Data Fusion for Multiple-Sensor Nondestructive Evaluation on Concrete Bridge Deck

Corrosion of buried reinforcing steel in concrete bridge decks is one of the dominant damage types in terms of overall bridge maintenance costs. Early-stage detection, location and assessment of corrosion can significantly reduce the damage progression and maintenance costs. This study aims to assess and improve the ability of various nondestructive evaluation (NDE) methods to detect the early stages of corrosion. This paper presents the techniques to apply data fusion on two NDE methods – ground penetrating radar and half-cell potential. Fusing data from multiple NDE methods may result in better and more accurate evaluation of active corrosion.