摘要
为实现大型结构件焊后焊缝自动磨抛,磨抛机器人除了具备移动能力和磨抛能力外,更需要在复杂和不规则的工业环境中对焊缝进行准确的跟踪和测量,进而为焊缝磨抛提供有效的加工参数。将两个电荷耦合器件(Charge-coupled device,CCD)相机和激光器搭载在吸附移动机器人本体上,构成焊缝磨抛机器人视觉系统。根据结构光的亮度分布特征,提出定位图像感兴趣区域(Region of interest,ROI)的算法,减小了计算量,提高了计算效率;提出在噪声干扰条件下快速检测结构光特征线的列高斯差分算法,成功提取结构光特征线;提出差分最值粗定位-距离阈值精定位的焊缝边缘点检测算法,快速、精确提取焊后焊缝的边缘点,计算出焊后焊缝的几何信息。图像处理试验及相应的焊缝磨抛试验结果表明:该视觉系统稳定、可靠,视觉算法快速、精确并且具有很好的鲁棒性,为复杂工业环境下大型结构件焊缝磨抛自动化奠定了基础。
To automatically grind and polish weld bead on large-scale structure parts, grinding/polishing robot should not only be capable of moving and polishing, but also accurately tracking and measuring the weld bead in complex industrial environment. The collected data is useful for weld-bead grinding and polishing. The vision system for the grinding and polishing robot in this paper consists of a double charge-coupled device（CCD） camera and a laser, both fixing on the robot. According to the brightness distribution of structured light, a region of interest（ROI） positioning algorithm for image pair is proposed. By using the new algorithm, the calculating efficiency is largely improved. Gaussian differential method related to the image columns is proposed, and the typical lines of structured light can be extracted from noise-polluted images. Rough location of the weld bead edge is realized by finding maximum and minimum difference values, while the exact bead edge is accurately and rapidly extracted based on definition of distance threshold. Thus, the geometric information of the weld bead can be obtained. The results of image processing experiments and grinding/polishing experiments show that the visual system is reliable and stable, and vision algorithm is rapid and accurate. The system would lay foundation for automatically grinding and polishing large-scale structure parts in a complex industrial environment.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2013年第20期42-48,共7页
Journal of Mechanical Engineering
基金
国家自然科学基金资助项目(50975123)
关键词
磨抛
视觉算法
焊后焊缝
结构光
Grinding/polishing Vision algorithm Weld bead StrucRtred light
