Zhang Gong, Zhang Yuhang, Tuo Shuaihua, Hou Zhicheng, Yang Wenlin, Xu Zheng, Wu Yueyu, Yuan Hai, Shin Kyoosik
Guangzhou Institute of Advanced Technology, Chinese Academy of Sciences, Guangzhou 511458, China.
School of Engineering Science, University of Chinese Academy of Sciences, Beijing 100049, China.
Sensors (Basel). 2021 Apr 28;21(9):3067. doi: 10.3390/s21093067.
The seam tracking operation is essential for extracting welding seam characteristics which can instruct the motion of a welding robot along the welding seam path. The chief tasks for seam tracking would be divided into three partitions. First, starting and ending points detection, then, weld edge detection, followed by joint width measurement, and, lastly, welding path position determination with respect to welding robot co-ordinate frame. A novel seam tracking technique with a four-step method is introduced. A laser sensor is used to scan grooves to obtain profile data, and the data are processed by a filtering algorithm to smooth the noise. The second derivative algorithm is proposed to initially position the feature points, and then linear fitting is performed to achieve precise positioning. The groove data are transformed into the robot's welding path through sensor pose calibration, which could realize real-time seam tracking. Experimental demonstration was carried out to verify the tracking effect of both straight and curved welding seams. Results show that the average deviations in the direction are about 0.628 mm and 0.736 mm during the initial positioning of feature points. After precise positioning, the average deviations are reduced to 0.387 mm and 0.429 mm. These promising results show that the tracking errors are decreased by up to 38.38% and 41.71%, respectively. Moreover, the average deviations in both and direction of both straight and curved welding seams are no more than 0.5 mm, after precise positioning. Therefore, the proposed seam tracking method with four steps is feasible and effective, and provides a reference for future seam tracking research.
焊缝跟踪操作对于提取焊缝特征至关重要,这些特征可指导焊接机器人沿焊缝路径运动。焊缝跟踪的主要任务可分为三个部分。首先是起点和终点检测,其次是焊缝边缘检测,接着是接头宽度测量,最后是相对于焊接机器人坐标系确定焊接路径位置。本文介绍了一种新颖的四步法焊缝跟踪技术。使用激光传感器扫描坡口以获取轮廓数据,并通过滤波算法对数据进行处理以平滑噪声。提出二阶导数算法对特征点进行初始定位,然后进行线性拟合以实现精确定位。通过传感器位姿校准将坡口数据转换为机器人的焊接路径,从而实现实时焊缝跟踪。进行了实验演示以验证直线焊缝和曲线焊缝的跟踪效果。结果表明,在特征点初始定位期间,x方向的平均偏差约为0.628毫米和0.736毫米。精确定位后,平均偏差降至0.387毫米和0.429毫米。这些令人满意的结果表明,跟踪误差分别降低了38.38%和41.71%。此外,精确定位后,直线焊缝和曲线焊缝在x和y方向的平均偏差均不超过0.5毫米。因此,所提出的四步法焊缝跟踪方法是可行且有效的,为未来的焊缝跟踪研究提供了参考。