Ontological Approach for Automatic Inference of Concrete Crack Cause

The cause of cracks in concrete is traditionally estimated by analyzing information such as patterns and locations of the cracks and whether other defects are present, followed by aggregating the findings to estimate the cause. This method is highly dependent on the expert's knowledge and experience in the process of identifying the cause of the cracks by compiling information related to the occurrence of the cracks, and it is likely that each expert will make a different diagnosis or an expert with insufficient knowledge and experience will make an inaccurate diagnosis. Therefore, we propose automated technology using the ontology to improve the consistency and accuracy of crack diagnosis results in this research. The proposed approach uses information on the crack patterns, locations, and penetration status, as well as the occurrence of other defects, to automatically infer the causes of cracks. We developed ontology that can infer the cause of cracks using the information on their appearance and applied actual cases of cracks to verify the ontological operation. In addition, the consistency and accuracy of the ontology were validated using eight actual cases of crack. The approach of this study can support expert decision-making in the crack diagnosis process, thereby reducing the possibility of various errors caused by the intervention of inaccurate judgments in the crack diagnosis process and improving the efficiency of the crack diagnosis tasks.