Visual distance measurement method for foreign objects under transmission lines by integrating 3D point cloud terrain data

姜骞; 黄欢; 吴建蓉; 张义钊; 广进; 付涛涛; 邹雕

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Visual distance measurement method for foreign objects under transmission lines by integrating 3D point cloud terrain data

更新时间：2026-02-04

- Visual distance measurement method for foreign objects under transmission lines by integrating 3D point cloud terrain data
- Issue 12, (2025)
- 作者机构：
  
  1. 贵州电网有限责任公司电力科学研究院
  2. 贵州电网有限责任公司六盘水供电局
  3. 贵州大学电气工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2025
- 稿件说明：
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姜骞, 黄欢, 吴建蓉, et al. Visual distance measurement method for foreign objects under transmission lines by integrating 3D point cloud terrain data[J]. 2025, (12).
DOI：

姜骞, 黄欢, 吴建蓉, et al. Visual distance measurement method for foreign objects under transmission lines by integrating 3D point cloud terrain data[J]. 2025, (12). DOI：

摘要

针对输电线路二维可视化视频监测方法无法判定异物实际距离而导致误告警频发的问题，本文提出了一种融合三维点云地形数据的输电线路异物可视化测距方法。该方法以广泛应用的无人机三维激光扫描点云地形数据为基础，首先对地面点云数据进行空洞填充，恢复稠密的地面点云数据；随后基于立体视觉空间变换原理，建立三维点云与可见光视频监测终端的空间变换关系；进一步采用YOLOv8算法对监测图像中的塔吊、吊车、挖掘机等机械类异物进行实时动态识别，并输出其像素级包围框；最后结合地面点云数据计算异物的最高点空间坐标，并通过与输电导线点云数据进行空间比对，输出异物与输电线路的实际距离，从而实现输电线路异物的可视化精确测距。实验结果表明，所提方法在实验室模拟环境下的测距误差为2cm，实际线路环境下的平均测距误差为1.01米，可使可视化监测系统有效提高告警准确率。

Abstract

Aiming at the problem that the two-dimensional visual video monitoring method for transmission lines can not determine the actual distance of foreign objects

which leads to frequent false alarms

this paper proposes a visual distance measurement method for foreign objects in transmission lines based on three-dimensional point cloud terrain data. This method is based on the widely used UAV 3D laser scanning point cloud terrain data. Firstly

the ground point cloud data is filled with holes to recover the dense ground point cloud data; Then

based on the spatial transformation principle of stereo vision

the spatial transformation relationship between 3D point cloud and visible light video monitoring terminal is established; Further

the yolov8 algorithm is used to dynamically identify the mechanical foreign bodies such as tower cranes

cranes and excavators in the monitoring image in real time

and its pixel level bounding box is output; Finally

combined with the ground point cloud data

the spatial coordinates of the highest point of the foreign body are calculated

and through the spatial comparison with the transmission line point cloud data

the actual distance between the foreign body and the transmission line is output

so as to realize the visual and accurate distance measurement of the foreign body in the transmission line. The experimental results show that the ranging error of the proposed method in the laboratory simulation environment is 2cm

and the average ranging error in the actual line environment is 1.01 m

which can effectively improve the alarm accuracy of the visual monitoring system.

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