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一种基于大型无人直升机的电力线路巡检多传感器平台方法。

A Multiple Sensors Platform Method for Power Line Inspection Based on a Large Unmanned Helicopter.

作者信息

Xie Xiaowei, Liu Zhengjun, Xu Caijun, Zhang Yongzhen

机构信息

Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100830, China.

School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China.

出版信息

Sensors (Basel). 2017 May 26;17(6):1222. doi: 10.3390/s17061222.

DOI:10.3390/s17061222
PMID:28587114
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5492564/
Abstract

Many theoretical and experimental studies have been carried out in order to improve the efficiency and reduce labor for power line inspection, but problems related to stability, efficiency, and comprehensiveness still exist. This paper presents a multiple sensors platform method for overhead power line inspection based on the use of a large unmanned helicopter. Compared with the existing methods, multiple sensors can realize synchronized inspection on all power line components and surrounding objects within one sortie. Flight safety of unmanned helicopter, scheduling of sensors and exact tracking on power line components are very important aspects when using the proposed multiple sensors platform, therefore this paper introduces in detail the planning method for the flight path of the unmanned helicopter and tasks of the sensors before inspecting power lines, and the method used for tracking power lines and insulators automatically during the inspection process. To validate the method, experiments on a transmission line at Qingyuan in Guangdong Province were carried out, the results show that the proposed method is effective for power line inspection.

摘要

为了提高电力线路巡检的效率并减少人力,已经开展了许多理论和实验研究,但仍存在与稳定性、效率和全面性相关的问题。本文提出了一种基于大型无人直升机的架空电力线路巡检多传感器平台方法。与现有方法相比,多传感器可以在一次飞行架次中实现对所有电力线路组件及周围物体的同步巡检。在使用所提出的多传感器平台时,无人直升机的飞行安全、传感器的调度以及对电力线路组件的精确跟踪是非常重要的方面,因此本文详细介绍了在巡检电力线路之前无人直升机飞行路径的规划方法和传感器的任务,以及在巡检过程中自动跟踪电力线路和绝缘子的方法。为验证该方法,在广东省清远市的一条输电线路上进行了实验,结果表明所提出的方法对电力线路巡检是有效的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8a3/5492564/43ef247cf2eb/sensors-17-01222-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8a3/5492564/7d87943422e5/sensors-17-01222-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8a3/5492564/9c05cc7c81d8/sensors-17-01222-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8a3/5492564/2b711c2d0680/sensors-17-01222-g009.jpg
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本文引用的文献

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Sensors (Basel). 2016 Mar 11;16(3):366. doi: 10.3390/s16030366.
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Sensors (Basel). 2016 Feb 19;16(2):250. doi: 10.3390/s16020250.
Sensors (Basel). 2020 Dec 12;20(24):7126. doi: 10.3390/s20247126.
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Cooperative UAV-UGV Autonomous Power Pylon Inspection: An Investigation of Cooperative Outdoor Vehicle Positioning Architecture.无人机-无人地面车辆协作式自主电力塔架巡检:协作式户外车辆定位架构研究
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Fault Detection in Power Equipment via an Unmanned Aerial System Using Multi Modal Data.基于无人机系统利用多模态数据的电力设备故障检测
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