基于点云数据配准的输电线路异常检测方法
Transmission Line Anomaly Detection Method Based on Point Cloud Data Registration
张乐 1王维坤 1崔雷 1周飞飞 1张振威1
作者信息
- 1. 安徽送变电工程有限公司,安徽合肥 230601
- 折叠
摘要
异常检测是输电线路运维中的重要环节,可为输电线路故障维修提供可靠依据.但现有检测方法命中率较低,且检测结果与实际运行线路的斯皮尔曼相关系数较低.针对现有方法的不足,提出了一种基于点云数据配准的输电线路异常检测方法.首先,利用三维激光扫描仪采集输电线路点云数据;其次,对采集点云数据中离散点进行降噪处理,并通过点云数据配准方法模拟输电线路状态;最后,通过与正常输电线路对比识别线路异常状态,以完成输电线路异常检测.实验表明,异常检测方法命中率高达 96%以上,检测结果与实际运行线路的斯皮尔曼相关系数达 0.9以上,同时,该方法在输电线路异常检测方面具有良好的应用前景.
Abstract
Anomaly detection is an important link in the operation and maintenance of transmission lines,providing reliable basis for fault maintenance of transmission lines.However,existing detection methods have a low hit rate,and the Spearman correlation coefficient between detection results and actual operating lines is low.A transmission line anomaly detection method based on point cloud data registration is proposed to address the shortcomings of existing methods.Firstly,use a 3D laser scanner to collect point cloud data of transmission lines.Secondly,denoise the discrete points in the collected point cloud data and simulate the status of transmission lines through point cloud data registration methods.Finally,by comparing with normal transmission lines,identify the abnormal status of the transmission lines to complete the detection of abnormal transmission lines.The experiment shows that the hit rate of the anomaly detection method is over 96%,and the Spearman correlation coefficient between the detection results and the actual operating lines is over 0.9.At the same time,this method has good application prospects in anomaly detection of transmission lines.
关键词
点云数据配准/输电线路/三维激光扫描/离散点/命中率Key words
point cloud data registration/transmission lines/3D laser scanning/discrete points/hit rate引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据