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知识引导的铁路站场接触网点云导线特征智能提取方法

朱军 张传军 赵剑峰 王学柱 付林 黄智勇 郭鹏飞

朱军, 张传军, 赵剑峰, 王学柱, 付林, 黄智勇, 郭鹏飞. 知识引导的铁路站场接触网点云导线特征智能提取方法[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20230435
引用本文: 朱军, 张传军, 赵剑峰, 王学柱, 付林, 黄智勇, 郭鹏飞. 知识引导的铁路站场接触网点云导线特征智能提取方法[J]. 西南交通大学学报. doi: 10.3969/j.issn.0258-2724.20230435
ZHU Jun, ZHANG Chuanjun, ZHAO Jianfeng, WANG Xuezhu, FU Lin, HUANG Zhiyong, GUO Pengfei. Intelligent Extraction Method of Railway Station Overhead Catenary Wire Features from Point Cloud Guided by Knowledge[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230435
Citation: ZHU Jun, ZHANG Chuanjun, ZHAO Jianfeng, WANG Xuezhu, FU Lin, HUANG Zhiyong, GUO Pengfei. Intelligent Extraction Method of Railway Station Overhead Catenary Wire Features from Point Cloud Guided by Knowledge[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20230435

知识引导的铁路站场接触网点云导线特征智能提取方法

doi: 10.3969/j.issn.0258-2724.20230435
基金项目: 国家自然科学基金项目(42271424)
详细信息
    作者简介:

    朱军(1976—),男,教授,博士,研究方向为三维地理信息系统与虚拟地理环境,E-mail:zhujun@swjtu.edu.cn

  • 中图分类号: P232

Intelligent Extraction Method of Railway Station Overhead Catenary Wire Features from Point Cloud Guided by Knowledge

  • 摘要:

    为解决铁路站场接触网点云噪声分布不规律及语义分割难度大的问题,提出一种智能提取方法,以增强接触网异常检测能力. 首先,对站场接触网场景数据进行深入分析,构建导线及钢轨顶面点云提取的知识框架;其次,考虑站场接触网点云空间特征,设计站场关键要素点云的分割与融合滤波方法;然后,建立站场接触网强空间语义约束规则,提出知识引导的导线特征智能精细提取方法;基于此,采用WHU-TLS等站场点云数据集,搭建实验平台并开展实验分析,实验结果表明:在部分点云缺失以及噪声干扰等复杂环境下,本文方法易于操作且自动化程度高,相比传统导线特征提取方法耗时最少,100 m范围内站场接触网导线特征提取的平均精度达到±5 mm,能够有效支撑铁路站场接触网几何特征的智能检测.

     

  • 图 1  总体研究框架

    Figure 1.  Overview of the research framework

    图 2  预处理算法结构框架

    Figure 2.  Preprocessing algorithm framework

    图 3  接触网导线参数智能提取

    Figure 3.  Intelligent extraction of catenary wire parameters

    图 4  导线点云自适应邻域点选择

    Figure 4.  Adaptive neighborhood point selection of wire point cloud

    图 5  接触网导线精细提取方法

    Figure 5.  Method for Precise Extraction of Catenary Wire

    图 6  P60钢轨点云模型

    Figure 6.  Point Cloud Model of P60 Steel Rail

    图 7  站场接触网原始点云

    Figure 7.  Original point cloud of catenary in railway station

    图 8  站场点云分类滤波抽稀结果

    Figure 8.  Results of point cloud classification, filtering, and thinning

    图 9  接触网导线结点局部图

    Figure 9.  Local diagram of catenary wire node

    图 10  接触网导线与钢轨顶面分割结果

    Figure 10.  Catenary wire and rail top surface segmentation results

    图 11  导线几何特征超限预警系统

    Figure 11.  Parameter out-of-range warning system

    表  1  软硬件配置

    Table  1.   Hardware and software configuration

    环境配置 详细信息
    硬件CPU12th Gen Intel Core i7-12700H
    内存16 GB
    显卡NVIDIA GeForce RTX 3060
    软件系统Windows11
    软件PCL1.12.1、VS2019
    下载: 导出CSV

    表  2  接触网导线点云分割算法对比

    Table  2.   Accuracy of contact wire point cloud extraction

    方法处理范围耗时鲁棒性精确度
    本文方法长距离最少一般最好
    RANSAC短距离较多较强一般
    3D Hough短距离最多较强最差
    下载: 导出CSV

    表  3  接触网导线特征提取结果

    Table  3.   Exaction results of contact wire features mm

    组号 导高 实测
    导高
    导高
    差值
    拉出值 实测拉出值 拉出值差值
    1 5306 5311 −5 193 199 −6
    2 5300 5297 3 197 205 −8
    3 5304 5310 −6 214 212 2
    4 5304 5305 −1 220 218 2
    5 5299 5294 5 223 223 0
    6 5303 5297 6 230 231 −1
    7 6449 6447 2 200 202 −2
    8 6447 6450 −3 211 218 −7
    9 6458 6464 −6 224 225 −1
    10 6450 6456 −6 238 243 −5
    下载: 导出CSV
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  • 收稿日期:  2023-08-29
  • 修回日期:  2024-03-26
  • 网络出版日期:  2025-01-23

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