On-line physical parameter estimation and damage detection with adaptive Kalman filtering approach

On-line tracking and detection of system parameters is the main objective of this Study. The proposed method is focus on the development of adaptive covariance matrix of the estimation error. Through the implementation of the adaptive covariance matrix of the estimation residual error the normal extended Kalman filter estimation method can be used. First, the residual error of each time-step is Calculated, and then the adaptive factor matrix is generated in accordance with the residual error. Based on this concept the online adaptive tracking of model parameter can be identified. The advantages of the proposed technique have been demonstrated by using the shaking table test data of a 3-story steel frame Structure with abrupt change of floor stiffness and a collapse test of-a full-scale reinforced concrete frame. Through this modification on the adaptive Kalman filter approaches the estimation Oil the abrupt change of system parameters through numerical and experimental study can be identified on-line.