Reliability prediction of aging bridges based on Bayesian dynamic linear model

The performance of bridge structures was time-dependent, which was able to be depicted by time series models. The Bayesian dynamic linear model(DLM) was then introduced. The state equation and observation equation of resistance degradation of the bridge structures were established by applying the Bayesian dynamic linear model. The resistance degradation state parameters were deduced with the Bayesian posterior probability. Through continuous recursion operation of probability forecast-updating the optimal resistance degradation state probability was obtained to predict the bridge degradation resistance. The DLM was built to predict the changing tendency of bridge resistances. To allow for the epistemic uncertainty of state variants, the discount factor was used to specify the variance of state errors. The prediction formula of bridge reliability was built on the basis of the Bayesian DLM of bridge resistance probability. Finally numerical examples verify the applicability of the proposed model.