Identification of Damping Ratios of Long-Span Bridges Using Adaptive Modal Extended Kalman Filter

Abstract

Identification of damping ratio is very important for the assessment of service performance of long-span bridges. In this paper, an adaptive EKF in modal domain, named adaptive modal EKF (AMEKF), is proposed for identifying the damping ratios of long-span bridges. The dominant modes are selected, and the dimension of the extended state vector is significantly reduced with the aid of modal coordinate and the corresponding modal transformation. Then, the EKF principle is employed for the identification in modal domain. Moreover, an innovation-based procedure is presented to adaptively adjust the covariance matrix of process noise for the purpose of assuring the parametric identification accuracy. A forgetting factor is employed to put proper weights for the previous and current estimates in each time step. A merit of the proposed approach is that all the damping ratios of the selected modes can be simultaneously identified. The effectiveness of the proposed approach is numerically verified via a long-span suspension bridge. The dynamic tests on a simply supported overhanging steel beam and an aeroelastic model of some long-span suspension bridge are further used for the validation. Results show that the proposed approach is capable of identifying damping ratios with acceptable accuracy.