Keywords: damage assessment, RC slab, pattern recognition, TAM network Introduction
In order to establish a rational management program for bridge structures, it is necessary to collect enough data about the material and structural characteristics and to evaluate the structural damage of existing bridges in a quantitative manner. However, it is often seen to lose the drawings or design specifications. Moreover, it is difficult to avoid the subjectivity of inspectors when visual data are used for the evaluation of damage or deterioration. In this paper, an attempt is made to develop a new system that can evaluate the damage condition of existing structures by using the visual information given by digital photos (Furuta et al., 2004a). The proposed system is based upon such new technologies as image processing, photogrammetry, pattern recognition, and artificial intelligence (Furuta et al., 2004b). The damage of Reinforced Concrete (RC) bridge decks is evaluated with the aid of digital photos and pattern recognition. Using the proposed system, it is possible to automatically evaluate the damage degree of RC bridge decks and therefore avoid the subjectivity of inspectors. Several numerical examples are presented to demonstrate the applicability of the proposed system.