Dynamic linear modeling of bridge monitored data and reliability prediction

A Bayesian dynamic linear model (BDLM) is introduced, which includes state equation and observation equation of bridge monitoring stress, and the stress is monitored with Bayesian factors. Combining parameters prior information with the early stress monitored data containing noise, the monitored stress state parameters are deduced with Bayesian posterior probability. Optimal stress state estimation uses continuous probability forecast-fixed recursion operator to predict the bridge stress. The prediction formula of bridge reliability is given based on BDLM of bridge stress. Finally, an actual example is provided to demonstrate the applicability and feasibility of the proposed model. © 2016, Editorial Department of Journal of Tongji University. All right reserved.