摘要
针对船舱格子间工作空间狭小,大型自动化设备难以完成舱内自动焊接的问题,提出了一种基于双目视觉获取焊缝路径三维信息的策略。基于张正友标定原理获取双目系统基本参数后,利用C++与OpenCV编写了自适应阈值的二值化处理、改进的Sobel轮廓提取算子、非连续像素点筛除等程序,对双目相机采集的图像进行处理,提取了清晰、低噪点的直角角焊缝中心轮廓图像。基于BM特征点匹配算法与像素点扫描方法,得到了焊缝轮廓上连续特征点的三维信息数据集,利用Origin作图软件拟合后生成了三维直角角焊缝路径。为了验证双目系统测距精度与鲁棒性,设计了可升降、角度可调的滑轨万向节组合模块,实现了从不同拍摄角度、高度采集焊缝图像,并对焊缝上设置的等距特征点的距离进行识别。试验结果表明,当拍摄偏角在30°之内,或正拍高度在150~190 mm内变化时,测距偏差都可以控制在2 mm内,基本满足焊接的精度与稳定性要求,并为焊接的自动化循迹过程提供了数据基础。
In view of small working space between cabins and difficulty of large-scale automation equipment to complete automatic welding in the cabin,a strategy based on binocular vision to obtain three-dimensional information of weld path was proposed.After obtaining basic parameters of binocular system based on Zhang Zhengyou’s calibration principle,C++and OpenCV were used to write programs such as binarization of adaptive threshold,improved Sobel contour extraction operator and non-continuous pixel screening,and extract a clear,low-noise image of center contour of the right angle weld.Based on BM feature point matching algorithm and pixel scanning method,a three-dimensional information data set of continuous feature points on weld outline was obtained,and a three-dimensional right-angle weld path was generated after fitting with Origin drawing software.In order to test accuracy of binocular system ranging,a universal joint combination module of sliding rails with adjustable angles was designed to collect weld images from different shooting angles and heights,and to identify distance of equidistant feature points set on weld.The experimental results showed that when shooting deflection angle was within 30°or shooting height was within 150~190 mm,ranging deviation could be controlled within 2 mm,which basically satisfied the precision and stability requirements of welding,and provided a data basis for automatic tracking process of welding.
作者
张勇
高延峰
张华
Zhang Yong;Gao Yanfeng;Zhang Hua(Shanghai Collaborative Innovation Center of Intelligent Manufacturing Robot Technology for Large Components,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《焊接》
北大核心
2022年第7期21-27,共7页
Welding & Joining
关键词
双目视觉
三维直角角焊缝路径
特征点匹配
图像处理
鲁棒性
binocular vision
3D right-angle weld path
feature point matching
image processing
robustness