摘要
针对实际生产中的大批量零件质量检测问题,建立基于扫描点云数据的质量检测系统。采用三维激光扫描设备获取待测零件的表面数据,提出基于随机抽样一致性的点云数据预处理方法,通过区域增长以及迭代最近点的配准方法完成目标点云的分割提取方法,实现实体产品同设计模型理论数值的对比分析。以某冲压件为例进行算法验证,实验结果验证点云处理用于大批量零件检测的可行性和准确性,为大批量零件快速检测提供一种新的高效、准确的方法。
To determine the quality of large quantities of parts in actual production,a quality determination method based on scanning point cloud data is proposed.With the help of point cloud processing software and algorithm,the three-dimension laser scanning equipment is used to establish the segmentation and extraction method of multi-target point cloud,and the physical product is campared with the theoretical value of the design model.Taking a certain stamping part as an example,the experimental results show that using the point cloud processing method to determine the quality of the large quantities of the parts is feasible and correct.The high-efficient and accurate method is provided for the quality determination of the large quantities of the parts.
作者
邢宏文
刘思仁
邱磊
张亚
XING Hongwen;LIU Siren;QIU Lei;ZHANG Ya(Shanghai Aircraft Manufacturing Limited Company,Shanghai 200436,China)
出处
《机械制造与自动化》
2020年第6期217-219,共3页
Machine Building & Automation
基金
中国商飞创新基金资助项目。
关键词
点云
零件检测
点云分割
激光扫描
point cloud
detection of parts
point cloud segmentation
laser scanning
