Research on Route Planning of Adaptive UAV Inspection Considering Sag Variation of Transmission Lines

doi:10.3969/j.issn.1008-0198.2024.04.015

Abstract

Abstract: At present, UAV based precision inspection does not consider the influence of temperature on the sag of guide ground wire, which is difficult to operate in field and low inspection efficiency. To solve the above problems, this paper proposes an adaptive UAV inspection route planning technology considering the sag variation of transmission lines. Based on catenary equation, vectorization analysis and calculation are carried out on the point cloud data of the classified transmission lines, and the vectorized transmission lines have been obtained. Based on the discrete point data generated by interpolation, the waypoint spacing is calculated according to the camera parameters, photo distance, overlap rate and other parameters of the inspection UAV, and the adaptive UAV inspection route is generated. The flight test of patrol route with adaptive sag change of the transmission line is carried out. The test results show that the autonomous patrol route planning can be carried out by fully considering the sag change of the wire caused by temperature change, and the appropriate photo distance and photo overlap rate can be set, the texture and defect of guide ground wire can be clearly identified, and the image of overhead transmission wires and ground wires can be collected autonomously, completely and efficiently.

Key words: UAV, overhead transmission lines, sag, flight route, precision inspection

CLC Number:

TM755

ZHANG Li, ZHOU Xueming, SHEN Yu, YAO Yao, FENG Zhiqiang. Research on Route Planning of Adaptive UAV Inspection Considering Sag Variation of Transmission Lines[J]. Hunan Electric Power, 2024, 44(4): 105-111.

References

[1] 王勇强,周学明,张政,等. 基于LSD与深度学习的轻量化导地线缺陷检测算法[J]. 光学与光电技术,2024,22(1):60-66.
[2] 赵蓂冠,王辉,董新胜,等. 某220kV架空线路地线断股故障分析[J].电工电气,2021(3):41-44.
[3] 王安才. 110kV架空线路常见故障原因分析[J].冶金设备,2023(增刊1):71-73.
[4] 卢正飞,蔡宜君,刘子俊,等. 基于双端信息的高压架空线断线故障识别原理[J]. 电力系统保护与控制,2018,46(20):39-45.
[5] 徐云鹏,毛强,李庭坚. 输电线路机巡与人巡效果对比及协同巡检建议[J]. 南方电网技术,2016,10(2):44-47.
[6] 张洪才.直升机巡检输电线路锈蚀缺陷识别方法研究[D].大连:大连海事大学,2009.
[7] 鲁杰,陈建,宁岩,等. 基于人工智能的输电线路无人机巡检技术分析[J]. 中国高新科技,2022(16): 44-46.
[8] 马斯维,靳函通. 输电线路无人机全自主巡检方案[J]. 流体测量与控制,2023,4(3):49-52.
[9] 李慧鹏,黄道春,邓永清,等.无人机巡检变电设备研究进展与展望[J].湖南电力,2022, 42(6):32-39.
[10] 尹林,胡京,王文彬,等. 环境条件对基于无人机红外检测的零值绝缘子检测判据的影响研究[J].电瓷避雷器,2023(5):171-177.
[11] 马博文. 面向无人机巡检的小目标智能检测技术研究[D].南京:南京邮电大学,2023.
[12] 严峻超,徐建军,徐军波,等. 基于“一线两向”模式下的无人机输电线路高效巡检方式研究 [J]. 电子制作,2023,31(12):106-109.
[13] 钱金伟,范杨,陈国辉,等. 基于多传感器的无人机自主导地线巡视方法[J]. 电子设计工程, 2023,31(18):136-139.
[14] 程玮,杨智玲. 基于改进PSO的无人机精细化自主巡检航迹布设优化[J]. 长春大学学报,2024,34(2):8-14.
[15] 杨航,宁芊,周新志. 基于PSO-Markov联合模型的无人机路径规划[J]. 火力与指挥控制,2019,44(12):6-11.
[16] 周毅,李东武,孟浩,等. 遗传算法路径规划在无人机电力巡线中的应用[J].自动化技术与应用,2021,40(2):29-33.
[17] SENTHILNATH J, KUMAR A, JAIN A, et al. BS-McL:bilevel segmentation framework with metacognitive learning for detection of the power lines in UAV imagery[J].IEEE Transactions on Geoscience and Remote Sensing, 2022,60:1-12.
[18] WU Y,ZHA0 G,HU J,et al.Overhead transmission line parameter reconstruction for UAV inspection based on tunneling magneto-resistive sensors and inverse models[J]. IEEE Transactions on Power Delivery, 2019, 34(3): 819 -827.
[19] 罗隆福,李冬,钟杭.基于改进RRT的无人机电力杆塔巡检路径规划[J].湖南大学学报(自然科学版),2018,45(10):80-86.
[20] 戴永东,王永强,高超,等.电力输电线路无人机巡检航线智能规划方法[J]. 重庆理工大学学报(自然科学),2023,37(9):253-260.
[21] 戴佳权. 基于机载LiDAR的电力线三维建模与应用研究[D].厦门:厦门理工学院,2019.
[22] ZHANG L,RUAN J J,DU Z Y,et al. Short-term failure warning for transmission tower under land subsidence condition[J].IEEE Access,2020,8: 10455- 10465.
[23] 刘宏杰,陈泊远. 基于无人机低空摄影技术的架空输电线路智能巡检方法[J]. 电工技术,2024(3):80-83.