北京航空航天大学学报 ›› 2018, Vol. 44 ›› Issue (11): 2273-2282.doi: 10.13700/j.bh.1001-5965.2018.0050

• 论文 • 上一篇    下一篇

行车环境下钢轨轮廓自动配准方法

王昊1, 王胜春1,2, 王卫东1   

  1. 1. 中国铁道科学研究院, 北京 100081;
    2. 中国铁道科学研究院 基础设施检测研究所, 北京 100081
  • 收稿日期:2018-01-19 修回日期:2018-02-10 出版日期:2018-11-20 发布日期:2018-11-27
  • 通讯作者: 王昊,E-mail:wanghao1984@rails.cn E-mail:wanghao1984@rails.cn
  • 作者简介:王昊,男,博士研究生,副研究员。主要研究方向:机器视觉、结构光测量;王胜春,男,博士。主要研究方向:机器视觉、图像处理、缺陷检测;王卫东,男,博士,教授,博士生导师。主要研究方向:铁道工程、结构光测量。
  • 基金资助:
    中国铁路总公司科技研究开发计划(J2016G003);中国铁路总公司重大科研计划(2015G001-B);北京市科技计划(D17110600060000)

Automatic registration method of rail profile in train-running environment

WANG Hao1, WANG Shengchun1,2, WANG Weidong1   

  1. 1. China Academy of Railway Sciences, Beijing 100081, China;
    2. Infrastructure Inspection Research Institute, China Academy of Railway Sciences, Beijing 100081, China
  • Received:2018-01-19 Revised:2018-02-10 Online:2018-11-20 Published:2018-11-27
  • Supported by:
    The Research and Development Plan of Science and Technology of Chinese Railway Corporation (J2016G003); Major Research Plan of Chinese Railway Corporation (2015G001-B); Beijing Science and Technology Planning Project (D17110600060000)

摘要: 针对行车环境下列车晃动和环境噪声对钢轨磨耗测量的影响,提出了一种轨腰小圆弧自动提取方法,实现了钢轨轮廓的高精度配准。首先,提出了基于截断残差直方图的多项式拟合方法,寻找廓形最优拟合曲线,降低了噪声对轮廓拟合的影响;然后,针对拟合曲线的曲率分布特征,提出了基于动态窗口的最大曲率熵区间搜索算法实现轨腰小圆弧的自动分割;最后,基于两侧轨腰小圆弧拟合2个圆心作为匹配基准点,实现钢轨测量轮廓与标准设计轮廓的对齐配准。静态实验结果表明,该方法的系统测量误差均值和标准差都控制在0.01 mm之内,具有较小的测量误差和良好的重复性。现场动态测量也验证了该方法在行车环境下的重复性精度,多次测量结果的重复性良好,钢轨磨耗动态测量偏差控制在0.2 mm以内。

关键词: 钢轨磨耗, 轮廓配准, 曲率熵, 结构光, 行车环境

Abstract: Aimed at the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of small circular arc of the rail waist, and achieved the high-precision registration of rail profile. First, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting; Then, aimed at the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window's maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc; Finally, two circle centers were fitted as matching reference points based on small circular arcs on both sides, and the alignment from the measured profile to the standard designed profile was realized. The static experimental results show that the mean value of system measurement error and standard deviation of the method are controlled within 0.01 mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability accuracy of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2 mm with high repeatability.

Key words: rail wear, profile registration, curvature entropy, structured light, train-running environment

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