摘要
针对GMAW电弧光谱特征,设计了单目被动视觉熔池图像采集系统,利用工业像机加装复合滤光系统和相机外触发系统拍摄熔池图像。提出利用图像平均灰度值判断弧光对熔池图像的干扰程度,以及限定小波变换模极大值边缘检测算法中阀值的设置,提取出熔池轮廓及其特征参数。熔池轮廓特征能反映焊接对缝中心、焊接偏差(焊接对缝中心与焊丝投影中心的偏差)、板材错边、焊塌、焊穿等焊接信息。结果表明,熔池轮廓提取算法合理,熔池轮廓特能反映焊接缺陷,可以为基于视觉的焊接缺陷在线监测提供技术支持。
Based on the spectral characteristics of GMAW arc,a monocular passive vision image acquisition system for molten pool was designed to capture the images of molten pool by adding a compound filter system and an external trigger system to the industrial camera.The average gray value of the image is used to judge the interference degree of arc light to the weld pool image,and the threshold value of wavelet transform modulus maximum edge detection algorithm is defined by the average gray value to extract the weld pool contour and its characteristic parameters.The molten pool contour features can reflect I-groove center and welding defects such as welding deviation(the deviation between groove center and wire projection center),misalignment,excessive penetration and burn-through.The results show that the algorithm of molten contour extraction is reasonable,and the characteristic of molten pool defect is obvious,which provides technical support for the online monitoring of weld defects based on vision.
作者
朱彦军
吴志生
王安红
厉雷钧
ZHU Yanjun;WU Zhisheng;WANG Anhong;LI Leijun(College of Materials Science and Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China;Canadian Centre for Welding and Joining,University of Alberta,Canada)
出处
《电焊机》
2018年第11期13-18,共6页
Electric Welding Machine
基金
山西省应用基础研究项目(201601D011036)
山西省研究生联合培养基地人才培养项目(2017JD30)
关键词
熔化极气体保护焊
熔池图像
特征参数
缺陷检测
gas metal arc welding
molten pool image
characteristic parameters
defect detection