测绘通报 ›› 2023, Vol. 0 ›› Issue (12): 159-163,177.doi: 10.13474/j.cnki.11-2246.2023.0377

• 技术交流 • 上一篇    

机器视觉下的钢轨廓形提取与磨耗测量

赵静   

  1. 中铁建(天津)轨道交通投资发展有限公司, 天津 300000
  • 收稿日期:2023-08-29 发布日期:2024-01-08
  • 作者简介:赵静(1984-),女,高级工程师,主要从事轨道交通勘察设计研究及工程技术管理方面的工作。E-mail:124588205@qq.com
  • 基金资助:
    天津市交通运输科技发展计划(2022-40)

Extracting rail profile and measuring wear based on machine vision

ZHAO Jing   

  1. CRCC(Tianjin)Rail-transit Investment Development Co., Ltd., Tianjin 300000, China
  • Received:2023-08-29 Published:2024-01-08

摘要: 随着中国高速铁路的迅速发展,传统的接触式钢轨磨耗检测方法测量效率较低且易受钢轨变形与表面伤损的影响,已无法满足钢轨维修养护的需求。为了快速精确测量钢轨廓形及钢轨磨耗,本文提出了一种基于机器视觉的轮廓提取方法,搭建单目机器视觉钢轨廓形提取系统,通过自由平面靶标定位,采用基于结构光颜色和Steger算法的粗精二级钢轨廓形提取方法,提出基于粒子群优化的双圆拟合钢轨廓形匹配算法,实现测量廓形与标准廓形对齐,并得出磨耗值。试验结果表明,该系统检测精度达0.128 mm,同时具备较高的测量效率。

关键词: 高速铁路, 轨道轮廓提取, 线结构光, 光平面标定, 图像处理

Abstract: With the rapid development of China's high-speed railways, traditional contact-based rail wear detection methods have limitations in measurement efficiency and are easily affected by rail deformations and surface damages, failing to meet the demands of the rail maintenance. To quickly and accurately measure the rail profile and assess rail wear, a contour extraction method based on machine vision is proposed. A monocular machine vision system for rail profile extraction has been established. After positioning with a free planar target, a two-level rail profile extraction method based on structured light color and the Steger algorithm is employed. A double circle fitting rail profile matching algorithm based on particle swarm optimization is introduced to align the measured profile with the standard profile and derive the wear value. Experimental results demonstrate that this system achieves a detection accuracy of 0.128 mm and offers high measurement efficiency.

Key words: high-speed rail, rail contour extraction, linear structured light, optical plane calibration, image processing

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