Vision Sensing-Based Online Correction System for Robotic Weld Grinding  

作　　者：Jimin Ge Zhaohui Deng Shuixian Wang Zhongyang Li Wei Liu Jiaxu Nie 

机构地区：[1]Hunan Provincial Key Laboratory of High Efciency and Precision Machining of Difcult Machine Material,Hunan University of Science and Technology,Xiangtan 411201,China [2]Institute of Manufacturing Engineering,Huaqiao University,Xiamen 361021,China [3]ZOOMLION Heavy Industry Science and Technology Co.,Ltd.,Changsha 410000,China

出　　处：《Chinese Journal of Mechanical Engineering》2023年第5期97-108,共12页中国机械工程学报（英文版）

基　　金：Supported by Hunan Provincial Natural Science Foundation of China(Grant No.2021JJ50116).

摘　　要：The service cycle and dynamic performance of structural parts are afected by the weld grinding accuracy and surface consistency. Because of reasons such as assembly errors and thermal deformation, the actual track of the robot does not coincide with the theoretical track when the weld is ground ofine, resulting in poor workpiece surface quality. Considering these problems, in this study, a vision sensing-based online correction system for robotic weld grinding was developed. The system mainly included three subsystems: weld feature extraction, grinding, and robot real-time control. The grinding equipment was frst set as a substation for the robot using the WorkVisual software. The input/output (I/O) ports for communication between the robot and the grinding equipment were confgured via the I/O mapping function to enable the robot to control the grinding equipment (start, stop, and speed control). Subsequently, the Ethernet KRL software package was used to write the data interaction structure to realize realtime communication between the robot and the laser vision system. To correct the measurement error caused by the bending deformation of the workpiece, we established a surface profle model of the base material in the weld area using a polynomial ftting algorithm to compensate for the measurement data. The corrected extracted weld width and height errors were reduced by 2.01% and 9.3%, respectively. Online weld seam extraction and correction experiments verifed the efectiveness of the system’s correction function, and the system could control the grinding trajectory error within 0.2 mm. The reliability of the system was verifed through actual weld grinding experiments. The roughness, Ra, could reach 0.504 µm and the average residual height was within 0.21 mm. In this study, we developed a vision sensing-based online correction system for robotic weld grinding with a good correction efect and high robustness.

关 键 词：Online correction system ROBOT GRINDING Weld seam Laser vision sensor 

分 类 号：TG444.72[金属学及工艺—焊接]