NDE data fusion to improve the evaluation of concrete structures

A new data fusion application is presented, in the context of a national research project. This project aims to improve the evaluation of indicators or pathologies of in situ concrete structures, combining measurements provided by various non-destructive evaluation techniques. The indicators of interest are: porosity rate, water saturation, modulus of elasticity, compressive strength, chloride content and carbonatization depth. Any non-destructive measurement will tend to provide an estimation of the unknown indicators, with a certain degree of confidence that is a function of its reliability and sensitivity to each of the indicators. When the estimations converge, data fusion improves the final confidence in the estimated values of these indicators. In case of disagreement, conflicts can be managed by specific operators. An adapted solution has been developed, based on the possibility theory and fuzzy sets. Application results are presented for two simultaneous evaluations of two pairs of indicators: water saturation and porosity rate, and water saturation and modulus of elasticity. These results show that the chosen adaptive operator, which is a function of reliability, is appropriate for this type of problem.