A case-based reasoning approach for fault detection state in bridges assessment

Case-Based Reasoning (CBR) systems use previous knowledge stored in data bases to solve current issues. Nowadays, CBR approach is widely used in different areas with good results. Such an area is system diagnose and fault detection. In this paper, we suggest a new approach, based on CBR, for fault detection of reinforced concrete bridges on polluted area. Nowadays the bridge inspection and diagnose is usually performed by civil engineers mainly on visual inspections, action involving subjective judgments and uncertainties. So far, intelligent diagnose on bridges was made based on models approaches, like fuzzy models and neural networks models. This paper aims to present a new approach based on CBR paradigm, to solve the above mentioned issues. We suggest and implement the architecture for data gathering and data base storing. Also, the CBR paradigm is tested by using jCOLIBRI platform.