圆结构光视觉三维点管道缺陷检测及重构

王颖, 韩静文, 金翠云, 张艳辉

王颖, 韩静文, 金翠云, 张艳辉. 圆结构光视觉三维点管道缺陷检测及重构[J]. 应用光学, 2014, 35(3): 441-445.
引用本文: 王颖, 韩静文, 金翠云, 张艳辉. 圆结构光视觉三维点管道缺陷检测及重构[J]. 应用光学, 2014, 35(3): 441-445.
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WANG Ying, HAN Jing-wen, JIN Cui-yun, ZHANG Yan-hui. In-pipe defects detection and reconstruction based on circle structured light[J]. Journal of Applied Optics, 2014, 35(3): 441-445.
Citation: WANG Ying, HAN Jing-wen, JIN Cui-yun, ZHANG Yan-hui. In-pipe defects detection and reconstruction based on circle structured light[J]. Journal of Applied Optics, 2014, 35(3): 441-445.
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圆结构光视觉三维点管道缺陷检测及重构

  • 北京化工大学 信息科学与技术学院 北京 100029

详细信息
    通讯作者:

    王颖(1969-)，女,天津人，博士，副教授，主要从事机器视觉和光电精密测试技术研究工作。 Email：wangying@mail.buct.edu.cn

  • 中图分类号: TN911.73;TP391.41

In-pipe defects detection and reconstruction based on circle structured light

  • College of Information Science &Technology,Beijing University of Chemical Technology,Beijing 100029,China

摘要

    摘要
  • 摘要: 管道内表面的缺陷检测对于保证介质运输安全，避免泄漏和爆炸事故非常重要。在分析三维点分布几何特征的基础上，对基于视觉检测获得的管道内表面三维点,通过判断同一圆周上相邻点法线夹角变化检测管道内表面的凹凸缺陷，采用空间点相邻三角平面法线加权平均获取空间点的法线。依据三维点呈圆周分布的特点，采用相邻圆周上点顺次连接进行快速三角剖分。基于上述方法对实际测量的管道内表面三维点和仿真三维点分别进行了凹凸缺陷检测和三维重构。该方法能实现径向变化小于0.1 mm的管道凹凸缺陷的检测和识别,三维测量精度为0.081 mm。
    Abstract: Pipe inner surface defects detection is very important to ensure transmission safety and avoid leaking and explosion accidents. Based on the analysis of the geometry characteristic of the 3D points distribution, for the pipe inner side 3D data which are obtained based on circle structured light machine vision technology, a defect detection method about pipe inner side is proposed by comparing the normal vector angle between adjacent points which are on the same circumference. The point normal vector is calculated by the weighted average of adjacent triangles normal vectors. As the 3D points distribute circumferentially, the adjacent points are adopted to do fast triangulation. By using above method, we conducted defects detection and 3D reconstruction of measured and simulated 3D points inside the pipe, respectively. Results show that the method can detect and identify pipe defects of less than 0.1 mm racial variation with 0.081 mm accuracy.
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  • 刊出日期:  2014-05-14

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