首页> 外文会议>2019 23rd International Conference Information Visualization >A Comparative Study of Extraction Cylinder Features in Industrial Point Clouds
【24h】

A Comparative Study of Extraction Cylinder Features in Industrial Point Clouds

机译:工业点云中提取缸特征的比较研究

获取原文
获取原文并翻译 | 示例

摘要

With the technological advancement in the field of Computer Aided Design such as the rapid development of scanning technologies, the reconstruction of complete and incomplete cylinders given noisy point clouds with form defects becomes an important issue. In fact, cylindrical surfaces are found in domestic to industrial contexts. In this paper, a comparative study of cylinder fitting algorithms manufactured in the LIPPS laboratory is proposed. The aim of the proposed approach is to determine the diameter of cylindrical feature for minimizing roundness error from experimental data-points. The roundness error is evaluated using two internationally defined methods: Minimum Circumscribed Cylinder (MCC) and Maximum Inscribed Cylinder (MIC). All algorithms give similar results in the case where the scanned cylinder is complete and without form defects, but in the case of missing data some algorithms give unacceptable results. The two reference cylinders have been independently analyzed, respecting six criteria (calculation complexity, damping parameter, initial guess, time, circularity error and complexity cylinder). The results of algorithms are also compared to help manufacturers and inspectors facilitate and improve the application of these methods and to select the appropriate algorithm for size and form evaluation.
机译:随着计算机辅助设计领域的技术进步,例如扫描技术的飞速发展,给定带噪声的点云和形式缺陷的完整圆柱体和不完整圆柱体的重建成为重要的课题。实际上,在家庭到工业环境中都可以找到圆柱形表面。在本文中,对LIPPS实验室制造的气缸装配算法进行了比较研究。提出的方法的目的是确定圆柱特征的直径,以从实验数据点最小化圆度误差。圆度误差使用两种国际定义的方法进行评估:最小外接圆柱(MCC)和最大外接圆柱(MIC)。在已扫描的圆柱体完整且没有形式缺陷的情况下,所有算法都给出相似的结果,但是在数据丢失的情况下,某些算法给出的结果不可接受。对两个参考圆柱体进行了独立分析,并遵循六个标准(计算复杂度,阻尼参数,初始猜测,时间,圆度误差和复杂度圆柱体)。还比较了算法的结果,以帮助制造商和检查人员促进和改进这些方法的应用,并选择合适的算法进行尺寸和形状评估。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号