摘要
目前,焊接结构件焊缝成形质量的无损检测仍普遍采用低效率、低精度的目视方法.为改善这一现状,一种基于结构光视觉的焊缝成形质量在线检测技术被提出,建立的3D坐标识别模型,赋予了该技术对空间3D信息的感知能力,融合YOLOv5与空间距离判断法的图像处理算法,从结构光图像中自主判定焊缝的类型,并自动测量焊缝的几何尺寸,如焊缝宽度、余高与焊脚尺寸等,该算法不再局限于焊缝轮廓的监测,还可准确地识别、分类与定位各种焊缝几何缺陷,如焊缝超高、错边、未焊满下垂、咬边、焊瘤、凸度过大与焊脚不对称等,并根据ISO 5817:1992标准在线自主评定缺陷的质量等级.结果表明,该技术对焊缝几何尺寸的测量精度可达10^(-2)mm量级,对焊缝几何缺陷的质量等级评定准确率达100%,完全满足自动化焊接生产线在线评定焊缝成形质量的技术要求.
Currently,the non-destructive testing for weld formation quality of welded structural components still predominantly employs visual evaluation with low efficiency and low accuracy.To improve the situation,an online inspection technology for weld formation quality based on structured light vision was proposed.The established 3D coordinate recognition model endowed this technology with the capability to perceive spatial 3D information;the image processing algorithm integrating YOLOv5 and the spatial distance judgment method autonomously identified weld types from structured light images and automatically measured geometrical dimensions such as weld width,weld reinforcement,and weld leg sizes.Particularly,this algorithm was not limited to monitoring weld profiles,but it could also accurately identify,classify,and locate various geometrical defects including excess weld metal,align deviation,incompletely filled sags,undercut,overlap,excessive convexity,and asymmetric weld leg.Moreover,it could autonomously evaluate defect quality grades online according to the ISO 5817:1992 standard.Experimental results demonstrate that this technology achieves measurement accuracy at the 10^(−2) mm level for geometrical dimensions of welds,attains 100%grading accuracy for geometrical defect quality,and fulfills the requirements for online inspection of weld formation quality in automated welding production lines.
作者
王浩
池玉朋
方荣超
陈超
赵小辉
WANG Hao;CHI Yupeng;FANG Rongchao;CHEN Chao;ZHAO Xiaohui(School of Materials Science and Engineering,Jilin University,Changchun,130025,China;Xuzhou XCMG Excavator Machinery Co.,Ltd.,Xuzhou,221132,China)
出处
《焊接学报》
北大核心
2025年第6期52-60,共9页
Transactions of The China Welding Institution
基金
国家自然科学基金项目(52275338)
吉林省科技厅重点科技研究与发展项目(20210201056GX)
吉林省金属材料先进焊接技术创新团队(20230508039RC)。
关键词
焊接结构件
焊缝成形
质量检测
结构光视觉
welded structural component
weld formation
quality inspection
structured-light vision
