基于点云的机器人焊缝自动化磨削系统与方法
Automated Grinding System and Method for Robotic Weld Seams Based on Point Cloud
葛吉民 1邓朝晖 2王水仙 1卓荣锦 1刘伟 1陈曦3
作者信息
- 1. 湖南科技大学机电工程学院,湘潭,411100
- 2. 华侨大学制造工程学院,厦门,361021
- 3. 上汽大众长沙分公司,长沙,410000
- 折叠
摘要
结构件的服役周期和动态性能受焊缝磨削精度和表面一致性的影响,目前,焊缝磨削主要依靠人工或轨迹示教的方式,存在均一性差、效率低、成本高等问题.鉴于此,开发了基于点云的机器人焊缝自动化磨削系统,采用焊缝点云二次精简方法准确获取焊缝表面的全局信息,基于采样点与邻域重心点之间的距离准确提取焊缝宽度、高度及中心线特征.系统提取后的焊缝高度、宽度误差约为0.09 mm和0.2 mm,磨削后焊缝最小残留高度约为0.17 mm,表面粗糙度Ra值可达0.498μm.
Abstract
Service life and dynamic performance of structural components were affected by the ac-curacy and surface consistency of weld grinding.Currently,weld grinding mainly relied on manual or trajectory teaching methods,which had problems such as poor uniformity,low efficiency and high cost.So,a point cloud-based automated grinding system for robotic weld seams was proposed.A quadratic streamlining method for weld seam point cloud was proposed to obtain the global informa-tion of the weld seam surfaces accurately,and the weld seam width,height,and centerline features were extracted based on the distances between sampling points and neighborhood center of gravity points.The errors of height and width of the extracted weld seams are as 0.09 mm and 0.2 mm respec-tively,and the minimum residual height of the weld seams after grinding is as 0.17 mm,and the vlaue of surface roughness Ra is up to 0.498 μm.
关键词
焊缝/机器人磨削/点云/特征提取Key words
weld seam/robotic grinding/point cloud/feature extraction引用本文复制引用
基金项目
国家自然科学基金(U23A20634)
湖南省市联合基金(2021JJ50116)
出版年
2024
国家科技期刊平台
NSTL
万方数据