基于信息融合的液壓缸故障模式識(shí)別方法研究.pdf

1、武漢理工大學(xué)碩士學(xué)位論文基于信息融合的液壓缸故障模式識(shí)別方法研究姓名：張衛(wèi)兵申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：機(jī)械工程指導(dǎo)教師：趙秀栩201205AbstractHydraulicsystemshavemanyleadingfeatures，suchaslightweightstructures，easyimplementationofpolelessspeedadjustingandremotecontrol，andmoreover，their

2、operationsalestableThereforetheyalewidelyappliedinnumerousengineeringfieldsandplayakeyroleinnumerousengineeringequipment，includingdriveringandcontr01Thetimelyandaccurateimplementationofhydraulicsystem’Sfaultdiagnosisandi

3、tsnormaloperationisplayingasignificantroleinimprovingefficiency，reducingmaintenancecostsandreducingunnecessaryeconomiclossesAstheexecutionelementofhydraulicsystem，hydrauliccylinder’failurewilldirectlyinfluentthehydraulic

4、systemorevenoverallunitInformationfusiontechnologyisusedinhydrauliccylinder’faultdiagnosisbasedontheanalysisofcurrentresearchRedundancyandcomplementaryinformationofeachsensoraremadefilll嘁，thedecision’Saccuracyandrobustne

5、ssofsystemaleimprovedThefailuremechanismofhydrauliccylinder’intemalleakageWasfirstintroducedinthispaper，testbenchWasbuilttosimulatehydrauliccylinder’intemalleakageThesuitablehardwareswerechoosedandthedataacquisitionwerep

6、rogrammedtorealizethesignalacquisitionAfterSignalcharacteristicswereacquired，informationfusiondiagnosismethodWas西VenbasedontheBPneuralnetworkandWastestedinhydrauliccylinder’intemalleakageDuetotheinfluenceofuncertaintyfac

7、tors，informationfusiondiagnosismethodbasedontheBPneuralnetworkhascertainshortcomingsinthefaultdiagnosisofhydrauliccylinder’SinternalleakageDSevidencetheory’advantageindealingwitlluncertainknowledgemakesupthisdeficiency，b

8、utstillCan’tachievecompletediagnosisAftertheabovemethodswereexplored，comprehensivediagnosismethodbasedontheBPneuralnetworkandtheDSevidencetheoryWasgivenandWastestedeffectiveThisstudyprovideanewwayforimprovingtheaccuracyr