中科大机械设备非平稳信号的故障诊断原理及应用讲义00序、前言

1取故障信息的非平稳信号处理方法—Wigner-Ville时频分布、短时傅氏变换波、Laplace小波、Hermitian小波、BriefIntroductionThisbookexpoundstheemergenceandchequipment,physicalmeaningoforthogonalsignaldecompositionandengineeringbackground.Itcontainsnon-stationarysignalprocessingmethodsfromwhichthefaultinformationisextrpacketanalysis;Harmonicwavelet;Laplacewavelettheirbasicprinciplesandapplications.Theilluminationofsignalreprocessingtechniquesofwavfollowing:Waveletpacketsandautoregressivespectrumanalysis;Surffrequencybandenergyofwaveletpacketdecomposition;orbit;Geneticwaveletanalysis;Fuzzyclusmonitoringanddiagnosisnetworksystemofmechanitechniques.Practicalapplicationsofmonitoringanddiagnosisinindustrialenterprisesareenumerated.Thecontentsofthebookaresubstantialandadvancedwithdesirablepractmanyscientificandtechnicalworkerswhoundertakeconditionmonitoring,faultdiagmanagementandmaintenabookforundergraduatesandpostgraduatesofmechanicalmanuspecialtiesetc.incollegesanduniversities.2序的分析。本书作者承担并完成了三项国家自然科学基金项目，在此基础上取得了多项研究成果，3提取十分重要。S.G.Mallat在他的论文中多次强调正交作者们有幸承担国家自然科学基金项目“处理机械动态信息的模糊数学方法”（编号：5870235，1988—1989）、“机械故障瞬变信息独立化提取的应用研究”（编号：59275241，），41、汲取国内外在本领域的最新研究成果，总结作者们在非平稳信号处理研究和应用中的新2、从工程应用角度出发，介绍了小波变换等非平稳信号处理技术在故障诊断中的原理和应3、本书的结构编排合理，既有基本方法，又有综合方法，内容深入浅出，工九州工业大学丰田利夫教授和陈鹏教授的指导、交流和合作研究感到十分愉快并表示诚挚的谢52.1机械摩擦、松动故障特征和诊2.2主分量分析2.4正弦分量和有色噪声的合理4.1短时傅立叶变换4.2.1多分辨分析及其工程意义4.2.2正交小波基的构造与信息独立化的提取4.3小波包信号分解4.4.1轧钢机振动分析4.4.2大型矿山电铲提升系统振动分析64.4.3压缩机齿轮箱轴瓦监测诊断5.4.1谐波小波分解及时频剖面图在旋转机组振动5.4.2谐波小波轴心轨迹阵列的实现6.3.2大型水轮机轴系转动时一789Chapter1Outline1.1Non-stationaryproblemsinmechanicalmonitoringand1.2Non-stationarysig1.3Orthogonaldecompositionofsignalandindependentextractionofinformation1.4DevelopmentandstatusquoofapplicationsonwavelettechniquesiChapter2Principalcomponentsandautoregressivespectrumanalysisanditsapplication2.1Faultcharacteristicsofmechanicalfrictionandloosenessanddiagnosiscountermeasure2.2Principalcomponentanalys2.3Principalcomponentsandautoregressivespectrumanalysis2.4Reasonableestimationofsinusoidandcolorednoise2.5Engineeringapplications2.5.1Frictionfaultdiagnosisofturbo-generatorset2.5.2FrictionfaultdiagnosisoflargecentrifugalcompressorsetChapter3Wigner-Villedistributionanditsapplications3.1DefinitionofWigner-Villedist3.2MainPropertiesofWigner-Villedist3.3CalculationofWigner-Villed3.4CrossterminterferenceandsupChapter4Time-frequencyanalysisofnon-stationarysignalprocessinganditsapplications4.1ShorttimeFourier4.2.1Multi-resolutionanalysisanditsengineeri4.2.2Constructionoforthogonalwaveletbasisandindependentextractionofinformation4.3Waveletpacketsandsignalde4.4Engineeringapplications4.4.2Vibrationanalysisofliftingsystemoflargeelectricexcavator4.4.3MonitoringanddiagnosisofgearboxaxlebushofcompressorChapter5Principleofharmonicwaveletanditsengineeringapplications5.1Definitionandorthogonalityofharmonicwavelet5.2Newlandfastalgorithmandtime-frequencyprofileplot5.2.2Harmonicwavelettime-fr5.2.3Wavelettime-f5.3Harmonicwavelet5.4ApplicationexamplesofHarmonicwaveletforvibrationcharacteristicextractioninrotatingmachinery5.4.2HarmonicwaveletorbitanditsirregulChapter6CorrelationfilteringoffeaturewaveusingLaplacewavelet6.1Laplacewaveletanditscharacteristics6.1.1DefinitionofLaplacewavelet6.1.2CharacteristicsofLaplacewavelet6.2CorrelationfilteringbasedonLaplacewaveletbasisfunction6.2.1BasisfunctionlibraryofLaplacewavelet6.2.2Correlationfiltering6.3Applicationexamp6.3.1Modalparameterrecognitionofrotortest-bed6.3.2Extractionoffirstordernaturalfrequencyofrunningshaftoflargehydro-turbineset6.3.3Vibrationsignalrecognitionofinternal-combustionenginecylinderheadChapter7Matchingpursuitsignaldecompositionanditsapplications7.1Signalexpansionandinnerpr7.2Matchingpursuitsignalexpansion7.3Matchingpursuittime-frequencyrepresentationanddistribution7.4Impulseresponsefeatureextractionformechanicalsys7.5.1Freecross-termtime-frequencydis7.5.2FeatureextractionandfaultdiagnosisforreciprocatingmachineryChapter8Waveletpacketsandautoregressivespectrumanalysis8.2Engineeringappli8.2.1Non-stationaryrotating8.2.2EarlydiagnosisforlatentdefectsinChapter9Surveillanceoffrequencybandenergyofwaveletpacketdecomposition9.2Loosenessfaultdiagnosisofbearingbridgeofturbo-generatorset9.3Analysisofvibrationexcitedbysteaminhigh-pressureturbine9.3.1Vibrationmeasu9.3.2Siteanalysisa9.3.3MeasuresofvibrationreductionChapter10Waveletfractaltechniqueanditsapplicationfornon-stationaryfaultdiagnosis10.1Waveletanalysisandfractalfornon-stationaryfaultdiagnos10.2Principleofwaveletfractaltechnique10.3Calculationofboxdimensionofwaveletfractalforvibrationsignal10.3.1Genericalgorithmofboxdimensionofdiscretesignal10.3.2Disadvantageofgenericalgorithmofboxdimensionanditsimprovement10.3.3Empiricalformulaofscale-invariantregionofboxdimensionviawaveletfractal10.4MechanicalloosenessfaultanalysisusingwaveletfraChapter11Geneticwaveletanditsapplicationtointernalcombustionenginediagnosis11.3Foundationoffaultdiagnosisforinternalcombustion11.3.1Faulttypesoncomponentsofinternalcombusti11.3.2Formationofvibrationandnoiseininternalcombustionengine11.3.3Basicprincipleofvibrantdetectionofinternalcombustionengine11.3.4Experientialknowledgebaseonvibrationanalysisofinternalcombustionengine11.4ComputersimulationofgeneticwaveletandfaultdiagnosisofinternalcombustioneChapter12Fuzzyclusterdiagnosisnetworkbasedonwaveletpacketsanditsapplication12.1Featureextractionbasedonwavelet12.2Classificationonfuz12.2.1Classifiedprinciple12.2.2ConstructionoffuzzyclusterneuralnetworkbasedonwaveletpacketsChapter13Hermitiancontinuouswavelettransformandsignalsingularitydetection13.1Singularityinmecha13.2Basicprincipleofsignalsingularitydetectionusingwavelettransform13.2.1Definitionofsingulari13.2.2Convolutionrepresentationofwavelettransform13.2.3Relationamongextremepoints、overstepzeropointsofwavelettraandsingularityofsignal13.2.4Progressofwavelettransforminsingularitydetection13.3DefinitionandcharacteristicresearchonHermitianw13.3.1DefinitionofHermitianwavelet13.3.2CharacteristicresearchofHermitianwavelet13.4Hermitiancontinuouswavelettransformandtherepresentationofdecompositionresult13.4.1RealizationofHermitiancontinuouswavelettransform13.4.2Amplitu