Structural Nonlinear Damage Identification Based On ARCH Model And Improved Evidence Theory

In recent decades,China's building structure and infrastructure has developed rapidly,and various new buildings have risen from the ground.However,the performance of old buildings has been declining as the years of use have passed.On the one hand,during normal use,the durability of the material decreases,the mechanical properties change,and the building is corroded.On the other hand,buildings will encounter many serious natural disasters during their use,including typhoons and earthquakes.These will cause different degrees of damage to the building,which will seriously affect the comfort and safety of the building and threaten the lives and property of the people.Therefore,structural damage identification has become one of the hot research directions in the field of civil engineering in recent years.Among them,structural damage identification based on structural vibration characteristics analysis is currently recognized as a method with wide applicability and accurate recognition results.Time series analysis applied in the financial industry is now gradually applied to engineering,and has achieved good results in the field of damage identification in civil engineering.At present,the damage identification of structures is mostly based on linear damage,while the research on nonlinear damage is less.Therefore,this paper will focus on the application of non-linear time series model in structural non-linear damage identification,and compare it with the application of stationary time series in non-linear damage identification,and further improve the effect of damage identification by improving the weighted evidence theory.This paper first introduces the related theory of stationary time series AR model,including the introduction of model formula,the stability of the model,the Green's function of the model,the autocorrelation function and the partial autocorrelation function,and elaborates the modeling steps and modeling of the AR model.At the point of attention,the analysis of the cepstrum distance theory based on the ARMA family is carried out,and the linear damage identification index CMI is constructed and converted into the interlaminar stiffness index CMCI.This paper then focuses on the related theory and modeling process of the nonlinear ARCH model.Based on the modeling of the AR model,the residual model is used to further apply the ARCH model to the damage identification,and the nonlinear damage transformation index SOVI is constructed.It is converted to the interlaminar stiffness index SOVCI.Then,using a three-layer frame experiment and a ten-degree-of-freedom inter-layer shear structure as the carrier,the above two damage theories and indicators are applied to these two examples,and through comparative analysis under various different conditions.The result that the nonlinear index SOVCI recognition effect is superior is obtained.Finally,this paper introduces the classical D-S evidence theory in uncertainty reasoning,and expounds the basic combination rules and the existing problems of the fusion of high-conflict evidence sources.In this paper,the problem of evidence theory is solved by the improved weighting method.Based on this,an improved evidence theory based on the judgment conflict coefficient is proposed.The two damage indicators are merged through the improved method,and the positioning is more accurate.The recognition result reduces the possibility of misjudgment.