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ApplicationofmultisensorinformationfusiontechnologyonfaultdiagnosisofhydraulicsystemLQZhang1,2,GLYang1,2,LGZhang3andSYZhang41SchoolofEnergyandPowerEngineering,LanzhouUniversityofTechnology,QiliheDistrict,Lanzhou,730050,China2WenzhouAcademyofPumpandValveEngineering,LanzhouUniversityofTechnology,MadaoWestRoad,Oubei,Yongjia,Wenzhou,325105,China3HandanSpecialSinkingLimitedCompanyofChinaCoal,ChinaCoalFifthConstructionCompany,FuxingDistrict,Handan,056003,China4ChineseAcademyofAgriculturalMechanizationSciences,ChaoyangDistrict,Beijing,100083,ChinaEmailizlq163.comAbstract.Thestructurallayersandmethodsofmultisensorinformationfusiontechnologyareanalysed,anditsapplicationinfaultdiagnosisofhydraulicsystemisdiscussed.Aimingathydraulicsystem,amodelofhydraulicfaultdiagnosissystembasedonmultisensorinformationfusiontechnologyispresented.Choosingandimplementingthemethodofinformationfusionreasonably,themodelcanfuseandcalculatevariousfaultcharacteristicparametersinhydraulicsystemeffectivelyandprovidemorevaluableresultforfaultdiagnosisofhydraulicsystem.1.IntroductionHydraulicsystemplaysanimportantroleinengineeringindustry.Toensurethathydraulicsystemisworkingsafely,reliablyandwithoutanypotentialaccident,itsfaultdiagnosisisveryimportant.Butengineeringpracticeshowsthatfaultdiagnosisbasedononeparametercannotmakesurewhetherthesystemisoutoforderornotallthetime.Andbymultisensorinformationfusiontechnology,differentparametersabouttheoperatingconditionsofthehydraulicsystemfromdifferentanglescanbeobtained.Integratingandfusingalloftheparameterseffectively,thefaultdiagnosisofhydraulicsystemissuccessfullycarriedoutandthefaultofhydraulicsystemcanbeidentifiedandlocatedmoreaccurately1,2.Inthispaper,thestructurallayersandmethodsofmultisensorinformationfusiontechnologyareanalyzed,andthenitsapplicationinfaultdiagnosisofhydraulicsystemisdiscussed.2.TechnologyofmultisensorinformationfusionMultisensorinformationfusionisamultilayer,allroundprocessingprocedure.Itcandetect,fuse,correlate,estimateandcombinealloftheparametersmeasuredinhydraulicsystemtoachievethestateestimation,includingsituationestimationandriskestimationofthesystemaccurately1,2.Tofaultdiagnosissystemofhydraulicsystem,multisensorinformationfusionconsistsofdatafusionandknowledgefusion,inadditiondatatoknowledgefusion,thatisdatamining,isalsoincluded.2.1.LayersofmultisensorinformationfusionAsshowninfigure1,informationfusioncanbepartedinto3layers3.Figure1.SchematicdiagramoflayermodelofinformationfusionInformationfusionofdetectinglayerandfaultdiagnosis.Informationfusionofdetectinglayeristofuseoriginalinformationmeasuredbythesamekindsensorsbeforetheirpretreatment.Bythis,infirsttime,theoperatingconditionsofthesystemcanbemonitoredintuitivelyandperceptually.Atthesametimealloftheinformationisinputtedintodatabasetocarrydataminingout.Informationfusionoffeaturelayerandfaultdiagnosis.Informationfusionoffeaturelayeristofuseoriginalinformationmeasuredbyallkindssensorsandrelatedtheoreticalknowledge.Bythisthefaultofhydraulicsystemcanbeidentifiedandlocated,butitisall.Thespecificmethodsandtechnologyaimingatthefaultdiagnosiscannotbepresentedhere.Informationfusionofdecisionlayerandfaultdiagnosis.Thisisthefusionofthehighestlayer.Allinformationmeasuredbydifferentkindssensorsandrelatedtheoreticalknowledgearefusedandthecountermeasures,thatisthespecificmethodsandtechnologyaimingatthefaultdiagnosisincludingfaultisolation,redundancycontrollingandsoonareachieved.Andifthecountermeasuresareprovedtobeworkable,theexperienceofthistypicalcasecanalsobeinputtedintothedatabasetousesometime.2.2.MethodsofmultisensorinformationfusionTherearemanymethodsofmultisensorinformationfusion,suchasbasedonBayestheory,DemperShaferDStheory,neuralnetworktechnologyandsomeestimationtheoryandsoon4,5.AsamodifiedtheoryofBayestheory,DStheory,alsocalledevidencetheory,hasawiderapplicationinmultisensorinformationfusiontechnology.Thismethodavoidsthesimpleassumptiontoanunbeknownprobabilityandshowsthedeterminacyandindeterminacyofinformation.ThebasicmethodofDStheoryisdividingtheevidencesetintomutuallyindependentparts.Eachevidenceparthasaprobabilitydistributionfunctiontotherelatedtheoreticaldiagnosis,alsocalledbelieffunction.Basedonthefusionofdifferentevidenceandtherelatedtheoreticaldiagnosis,thatistointegrateallofthebelieffunctions,thetotalbeliefdegreeofintegratedevidencebasedontherelatedtheoreticalknowledgecanbeobtained6,7.Figure2showsthecourseofreasoningofDStheory.Figure2.SchematicdiagramofthecourseofreasoningofDStheory3.Applicationofmultisensorinformationfusiontechnologyonfaultdiagnosisofhydraulicsystem3.1.StructureandprincipleofthefaultdiagnosissystemThecommonfailuremodesofhydraulicsystemconsistofoilleakage,abrasion,corrosion,fatigue,cavitations,hydraulicpressureseizure,andimpactbreakandsoon.Thustoahydraulicsystemthemonitoringparametersincludehydraulicpressure,flowquantity,temperature,oilleakageandsoon.Thefaultdiagnosissystemofhydraulicsystembasedonmultisensorinformationfusiontechnologyincludestwofunctionmodules,dataacquisitionmoduleandcentralprocessmodule.Thedataacquisitionmoduleisinstalledateachmajorcomponent,includingsensor,signalconditioningcircuit,A/Dconvertor,andbusinterfaceandsoon,toachieveeachstatussignalofthehydraulicsystemacquisitionandtransmission.ThecentralprocessmoduleconsistsofCPUandthesoftware.Consideringthatthecomplexitiesofhydraulicsystem,useIPCastheCPUofinformationfusiontoachievethedataanalysis,fusion,faultdiagnosisandgivingcountermeasure79.Figure3showstheblockdiagramofthemodeloffaultdiagnosissystem.Figure4showstheflowchartofthediagnosticprogram.3.2.CharacteristicsofthefaultdiagnosissystemAlloftheoperatingparameters,includinghydraulicpressure,flowquantity,temperature,oilleakageandsoon,canbemonitoredanytime.BasedonDStheory,byfusingalloftheoperatingparametersmeasuredbysensorsthestaterecognition,thetypicalfaultdiagnosis,andthesafetyprotectioncanbeachievedsuccessfully.3.3.KeytechnologyofthefaultdiagnosissystemInordertomakeallthesignalsaccurate,howtochooseeachsensorreasonablyandpretreatallthesignalsavailably.Inordertomakesurethatthefaultdiagnosisisright,howtochooseandimplementthemethodofinformationfusion.BecausethemethodofDStheorymaynotworkwellundercertaincondition,theothermethods,forexample,neuralnetworktechnologymaybeabetterchoice.Figure3.BlockdiagramofthemodeloffaultdiagnosissystemFigure4.Flowchartofthediagnosticprogram4.ConclusionsBasedonmultisensorinformationfusiontechnology,thefaultdiagnosissystemmakesfulluseofmultiplesignalsthatcanbemeasuredfromhydraulicsystemtorealizeconditionalarminganddiagnosisofthehydraulicsystems.Thiscanincreaseworkefficiencyandreliabilityofthehydraulicsystems.Themodeloffaultdiagnosissystemofhydraulicsystempresentedinthispaperisageneralizedmodel.Inspecificengineeringpracticethemonitoringparametersandtheactualstructureandimplementationofthefaultdiagnosissystemdependonthecorrespondinghydraulicsystem.AcknowledgmentsWewouldliketothankthesupportofScienceandTechnologyProjectofWenzhouCityH20110007andNaturalScienceFundofGansuProvince1014RJZA023.References1VarshneyPK1997MultisensorDataFusionElectronicsCommunicationEngineeringJournalDecember245–2532WaltzEandLlinasJ1991MultisensorDataFusionArtechHouse35–423AlanNS2001DatafusionsystemengineeringIEEEAESSSystemsMagazineJune7–144HalldL2000MathematicaltechniqueinmultisensordatafusionArtechHouse15–215HFDurrantWhyte2001SensormodelsandmultisensorintegrationTheInt.J.ofRoboticsResearch7687–926MouradO2004SomenotesonfusionofuncertaintyinformationInt.J.ofIntelligentSystems196457–4717RichardT2003PrinciplesofeffectivemultisensordatafusionMilitaryTechnology27529–378ZhangYDandJiangXW1999MultisensorinformationfusiontechniqueanditsapplicationonintelligentfaultdiagnosissystemChineseJ.ofTransducerTech.18218–229AnFY,LuHW,LiuCJ,etal.2006ResearchandapplicationofinformationfusiontechnologyonmachineryfaultdiagnosisChineseJournalofChongqingUniversity29115–18
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