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基于动力响应的结构非线性单元模式识别和参数确定 Title:StructuralNonlinearUnitPatternRecognitionandParameterDeterminationBasedonDynamicResponse Abstract: Inrecentyears,therehasbeenagrowinginterestinstructuralnonlinearitiesduetotheirsignificantinfluenceonthedynamicbehaviorofstructures.Thispaperfocusesonthedevelopmentofanovelapproachforpatternrecognitionandparameterdeterminationofstructuralnonlinearunitsbasedontheirdynamicresponsecharacteristics.Theproposedmethodologyaimstoenhancetheunderstandingandanalysisofstructuralsystems,withpotentialapplicationsinvariousfieldssuchascivilengineering,mechanicalengineering,andaerospaceengineering. 1.Introduction: Structuralsystemsoftenexhibitnonlinearbehaviorduetothepresenceofvariousphysicalphenomenasuchasmaterialnonlinearity,geometricnonlinearity,anddampingnonlinearity.Theaccurateidentificationandcharacterizationofthesenonlinearitiesarecrucialfortheefficientdesignandanalysisofstructures.However,traditionallinearanalysismethodsfailtocapturethecomplexbehaviorofnonlinearsystems.Therefore,theuseofadvancedtechniquesforpatternrecognitionandparameterdeterminationisessential. 2.OverviewoftheProposedMethodology: Theproposedmethodologyisbasedontheanalysisofthedynamicresponseofstructuralnonlinearunits.Thekeystepsofthemethodologyareasfollows: 2.1DataAcquisition: Experimentaltestingornumericalsimulationsareconductedtocollectthedynamicresponsedataofthenonlinearunitunderdifferentloadingconditions.Thedatashouldincludevariousparameterssuchasdisplacement,velocity,acceleration,andforce. 2.2DataPreprocessing: Thecollecteddataispreprocessedtoeliminatenoiseandoutliersandensuretheconsistencyandintegrityofthedataset.Techniquessuchaswaveletdenoisingandoutlierdetectionalgorithmscanbeemployed. 2.3FeatureExtraction: Variousfeaturesofthedynamicresponsedataareextractedtorepresentthebehaviorofthenonlinearunit.Commonlyusedfeaturesincludestatisticalmoments,spectralfeatures,time-frequencyfeatures,andwaveletcoefficients.Featureselectiontechniquesmaybeappliedtoreducethedimensionalityoftheda