Bayesian dynamic modification of corrosion in a cylindrical rod quantified by guided waves technique

In this study, both estimation and modification strategies of measurement uncertainty were investigated when using a guided waves (GWs) technique to quantify the corrosion level of a cylindrical rod induced by an accelerated setup, thus providing essential and reliable information for making decisions regarding necessary remedial work. First, the remnant diameters under corrosion were quantified based on the dispersion characteristics of GWs, and the measurement uncertainty derived from time-frequency analysis was specifically considered. After demonstrating the equivalence with the self-adaptive Monte Carlo method, the method in guide to the expression of uncertainty in measurement (GUM) was used as a more efficient approach for carrying out interval estimation of the corrosion level. Furthermore, a designed Bayesian dynamic linear model (BDLM) with a model monitoring mechanism was introduced to modify the measurement sequence. Thus, not only were more credible estimations achieved but discrepant sequences of measurement data could also be identified to avoid a misled judgement.