Damage Identification of Bridge Based on Kalman Filter by Using Partial Structural Measurements

The damage identification of bridge structures is still a challenging task. The identification accuracy of most current methods relies on the location and number of sensors adopted. In this paper, based on the Kalman filter algorithm, a novel method is proposed to identify the damage of bridge structure by using only partially measured structural responses. The damage occurred is regarded as the sudden degradation of the stiffness parameter. Thus, the abruptly changing stiffness parameter can be represented by three coefficients, that is, the undamaged stiffness value, the damage instant, and the damaged stiffness value. In this way, the identification of each stiffness parameter is transformed into the identification of three coefficients instead. Then, the Kalman filter algorithm is used for the identification of structural state using partially measured structural responses. Finally, three defined coefficients are estimated by the nonlinear least-squares optimization, and the original abruptly changing stiffness parameters can be reconstructed. Numerical simulation is conducted to validate the effectiveness of the proposed method. It is demonstrated that only a few accelerometers are required in the proposed method, and the identification accuracy is not depend on the position of sensors. In addition, the proposed method is capable to identify the damages quantitatively and directly with no need to locate damages in advance.