基于非線性動力學的滾動軸承故障趨勢分析.pdf

1、江蘇大學碩士學位論文基于非線性動力學的滾動軸承故障趨勢分析姓名：馬東玲申請學位級別：碩士專業(yè)：檢測技術與自動化裝置指導教師：陳曉平20080601江蘇大學碩士畢業(yè)論文ABSTRACTTheoilweUdrillingisakindofcontinuousprocessOncetherehappensanyaCcident，theeconomiclosswillbeve叫seriousThedrillingisalarge—Scaleeq

2、uipmemwithmanytransmissionmechanisms，anditsrollingbe2uringseasilybreakdo、VnThus，deVelopingtheearlyfaultdiagnosisofdrillingrollingbearingshasgreatpraCticalsignificanceAccordingt0mecharacteristicsofbe州ngs向ult，thisdissertat

3、ionist0researchmeearlyfaultdiagnosismethodofrollingbearings，andgiVeapredictiontoit’sdeVelopmenttIendInmisdissercation，tllefaultmechanismandthevibrationcharacteristicsofrollerbearingsaresummarized，thenonlineardyn鋤icsanaly

4、sismethodsofmeVibrationsignalareintroducedBecauseofthenonstationaD，andnonlinearVibrationsignalwhentherollingbe撕ngshave蠡mlts，ab叭erdia印osise髓Ctisexpectdtogetbythenonlinearanalysismethodwhichare納ctalanalysisaIldsymbolicdyn鋤

5、icsanalysisTheaboVetwometllodsaureusedtoextractthefaultfeaturesofthebearingsVibrationsignalinthisp印erOnthatbasis，thesupportVectormachine(SVM)whichisbasedonclassification，isproposedtecognisedif|FerentpattemsTheresultofexp

6、erimentindicatesthatthe“，ononlinearanalysismethodise行ectiVe，andthetwoen仃opiesofsymbolicdynamicsmethodarebothbettermantheconelationdimensionmethodevenifunderthesmallsamplesconditionInordertopredictthefaulttrendofthebearin

7、g，thenonlinearlocalpredictionalgorithmisusedwhichisbasedonthechaotictimeseriesinthisdissertationTheresultofexperimentindicatesthatthepredictionalgorithmhaSagoodprecisionKeyWbrds：rollingbearings，faultdiagnosis，thenonlinea