Abstract

The shear reinforcement of dual-anchorage (SRD) is used to enhance the safety of reinforced concrete structures in construction sites. In SRD, welding is used to create shear reinforcement, and after production, a quality inspection of the welding bead is required. Since the welding bead of SRD is inspected for quality by measuring both horizontal and vertical lengths, it is necessary to obtain this information for quality inspection. However, it is difficult to inspect the quality of welding beads using existing methods based on segmentation, due to the similarity in texture between the welding bead and the base material, as well as discoloration around the welded area after welding. In this paper, we propose an algorithm that detects the welding bead using an image projection algorithm for pixels and classifies the quality of the welding bead. This algorithm detects the position of welding beads using the brightness values of an image. The proposed algorithm reduces the amount of computation time by first specifying the region of interest and then performing the analysis. Results from experiments reveal that the algorithm accurately classifies welding beads into good or bad classes by obtaining all brightness values in the vertical and horizontal directions in the SRD image. Furthermore, comparison tests with conventional algorithms demonstrate that the classification accuracy of the proposed algorithm is the highest. The proposed algorithm will be helpful in the real-time welding bead inspection field where fast and accurate inspection is crucial.

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