基于遗传神经网络的滚动轴承故障诊断方法的研究

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6、tI万方数据-ᳮᜧắ/!ᦻAbstractAbstractTheprobabilityofmachineryfailureisverybigforrollingbearingdamagedinmechanicalequipmentfailure.Theworkingconditionsofthebearingwilldirectlyinfluencetheoperationofthewholemachineryandequipment.Methodsonrollingbearingfaultdiagnosisaredifferent.Withthedevelop

7、mentofscienceandtechnology,itputsforwardnewrequirementstothereal-timedetectionofrollingbearingandtheaccuracyofdiagnosisresultsandmaintenanceplan,whichhasimportantsignificancetotheresearchofrollingbearingfaultdiagnosis.InordertobeabletodiagnosisRollingBearingFailurebetter,thispaperanalyze

8、sthecurrentmainmethodsappliedinrollingbearingfaultdiagnosis,adoptsthetheoryofwaveletanalysiswhichwidelyusedatpresenttode-noisetherollingbearingvibrationsignal,thencomesupwithamorereasonablenewthresholdfunction,whichisanalyzedintheory.Theexperimentalresultshowsthatthenoise