Structural damage identification based on recursive proper orthogonal decomposition and strong tracking extended Kalman filtering
Aiming at the problem that the existing damage identification methods are difficult to track the structural damage in real time and require a large amount of calculation,a model order reduction and online damage identification method based on the com-bination of recursive proper orthogonal decomposition(RPOD)and strong tracking extended Kalman filter(STEKF)is proposed.The structural damage identification under dynamic load is studied.The RPOD method is used to update online and construct the reduced-order model reflecting the structure state in real time,which solves the problem of large calculation and difficult conver-gence of dynamic analysis of multi-degree of freedom structures under unknown loads.Meanwhile,the evolution of damage is tracked and located.The STEKF method is used to track the state vector of the reduced-order model and identify the reduced-order model parameters degraded by damage.The feasibility of the proposed method is verified by numerical simulation of a six-story shear frame and model test of a three-story steel frame.The results show that the proposed method can accurately construct the re-duced-order model and track the time-varying history of the reduced-order model parameters.Meanwhile,it can effectively identify the location and extent of the damage of the shear building structure,even when dealing with high levels of noise,it retains high accuracy.
万方数据
维普
