提取磨削主轴型转子轴承系统在加速度期间振动信号的特征研究外文文献翻译中英文翻译.docx
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提取磨削主轴型转子轴承系统在加速度期间振动信号的特征研究外文文献翻译中英文翻译.docx
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提取磨削主轴型转子轴承系统在加速度期间振动信号的特征研究外文文献翻译中英文翻译
附录Ⅱ
Proceedingsofthe7thICFDM2006
InternationalConferenceonFrontiersofDesignandManufacturing
June19-22,2006,Guangzhou,China
Pages255-260
ASTUDYONVIBRATIONSIGNAL-BASEDFEATUREEXTRACTION
FORGRINDINGSPINDLE-TYPEDROTOR-BEARINGSYSTEM
DURINGACCELERATION
Jong-KweonPark,Bong-SukKim,Soo-HunLeeandJun-YeobSong
IntelligenceandPrecisionMachineryResearchDivision,KIMM,305343,Rep.ofKorea
SchoolofMechanicalEngineering,AjouUniversity,443749,Rep.ofKorea
Abstract:
Thegoalofsystemmonitoringistominimizeeconomicloss,toincreasereliability,tomaximizeproductivity,andtomaintainproductqualityinmanufacturing.Sincevibrationsignalssufficientlycontaintheabundant
runninginformationoftherealsystemandthehiddenfaultsymptoms,thefeatureextractionthroughthosesignalsiswidelyappliedforperformanceevaluationfaultdiagnosticsofrotatingmachineries.
Thispapershowsfeatureextractionfromvibrationsignalsgatheredinthegrindingspindle-typedrotor-bearingsystemduringaccelerationinordertomonitoranabnormalconditionofcurrentsystemlikeshaftcrackbyusingvariouskindsofsignalprocessingmethodssuchastheFastFourierTransform,Short-TimeFourierTransform,Wigner-VilleDistribution,andDiscreteWaveletTransform.Aswell,theresultoffeatureextractioninshaftcrackconditionwascomparedwiththatinnormalcondition.
Keywords:
Featureextraction,Grindingspindle-typedrotor-bearingsystem,Non-stationarysignalprocessingmethod,Acceleratingprocess,Wavelettransform
1.Introduction
Theconditionmonitoringorfaultdiagnosisinrotatingmachineriesandmachiningprocessisacrucialrequirementinordertomaintainreliability,safety,andproductqualityandtopreventfailuresordamages.Comparedwithothermachiningmethods,high-performancegrindingprocessisoneofthemostcomplicatedandimportantcuttingprocessesasfinalmachiningstage;consequently,themonitoringofgrindingprocessandmachineismuchmorenecessaryinordertosupervisetheprocessandmachineandalsodetectabnormalities.Amongvariouskindsofapproaches,vibrationsignalanalysismethodforfeatureextractionandnondestructivedamageidentificationhasbeenwidelyutilizedduetocapabilitytocarrytheabundantdynamicinformationandtoindicatedetailedmotionofmechanicalsystemsandtodescribesimultaneouslywhenafaultoccursorwhatisitsfrequency.However,sincemostofthevibrationsignalssampledonmechanicalsystemsarenon-stationaryortransientsignalswhichsufficientlycontainadditionalinformationorabnormalsymptom,whichcannotberevealedfromstationarysignal,itisthekeyhowtoaccuratelydrawdominantfeaturecomponentsfromvibrationsignalsbecausenon-stationarysignalismorecomplexthanstationarysignal.Uptodate,forfeatureextractionofrotatingmachinery,manykindsofresearchresultshavemainlybeenfocusedonthestationarysignalprocess;ontheotherhand,littleresearchhasbeenaccomplishedforthenon-stationarysignalprocesssuchasspeed-upprocess;especially,thereisalmostnofeatureextractionusingvibrationsignalofspeed-upconditioninthefieldofgrindingprocess.
.Thispaperwasaboutastudytoextractthedominantfeaturesfromvibrationsignalsacquiredinalaboratorygrindingspindle-typedrotor-bearingsystemduringaccelerationbyusingseveralsignalprocessingmethodssuchasTimeDomainAnalysis(TDA),Frequency
DomainAnalysis(FDA),andtheTime-FrequencyAnalysisMethod(TFAM).Modaltesting,whichdetectsdynamiccharacteristicsofthesystemlikenaturalfrequency,wasperformedforthepurposeofdeterminingoperatingrangeforaccelerationintestsetup.Vibrationdatafromthebearinghousingpassingthroughthedistinctiveresonancefrequenciesandfrequencybandinspeed-upprocessweregatheredthroughtheexperimentswithnormalandcrackshaftcondition.Togetprominentsignalsofabnormalityfromacquiredtimedataasafundamentalstagefordiagnosisormonitoringtechnology,theFastFourierTransform(FFT),Short-TimeFourierTransform(STFT),Wigner-Villedistribution(WVD),andWaveletTransform(WT)usingcommercialsoftwarewerecarriedoutandcomparedwitheachresult
2.TheoreticalBackground
2.1.ReviewofSignalAnalysisMethods
Therearetwomajortypesofsignalinthefirstnaturaldivisioncategory:
thestationarysignalandnon-stationarysignal.Stationarysignalsareconstantintheirstatisticalparametersovertime.Moreover,stationarysignalsarefurtherdividedintodeterministicandrandomsignals.
Randomsignalsareunpredictableintheirfrequencycontentandtheiramplitudelevel,buttheystillhaverelativelyuniformstatisticalcharacteristicsovertime.
Ontheotherhand,non-stationarysignalsaredividedintoc
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- 关 键 词:
- 提取 磨削 主轴 转子 轴承 系统 加速度 期间 振动 信号 特征 研究 外文 文献 翻译 中英文
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