基于林火风险的高压输电线路无人机巡检路径规划

张佳庆; 孙韬; 蒋弘瑞; 段君瑞; 缪煦扬; 纪杰

doi:10.16511/j.cnki.qhdxxb.2023.27.007

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清华大学学报（自然科学版） ›› 2024, Vol. 64 ›› Issue (5) : 911-921. DOI: 10.16511/j.cnki.qhdxxb.2023.27.007

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基于林火风险的高压输电线路无人机巡检路径规划

张佳庆¹, 孙韬¹, 蒋弘瑞², 段君瑞², 缪煦扬¹, 纪杰²

作者信息 +

Path planning for transmission line unmanned aircraft inspection based on forest fire risk

ZHANG Jiaqing¹, SUN Tao¹, JIANG Hongrui², DUAN Junrui², MIAO Xuyang¹, JI Jie²

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文章历史 +

摘要

跨越林区的高压输电线路建设存在诱发森林火灾的风险，因此必须重视高压输电线路的巡检工作。目前，以防范林区火灾风险为目的开展的无人机巡检路径规划的相关研究较少，且已有研究未针对电网系统的运维安全，也未考虑各火灾风险因素间的相互影响。因此，该文提出一种基于网络分析法（analytic network process， ANP）和遗传算法（genetic algorithm， GA）的森林电网无人机巡检路径规划方法。首先结合历史数据和实地调研，识别出影响森林火灾风险的典型因素，并对所在线路及周边林区开展火灾风险评估，划分出高火险区域；再将这些高火险区域设置为巡检节点，基于GA规划出最短的无人机巡检路径。此外，提出一种基于最大偏转角约束的路径优化方法，对路径中不满足最大偏转角约束的节点进行了优化。该文以中国安徽省某重要输电通道线路3542#-3547#为应用对象，评估得出了线路周边存在10处高火险区域，规划出长度为5 391.72 m的无人机巡检路径，再利用最大偏转角约束的方法进行路径优化，优化后的路径总长为5 401.36 m，仅比原路径增长了0.179 %。该文提出的无人机巡检路径规划方法以火灾风险评估为基础，兼顾了各林火风险因素间的相互影响，可以为后续林区高压输电线路的无人机巡检路径规划相关研究提供参考。

Abstract

[Objective] With the establishment of high-voltage transmission lines across forested areas, their inspection becomes crucial to reduce the fire risk of transmission lines and forest areas. At present, few studies have studied the path planning for unmanned aircraft inspection of transmission lines based on the fire risk in forest areas, but they do not address the security of the operation and maintenance of the power grid system or consider the interactions between different influencing factors. Therefore, an unmanned aerial vehicle path planning framework for forest power grid inspection is proposed based on the analytic network process method and genetic algorithm. Moreover, a path optimization method based on the maximum deflection angle constraint is developed. [Methods] After determining the assessment routes, the framework integrates field research and historical data to determine the objective data of these routes and identifies six classes of factors affecting the risk of forest fires: combustible factors, terrain factors, meteorological factors, human factors, surface wet conditions, and rescue conditions. These factors are subdivided into 18 typical factors by researching the historical accident cases and related literature. The forest fire risk indicator system is developed using typical factors, and to guarantee that this indicator system can effectively reflect the actual risk level, herein, the typical factors selected are those that are commonly used and recognized by previous researchers. Subsequently, weights for these typical factors are computed based on the analytic network process. Compared with the hierarchical analysis method, which is traditionally applied in earlier works, the network analysis method has the advantage of considering the interactions between the factors. The weights with objective data are combined to calculate the fire risk value for each grid. The high fire risk grids are employed as inspection nodes, and the shortest inspection path is acquired using path planning via the unmanned aerial vehicle inspection based on the genetic algorithm to reach the objective of obtaining real-time data in a short time, at low cost, and with high coverage. For the nodes in the path that do not meet the maximum deflection angle constraint, path optimization is conducted by adding new optimization nodes and the shortest path is ensured under the condition that the roadbed meets the maximum deflection angle constraint. [Results] Sections #3542—#3547 of the line of an important transmission channel in Anhui are taken as an application object. Ten high fire risk areas around the line are determined, and path planning is performed on them. The proposed framework yields an optimal path length of 5 391.72 m, and the path length optimized based on the maximum deflection angle is 5 401.36 m. Here, the path length is only increased by 0.179 % compared with the original one. This indicates that the path optimization method not only makes the original path satisfy the constraint of maximum deflection angle, but also increases the path length to be shorter, which has good optimization effect. [Conclusions] This work presents a path planning framework for the unmanned aerial vehicle inspection based on the results of fire risk assessment considering the interactions between various forest fire risk factors. In addition, the proposed path optimization method can make the path satisfy all constraints with a small increase in the path length. The proposed framework and optimization method offer reference and future ideas for realizing the unmanned aerial vehicle inspection of transmission lines in forest areas.

导出引用

张佳庆, 孙韬, 蒋弘瑞, 段君瑞, 缪煦扬, 纪杰. 基于林火风险的高压输电线路无人机巡检路径规划[J]. 清华大学学报（自然科学版）. 2024, 64(5): 911-921 https://doi.org/10.16511/j.cnki.qhdxxb.2023.27.007

ZHANG Jiaqing, SUN Tao, JIANG Hongrui, DUAN Junrui, MIAO Xuyang, JI Jie. Path planning for transmission line unmanned aircraft inspection based on forest fire risk[J]. Journal of Tsinghua University(Science and Technology). 2024, 64(5): 911-921 https://doi.org/10.16511/j.cnki.qhdxxb.2023.27.007

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基金

国家重点研发计划项目（2022YFC3003101）；国网安徽省电力有限公司科技项目（521205220001）

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2023-09-19	2024-05-15
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