首页|面向点胶加工的壳体类工件三维重建

面向点胶加工的壳体类工件三维重建

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为了解决目前点胶加工中轨迹提取精度不高且过程繁琐的问题,提出一种基于线激光扫描的壳体类工件三维重建方法,可用于后续的点胶轨迹提取.首先,搭建了线激光扫描平台,获取了手机壳工件各视场的点云数据;其次,利用点云滤波方法对初始点云进行无效点移除、下采样和降噪的预处理;随后,采用五轴机床标定算法对点云进行粗配准,并采用迭代最近点(ICP)算法进行点云精配准,删除重复点后得到完整的手机壳工件三维模型;最后,通过实验验证了手机壳工件的重建精度,结果表明手机壳重建模型宽度的最大偏差在0.15 mm以内,平均偏差仅为0.079 mm,且和粗配准相比,精配准的精度提高了79.48%,故所提出的壳体类工件重建方法满足点胶加工精度要求.
Three-Dimensional Reconstruction of Shell Workpiece Oriented to Dispensing Processing
In order to solve the problem of low precision and complicated process in the current dispensing process,a three-dimensional reconstruction method of shell-like workpiece based on line laser scanning is proposed,which can be used for subsequent dispensing trajectory extraction.Firstly,a line laser scanning platform is built to obtain the point cloud data of each field of view of the mobile phone case workpiece.Secondly,the point cloud filtering method is used to remove invalid points,downsample and denoise the ini-tial point cloud.Then,the five-axis machine tool calibration algorithm is used for coarse registration of the point cloud,and the iterative closest point(ICP)algorithm is used for fine registration of the point cloud,and the complete three-dimensional model of the mobile phone case workpiece is obtained after deleting the duplicate points.Finally,the reconstruction accuracy of the mobile phone shell workpiece is verified by ex-periments.The results show that the maximum deviation of the width of the mobile phone shell reconstruc-tion model is within 0.15 mm,and the average deviation is only 0.079 mm.Compared with the rough reg-istration,the precision of fine registration is improved by 79.48%,so the reconstruction method of the mo-bile phone shell workpiece can meet the requirements of dispensing accuracy.

five-axis dispensing machinetrajectory extractionline laserpoint cloud registrationthree-di-mensional reconstruction

张敬宇、瞿佳伟、张春雷、田钊、洪国

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四川大学机械工程学院,成都 610065

成都乐创自动化技术有限公司,成都 610041

五轴点胶机 轨迹提取 线激光 点云配准 三维重建

2024

组合机床与自动化加工技术
大连组合机床研究所 中国机械工程学会生产工程分会

组合机床与自动化加工技术

CSTPCD北大核心
影响因子:0.671
ISSN:1001-2265
年,卷(期):2024.(10)