Evaluation and Analysis of Bridge Modal Parameters Under Intelligent Monitoring Environment

After the bridge is completed, the structural materials will be gradually eroded or aged under the influence of climate, temperature, and building environment. Under long-term static and dynamic loads, the structural strength and stiffness of bridge structures, including bridge deck and bridge support, will decrease with the accumulation of time. Bridge modal parameter identification is not only the premise and foundation of health monitoring, but also the main part of bridge structure dynamic identification. Therefore, this paper proposes a bridge modal parameter identification model based on Bayesian method. The model fully considers the uncertainty of parameters and the selection of modal parameters, and identifies more local information through the probability distribution of model parameters and a posteriori confidence. The reliability of the bridge is monitored in real time through the Bayesian dynamic model, and the monitoring error is only 0.01, which can realize high-precision bridge modal parameter identification.