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1、附录ResearchofidentificationofshaftorbitforrotatingmachineXIAOSheng-guang（TestCenterofChongqingUniversity，Chongqing400044，China）Abstract：Anovelapproachfortheidentificationofshaftorbitispresented.Thevibrationdisplacementsignalsacquiredintwomutuallyverticaldirectionsweretre
2、atedthroughnoisesuppressionandfittedtoformashaftorbit.Thenthedirectionchangingcharacterwasextractedandallshaftorbitswereclassifiedandidentifiedwiththefunctiondiscriminatedmethodaccordingtothepatternrecognitiontheory.Eachtypeofshaftorbitwasdescribedindetailwithonecharact
3、er，whichcanhelptojudgetheoperationstatusofthemechanicalandtheextentofthefailure.Theanalysisandsimulationgotgoodresults.Keywords：Shaftorbits；Faultdiagnosis；Geometricfeatures；Patternrecognition；Thinningclassification1TheintroductionWiththedevelopmentofscienceandtechnology
4、andmodernindustry,torotatingmachinesthelarge-scale,high-speedandautomationdirection,theshapeofrotatingmachinerystatemonitoringandfaultdiagnosisisputforwardhigherrequest,theaxistrajectoryforrotatingmachineryisanimportantstatecharacteristicparameters,canbesimpleandstraigh
5、tview,vividlyreflecttherunningstatusofequipment.Throughtotheaxisoftrackobservation,candeterminesomeofthecommonfaults,suchasoilfilmvortexStill,oilfilmoscillation,shaftnotmedium.Thetraditionalaxislocusandshapethedynamiccharacteristicsidentificationisbasedontheman-machined
6、ialoguemode,seriousaffectthelevelofintelligentfaultdiagnosis.Inordertoimprovethedegreeofintelligentfaultdiagnosis,itisnecessarytoin-depthstudythetrajectoryoftheaxisofrotatingmachineryautomaticidentificationtechnology.Axispathatpresent,alreadyhaveseveralidentificationmet
7、hods,including[1-2]invariantmomentmethod,atwo-dimensionalimagegraylevelmatrix[3].literature[1-2]axispathwithsevenmomentinvariantsasfeaturevectors,recognitionbythedistancebetweenthecharacteristicsofaxialtrajectoryshape,literature[3]theaxistrajectoryimagecoding,usingneura
8、lnetworkforidentification.Bothmethodscanbetteridentifyaxispath,butthemethodiscomplex,relativelylargeamountofca
