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1、AbstractWiththedevelopmentofthetechnologydesignofcoalpreparationplant,therotatingmachineryincoalpreparationplantbecomesmorecomplexandmorewidelyused,andwillcauseseriouseconomiclossesinthecaseofanaccident.Onlineconditionmonitoringandfaultdiagnosisforrotatingmachineryeq
2、uipmentofthecoalpreparationplantwillbringaboutlargeeconomicandsocialbenefits.PreparationPlantmechanicalequipmentfaultfeatureextractionequipmentanddiagnoSticrule-basedexpertsystemdesignaretheresearchobjectsofthispaper.Inthisthesis,coalpreparationplantrotatingmachinery
3、wasinvestigated,andthemajorfaultsandfaultsignalcharacteristicswereanalyzed,andexpertrulesweredesigned.First,asimplediagnosticdiagnosticdataandprecisediagnosisforrotatingmachinerywereobtained,andthecharacteristicparametersofthetime-domainsignalaswellaspowerspectrumoff
4、aultcharacteristicfrequencyamplitudeoftherotatingmachineryvibrationsignalswerethenextracted・Then,asfortheissueofvibrationsignalnoiseincoalpreparationplantmachineryandequipment,thediagnoSticparameterswereprocessedinthetimedomaintoreducetheimpactofnoiseonthediagnosis.A
5、tthesametime,inordertogettherightdiagnosisresults,diagnosticthresholdfordiagnosticparametersshouldbesetupappropriately,hereweusethenormalvaluemultipliedbythecoefficientofexperiencetoobtainthediagnosisparametersofthediagnosticthreshold.Afterthis,thediagnosisprocesswas
6、givenbasedonthefailuremechanismofthecoalpreparationplantmachineryandequipment,andfurtherbasedonthediagnoSticprocess,expertrulesweredesignedusingtheframeworkoftheexpertsystemknowledgeLawandproductionrepresentation.Finally,toimplementthesystem,LabVIEWwasusedfordataproc
7、essingandfaultcharacteristicsextractionofrotatingmachinery,andthenthefactlibraryoftheexpertsystemwasformed,andCLIPSwasusedforexpertsystem'sinferenceengine,andlastlytheexpertdiagnosticrulesweredesignedbasedoncoalminingequipmentcharacteristics.Whenthesimulationtime-dom
8、ainvibrationwaveformdataisinputted,thedataprocessingandfaultfeatureextractionmoduleofLabVIEWcanobtaincorrecttimedomainsignalparame