多级索引框及移动向量联合的接触网提取方法

doi:10.13474/j.cnki.11-2246.2023.0332

测绘通报 ›› 2023, Vol. 0 ›› Issue (11): 82-87.doi: 10.13474/j.cnki.11-2246.2023.0332

多级索引框及移动向量联合的接触网提取方法

林凯伦¹, 杨元维^1,2, 高贤君^1,2,3, 谭美淋⁴, 张跃¹

1. 长江大学地球科学学院, 湖北武汉 430100;
2. 湖南科技大学测绘遥感信息工程湖南省重点试验室, 湖南湘潭 411201;
3. 东华理工大学自然资源部环鄱阳湖区域矿山环境监测与治理重点试验室, 江西南昌 330013;
4. 内蒙古自治区测绘地理信息中心, 内蒙古呼和浩特 010050

收稿日期:2023-02-15 出版日期:2023-11-25 发布日期:2023-12-07
通讯作者: 杨元维。E-mail:yyw_08@163.com
作者简介:林凯伦(1999—),男,硕士生,主要研究方向为三维点云。E-mail:1418208258@qq.com
基金资助:
自然资源部环鄱阳湖区域矿山环境监测与治理重点试验室开放基金(MEMI-2021-2022-08);城市轨道交通数字化建设与测评技术国家工程试验室开放课题基金(2021ZH02);湖南科技大学测绘遥感信息工程湖南省重点试验室开放基金(E22133;E22205)

Catenary extraction method combined with multi-level index frame and motion vector

LIN Kailun¹, YANG Yuanwei^1,2, GAO Xianjun^1,2,3, TAN Meilin⁴, ZHANG Yue¹

1. School of Geosciences, Yangtze University, Wuhan 430100, China;
2. Open Fund of Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying, Mapping and Remote Sensing, Hunan University of Science and Technology, Xiangtan 411201, China;
3. Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang 330013, China;
4. Region Surveying and Mapping Geographic Information Center, Hohhot 010050, China

Received:2023-02-15 Online:2023-11-25 Published:2023-12-07

摘要/Abstract

摘要： 电气化铁道接触网的非接触式检测研究对保障铁道的安全运营具有重要意义,检测工作需要大量的精确接触网点云数据支持,目前存在接触网部件间不易分割导致难以提供精确接触网点云数据支持的问题。针对该问题,本文提出了多级索引及移动向量联合的接触网提取方法。首先利用多级索引框简化铁道场景数据;然后通过轨迹线构建提取通道获取支柱底部中心点集,以计算沿轨移动向量;最后进行二级索引框的姿态调整,实现接触网的准确提取。本文设计了参数分析与对比试验,在10 km铁道场景中进行试验分析。结果表明,本文算法对接触网提取的查准率、查全率、F1均在约99%,均优于参照算法,表明本文算法能够适应复杂场景。

关键词: 接触网提取, 多级索引, 三维激光点云, 点云邻域搜索, 移动向量

Abstract: The research on non-contact detection of catenary of electrified railway is of great significance to ensure the safe operation of the railway. The detection work requires a large number of accurate contact point cloud data support. At present, there is a problem that it is difficult to provide accurate contact point cloud data support due to the difficulty of segmentation between catenary components. Aiming at this problem, this paper proposes a catenary extraction method based on the combination of multi-level index and moving vector. Firstly, the railway scene data is simplified by multi-level index frame.Then the center point set at the bottom of the pillar is obtained by constructing the extraction channel through the trajectory line to calculate the moving vector along the rail. Finally, the attitude of the secondary index frame is adjusted to achieve the accurate extraction of the catenary. In this paper, parameter analysis and comparison experiments are designed, and experimental analysis is carried out in the 10 km railway scene. The results show that the precision, recall and F1 of the algorithm in this paper are about 99%, which are better than the reference algorithm, so the algorithm in this paper can adapt to complex scenes.

Key words: catenary extraction, multi-level index, 3D LiDAR, point cloud neighborhood search, movement vector

中图分类号:

P208

林凯伦, 杨元维, 高贤君, 谭美淋, 张跃. 多级索引框及移动向量联合的接触网提取方法[J]. 测绘通报, 2023, 0(11): 82-87.

LIN Kailun, YANG Yuanwei, GAO Xianjun, TAN Meilin, ZHANG Yue. Catenary extraction method combined with multi-level index frame and motion vector[J]. Bulletin of Surveying and Mapping, 2023, 0(11): 82-87.

参考文献

[1] 齐冬莲,钱佳莹,闫云凤,等. 一种基于RefineDet网络和霍夫变换的高速铁路接触网吊弦状态多尺度检测方法[J]. 电子与信息学报,2021,43(7): 2014-2022.
[2] 杨文明. 川藏铁路波密至林芝段工程地质灾害危险性评估[J]. 灾害学,2021,36(3): 7.
[3] 周靖松,韩志伟,杨长江. 基于三维点云的接触网几何参数检测方法[J]. 仪器仪表学报,2018,39(4): 239-246.
[4] 韩志伟,刘志刚,张桂南,等. 非接触式弓网图像检测技术研究综述[J]. 铁道学报,2013,35(6): 40-47.
[5] 张韬. 基于图像处理的接触网检测系统研究与改进[J]. 铁道机车车辆,2009,29(1): 68-71.
[6] 郝雪丽,孙朝云,耿方圆,等. 基于三维点云数据的集料颗粒棱角性量化评价[J]. 华南理工大学学报(自然科学版),2021,49(1): 142-152.
[7] GU Yanfeng,CAO Zhimin,DONG Limin. A hierarchical energy minimization method for building roof segmentation from airborne LiDAR data[J]. Multimedia Tools and Applications,2017,76(3): 4197-4210.
[8] SAMPATH A,SHAN Jie. Segmentation and reconstruction of polyhedral building roofs from aerial lidar point clouds[J]. IEEE Transactions on Geoscience and Remote Sensing,2010,48(3): 1554-1567.
[9] ELBERINK S O,KHOSHELHAM K. Automatic extraction of railroad centerlines from mobile laser scanning data[J]. Remote Sensing,2015,7(5): 5565-5583.
[10] 贾秋生,史新兴,李华聪,等. 基于混合区域极点配置的航空发动机全包线鲁棒变参数控制器设计[J]. 推进技术,2020,41(2): 431-438.
[11] ARASTOUNIA M. Automated recognition of railroad infrastructure in rural areas from LiDAR data[J]. Remote Sensing,2015,7(11): 14916-14938.
[12] ZHOU Liang,VOSSELMAN G. Mapping curbstones in airborne and mobile laser scanning data[J]. International Journal of Applied Earth Observation and Geoinformation,2012,18: 293-304.
[13] LV Wei,TANG Weiyu,HUANG Hongliang,et al. Research and application of intersection clustering algorithm based on PCA feature extraction and K-means[J]. Journal of Physics: Conference Series,2021,1861(1): 012001.
[14] PASTUCHA E. Catenary system detection,localization and classification using mobile scanning data[J]. Remote Sensing,2016,8(10): 801.
[15] POWERS D M W. Evaluation: from precision,recall and F-measure to ROC,informedness,markedness and correlation[EB/OL]. [2023-01-16]. https://arxiv.org/abs/2010.16061.pdf.

多级索引框及移动向量联合的接触网提取方法

Catenary extraction method combined with multi-level index frame and motion vector

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