基于加工余量优化的航空模锻件点云配准算法  

Point Cloud Registration Algorithm for Aviation Die Forgings Based on Optimization of Machining Allowance

作　　者：王杰 杨青平 曹珍珍 刘钢 WANG Jie;YANG Qingping;CAO Zhenzhen;LIU Gang(School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620;Chengdu Yongfeng Technology Co.,Ltd.,Chengdu 610511)

机构地区：[1]上海工程技术大学机械与汽车工程学院,上海201620 [2]成都永峰科技有限公司,成都610511

出　　处：《计算机与数字工程》2023年第12期3004-3009,共6页Computer & Digital Engineering

基　　金：国家自然科学基金项目(编号:51775328)资助。

摘　　要：为解决航空大型结构件在精密数控加工过程中毛坯加工余量分布不均的问题,提出了基于加工余量优化的模锻件点云配准算法。首先将降噪等预处理之后的毛坯点云数据和CAD设计数模通过四特征点法进行粗配准,然后基于加工面容差约束建立精配准数学模型,采用广义乘子法和奇异值分解法求解模型,同时采用迭代法让毛坯所有匹配点都满足加工面容差约束以及通过数据关联加快配准过程中对应点的搜索速度。点云配准试验结果表明:四特征点粗配准方法与“321”粗配准方法比,标准差和均方根偏差分别减小了5.35%、3.91%;基于加工余量约束优化的精配准方法与经典ICP方法比,标准差和均方根偏差分别减小0.09%、0.15%。因此,提出的点云配准方法在模锻件加工余量优化过程中比传统方法精度更高。In order to solve the problem of uneven distribution of blank machining allowance during precision CNC machining of large aviation structural parts,a point cloud registration algorithm for die forgings based on machining allowance optimization is proposed.First,the rough point cloud data and CAD design digital model after noise reduction and other preprocessing are coarsely registered through the four-feature point method,and then the fine registration mathematical model is established based on the toler-ance constraints of the machining surface,and the generalized multiplier method and singular value decomposition are adopted.At the same time,the iterative method is used to make all matching points of the blank meet the tolerance constraints of the machining surface,and the search speed of the corresponding points in the registration process is accelerated through data association.The point cloud registration test results show that:Compared with the"321"rough registration method,the standard deviation and root mean square deviation of the four-feature point coarse registration method are reduced by 5.35%and 3.91%respectively.Based on processing compared with the classic ICP method,the precision registration method of margin-constrained optimization reduces the standard deviation and the root mean square deviation by 0.09%and 0.15%,respectively.Therefore,the proposed point cloud regis-tration method has higher accuracy than the traditional method in the process of die forging machining allowance optimization.

关 键 词：精密数控加工 模锻件 四特征点 粗配准 精配准 加工余量优化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]