGAandsendstheresultstoallactingdivisionsrelatingtopowertransformers.Inreturn,theseactingdivisionsarerequestedtocollectandsupplytheirtransformeroilsamplesperiodically.Afteranalysingoilsamples,morethantenyears'worthygasrecordsarecollectedandclassifiedintothreevoltagelevel,69KV,16KVand345KV.Thus,gasrecordsforonetransformerarecomposedofseveralgroupsofdata.IntheprocessofDGAinterpretation,allofthesedatamaybeconsidered,butonlytherecentdatawhichhavesignificanteffectsondiagnosisarelistedinthelaterdemonstration.InMTL,allgasconcentrationsareexpressedbypminvolumeconcentration.100pmisequalto0.01ml(gas)/100ml(oil).Fromtheexpertiseofdiagnosis,thenormalstatecanbeconfirmedonlybyinspectionofthetransformer'snormslevel.Inpractice,mostofthetransformeroilsamplesarenormal,andthiscanbeinferredsuccessfullyontheearlyexecutionofthisexpertsystem.However,theSuccessofanexpertsystemismainlydependentonthecapabilityofdiagnosisforthetransformersinquestion.Intheimplementation,manygasrecordswhichareinabnormalconditionarechosentotesttheJustificationofthisdiagnosticsystem.Atotalof101transformerrecordshavebeenexecutedandtheresultsaresummarizedinTable5.Amongthoseimplemented,threearelistedanddemonstrated.ShowninTable5aretheresultsof101unitsoftransformersinthreetypesofremedy:normal,thermalfaultandarcfault.Aftercomparingthemwiththeactualstateandexpertjudgement,asummaryofresultswasobtained.Aspreviouslystated,oneunitoftransformermayincludemanygroupsofgasdata.Inevaluation,wedepictedsomekeygroupsinoneunittojustifybecausesometransformersmayhavedifferentincipientfaultsduringdifferentoperationalstages.Somemistakesimplementedfromtestingarecausedbytheremainingoilintheoilsamplingcontainer,unstablegascharacteristicsofthenewdegassingsampleandsomeobscuregastypes.Ifm