Analysis of Updating Parameters to the Nonlinear Dynamic System of Bridge Structure

A Bayesian probabilistic approach is employed to quantify the uncertain model parameters of nonlinear dynamic systems. A spectral density approach for the identification is used to update parameters by system response measurements. The proposed approach utilizes Fast Fourier Transform which respects the probability distribution of the response signal to obtain the updated probability density function for the nonlinear dynamic system parameters. The proposed approach is well suited to the nonlinear systems identification. For illustrate the proposed approach, a two-span continuous beam bridge nonlinear dynamic system will be employed.