Studying an improved recursive rough method for three-dimensional visual examination of steel plate butt welding surface quality

Abstract

An improved recursive rough algorithm is proposed to extract feature points in order to address the slow speed and poor accuracy of feature point extraction in 3D visual inspection, as well as the difficulty in meeting the requirements of efficient and quantitative analysis of welded surface quality detection. The preprocessed point cloud is sliced by section. The feature points are obtained according to the improved recursive rough algorithm. The defect evaluation is carried out to obtain the inspection conclusion of the weld appearance defect. Finally, according to the formulated weld defect evaluation process and standards, the typical weld template is selected for weld width, weld misedge and weld straightness test. Weld detection accuracy can reach 3 decimal places, the speed is 4 times the current manual detection speed. The detection results show that the system has the characteristics of high accuracy and fast speed which can replace manual detection. It also has a good application prospect.