Inspection and evaluation of a network of concrete bridges based on multiple NDT techniques

Bridge condition rating is a crucial variable used for prioritisation of bridge needs in bridge management systems (BMSs). At present, bridge rating is predominantly based on visual inspections. A practical method incorporating non-destructive testing (NDT) results for rating bridges in a BMS is not available. In this study, an integrated rating method for reinforced concrete bridges based on both visual inspection and multiple NDT techniques with the ultimate goal of incorporating it into BMSs was developed. The method uses a multi-component and multi-modal NDT application at network-level with improved testing speed. The application results of four non-destructive techniques including visual inspection, polarisation resistance, penetration resistance, and pulse velocity on a reinforced concrete bridge network of 100 bridges are presented. At bridge level, a multi-component approach was used, including decks, girders, cap beams, piers, and abutments. A novel method for NDT-based reinforcement corrosion rating was developed. Correlation among NDT variables was also investigated and the results are presented. Multiple linear regression models were developed using ANOVA analyses. Only the statistically significant regressors with the largest partial F-statistic were included in the model formulas. The expected weights of the four evaluation criteria in the formula were obtained by combining the results of two techniques: statistical data available in literature on the frequency of use of NDT techniques for bridge inspection, and a three-level analytical hierarchy process (AHP) based on expert survey. Application of three NDT techniques to inspections of concrete bridges, determination of NDT ratings using the integrated rating formula, and incorporation of the resulting ratings into a BMS for bridge ranking can be performed using the proposed methodology.

Automated summary

The study proposes an integrated rating method that combines visual inspection and multiple NDT techniques at network-level and multi-component approach at bridge level. By using multiple linear regression models and statistical analysis, the weights of evaluation criteria were determined, and the NDT ratings were incorporated into a bridge management system for ranking.