融合探测概率的电力线路点云分类方法
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1.国网内蒙古东部电力有限公司内蒙古自治区 呼和浩特 010010;2.国网内蒙古东部电力 有限公司兴安供电公司内蒙古自治区 乌兰浩特 137400

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TN

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Classification method of power line fused detection probability
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1.Unit 1 State Grid Inner Mongolia Eastern Power Co., Ltd.,Hohhot 010010, China;2.Unit 1 Xing′an Power Supply Company of State Grid Inner Mongolia Eastern Power Co., Ltd.,Ulanhot 137400, China

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    摘要:

    为了解决机载激光雷达在电力巡检应用中的点云快速精准分类问题,从激光雷达探测原理出发设计了一种电力巡检点云分类方法。从激光雷达方程出发建立了电力线、杆塔和地物等不同类型的目标的被探测概率模型,在此基础上将点云网格化并融合探测概率实现了网格点云的参数化描述,基于网格参数设计了点云分类方法完成不同类型的目标点云的快速分类。为验证本文算法的有效性,设计了多组电力巡检点云分类实验,实验结果表明本文所设计的电力线路点云分类方法分类查全率可达到98%,单档电力线点云分类耗时14 s,分类准确率和效率较高。

    Abstract:

    Method for classification of point cloud is presented based on LiDAR function in order to solve the problem of fast and accurate classification of point cloud application of power-line inspection. Detect probabilistic of different kind of targets such as power-line, tower and ground target are built based on LiDAR function. Based on the presented model of detecting probabilistic model, point cloud is meshed and parameters of each mesh are calculated based on the detecting probabilistic model. Fast classification method is designed based the parameters of each mesh, in which point cloud from power-line, tower and ground target is extracted. In order to verify the effectiveness of the presented method of classification, serval groups of point cloud are applied in experiment of point cloud classification. According to the results of experiments, recall ration of the presented method can reach as high as 98%, and time-consuming of classification for one segment of power line can reach 14 s. Results of the presented experiments show that the presented method of classification of point cloud can reach higher accuracy and efficiency.

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李海明,冯新文,吕通发,何永春,袁晓磊.融合探测概率的电力线路点云分类方法[J].电子测量技术,2023,46(22):102-108

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  • 在线发布日期: 2024-03-08
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