Research On Damage Identification Of A Continuous Rigid Frame Bridge Based On ARMA Model Combined With Vehicle-Bridge Coupling Theory

The damage identification of structure is not only an active research field in the current civil engineering, but also seems to have broad background, theory and technology. The research method based on Autoregressive Moving Average(ARMA) model is widely used in state predicts or system identification in the past few decades, and it's still in the rapid development stage and has a bright prospect.According to the current situation, an integrated ARMA model algorithm combined with vehicle-bridge coupling theory is developed in this study for the structural health monitoring of structure. In which, the partition and normalization procedure is firstly employed in signal pre-processing to remove the influence of various loading conditions, the auto-correlation function of the normalized signal is utilized as a substitute of analysis input to overcome noise effect and avoid the bias in Autoregressive Moving Average(ARMA) model fitting caused by noise disturbance as well.In numerical study, vehicle-bridge coupling vibration of continuous rigid frame bridge is numerically simulated in finite element software ANSYS and the acceleration responses of structures in various damage cases are analyzed utilizing the proposed integrated method. A damage indicator(DI) based on the ratio of the variance of residual error of the model in the unknown state to ones in the reference state is defined for damage detection and localization, which performs better than that based on Mahalanobis distance between ARMA models, with which Autoregressive(AR) parameters serving as damage feature vector. The thesis presents the analytical results of damage identification for the continuous rigid frame bridge without regard for noise, and comparison is made with the results of damage identification accounting for noise.Finally, the proposed method is proved to be appropriate and very sensitive to damage.