运用形态学运算的焊接前离线路径规划  

Offline path planning before welding using morphological operations

作　　者：曹学鹏[1] 樊豪 冯艳丽 王德硕 CAO Xuepeng;FAN Hao;FENG Yanli;WANG Deshuo(Institute of Mechatronics,School of Engineering Machinery,Chang’an Univisity,Xi’an 710064,CHN;Xi’an Aerospace Times Precision Electromechanical Co.,Ltd.,Xi’an 710100,CHN)

机构地区：[1]长安大学工程机械学院机电液一体化研究所,陕西西安710064 [2]西安航天时代精密机电有限公司,陕西西安710100

出　　处：《制造技术与机床》2023年第9期115-121,共7页Manufacturing Technology & Machine Tool

基　　金：陕西省重点研发计划项目(2021ZDLGY09-02)。

摘　　要：焊接特征点的自动提取是机器人自主规划焊接路径的关键。传统的焊接通常需要示教焊接中间点,当工件更改或装配出现误差时,通常需要重新进行示教,导致焊接效率较低。文章提出了一种基于单目相机的焊接特征点自动化提取的方法,首先采用双边滤波平滑图像;随后运用Sobel算子计算像素的梯度,以图像的平均灰度值为阈值进行二值化;接着通过闭运算填充细小孔洞并连接间断的细小轮廓线;使用改进的轮廓跟踪算子消除图像上的残留噪声;采用平均法从图像上提取特征点;然后通过相机标定将特征点从像素坐标系转换到用户坐标系。采取不同形状的平面薄板对接焊缝工件进行特征点提取实验,通过对比特征点与激光传感器采集得到的焊缝坡口中心点在用户坐标系y轴方向上的差值,获得混合型焊缝、直线型焊缝、曲线型焊缝的平均误差分别为0.45mm、0.23mm、0.42mm,表明该方法能够从图像中自动识别焊缝并提取焊接特征点,免除焊接系统的示教环节。Automatic extraction of weld feature points is the key to autonomous weld paths planning for robot.Conventional welding usually requires teaching welding intermediate points,which usually needs to be re-teached when the workpiece is changed or there is an error in the assembly,resulting in low welding efficiency.In this paper,we propose a method for automatic extraction of welding feature points based on a monocular camera,bilateral filtering is used to smooth the image;then Sobel operator is applied to calculate the gradient of the pixels and the average gray value of the image is used as the threshold to binary pixels;then a closed operation is used to fill the fine holes and connects the intermittent fine contour lines;then an improved contour tracking operator is used to eliminate residual noise on the image;then the feature points are taken from image and converted from the pixel coordinate system to the user coordinate system by camera calibration.Different shapes of flat sheet butt weld workpieces are chosen for feature point extraction experiments,by comparing the difference between the feature points and the weld bevel center points obtained by laser sensor in the y-axis direction of the user coordinate system,the average errors are 0.45 mm,0.23 mm,0.42 mm for hybrid,linear and curve welds respectively,which indicating that the method can automatically identify weld from the image and extract the weld feature points,furthermore,eliminate teaching of the welding system.

关 键 词：焊缝识别 轮廓跟踪 相机标定 数字图像处理 

分 类 号：TP212.9[自动化与计算机技术—检测技术与自动化装置]