基于熔池图像不变矩特征的激光-MIG复合焊接根部驼峰在线检测方法  

Online Detection of Root Hump in Laser⁃MIG Hybrid Welding Based on Invariable Moment Characteristics of Molten Pool Image

作　　者：黄宇辉 范西岸 张艳喜[1] 高向东[1] Huang Yuhui;Fan Xi’an;Zhang Yanxi;Gao Xiangdong(Guangdong Provincial Welding Engineering Technology Research Center,Guangdong University of Technology,Guangzhou 510006,Guangdong,China)

机构地区：[1]广东工业大学广东省焊接工程技术研究中心,广东广州510006

出　　处：《中国激光》2023年第12期72-80,共9页Chinese Journal of Lasers

基　　金：广州市科技计划(202002020068);国家自然科学基金(52275317);广东省自然科学基金项目(2314050004977)。

摘　　要：根部驼峰缺陷是激光-MIG复合焊接(MIG焊,熔化极惰性气体保护焊)中常出现的焊接缺陷之一,因该缺陷出现在焊件背部,所以在焊接过程中不易被发现。为检测根部驼峰缺陷,采用高速摄像机捕捉焊接图像。对预处理后的图像进行阈值分割得到熔池轮廓图像,通过局部形态学处理进一步获取熔池二值化图像。提取二值化图像的四组归一化不变矩,并采用滑动均值法进行降噪处理,进而获得不变矩特征。建立动态调整学习率算法的一维卷积神经网络模型,以熔池尾部图像的四组归一化不变矩及其滑动均值作为输入。通过9150个连续焊缝样本检测值和实际值的比较,验证了该网络模型具有良好的检测能力。该方法可应用于封闭式的平板对接焊,通过采集激光-MIG复合焊接中焊件表面信号,对无法直接观察的背部驼峰缺陷进行检测。Objective As a reliable technology for material joint processing,laser-MIG hybrid welding(MIG welding,melt inert-gas welding)has been applied to various fields of the product manufacturing industry for decades.Due to its characteristics such as deep penetration,high welding speed,and high-quality shaping,laser-MIG hybrid welding has become the research focus.However,all kinds of defects troubling many scholars often occur in laser-MIG hybrid welding,and root hump is one of the common defects.Unlike instantaneous defects such as undercut and non-penetration,root hump defects are caused by the accumulation of molten metal flowing to the end of the pool over a a period of time.During the formation of the root hump,the weld quality is continuously affected by it.When the molten metal has solidified to form a hump,the new molten metal will continue to accumulate in the next position to form a new hump,resulting in the periodic occurrence of the root hump within a certain range.This study presents an online detection of root hump based on invariable moment characteristics of the tail molten pool,which can detect accurately root hump defect in the strong noise environment of laser-MIG hybrid welding.We hope that our innovative approach could provide the basis for the online detection of defects in laser-MIG hybrid welding.Methods The laser-MIG hybrid welding process detection system is established by a high-speed camera,six-axis robot,arc welding machine,high-power fiber laser,and image processing computer.During laser-MIG hybrid welding,the images of the molten pool outlines are collected by the high-speed camera.To reduce the gray difference between the two sides of the molten pool when the arc is retracted or released,the multi-scale Retinex(MSR)enhancement method based on Retinex theory is used.After threshold segmentation and morphological processing,the binary images of the tail molten pool are obtained.Whereafter,the four kinds of invariant moments of the tail molten pool images are calculated.For suppressing the

关 键 词：激光技术 神经网络 激光-MIG复合焊 根部驼峰 熔池图像 图像不变矩 

分 类 号：TG409[金属学及工艺—焊接]