A method for corrosion depth prediction of gas pipeline based on Bayesian estimation

In order to accurately predict the corrosion depth of gas pipeline and its confidence interval, a nonlinear prediction model for the maximum corrosion depth of gas pipeline under different sample independencies was proposed by means of the Bayesian estimation method, based on the probability distribution of the model parameters. Then, this model was solved using the MCMC method. It is shown that the corrosion depth prediction model newly established in this paper can better predict the corrosion depths and confidence intervals of urban metal gas pipelines under different sample independencies, and it can be used to quantitatively evaluate the corrosion safety issues of metal gas pipelines.