Efficient Maintenance of Damaged RC Structures by Integrating 3D Data and Crack Information for Digital Twin

In the agricultural field, concrete headworks is the most important structure for the irrigation system. In recent years, several agricultural concrete infrastructures aging for a long-term period has been increasing. For maintenance and management, conventional inspection methods are time-consuming and costly, such as the electromagnetic wave method and elastic wave method. The detection of surface damage is more effective, safe and reliable than before since the laser scanning method provides detailed geometric information about the structure. The fundamental studies on point cloud data have been conducted in the civil engineering fields, nevertheless, the characteristics of point cloud in agricultural infrastructures, such as dam, headworks and canal, have not been discussed. In this study, 3D point clouds are generated for a concrete irrigation structure using the laser scanning method. We focused on the characteristics of surface damage, which are quantitatively evaluated using point cloud information, geometric information and intensity parameter. The types of detected damage are efflorescence and cracks. Which aligned point clouds or point clouds from a single scan is effective for high-precision detection is confirmed. The characteristics of surface damage are evaluated by geometric features. The distance between the fitted plane and points is calculated by RANSAC algorithm and roughness parameter. The amount of efflorescence is detected by the distance between the fitted plane from RANSAC algorithm and points. The crack is detected by the local plane fitting method. The types of damage are characterized by the intensity parameter which is related to the color, roughness and moisture of the object. The surface damage and condition are evaluated by both geometric information and intensity parameter. These results show the unique parameters of point clouds from laser scanning methods, such as geometric features and intensity parameter, are useful to evaluate the characteristics of surface damage.