Research Progress and Prospect of UAV Inspection of Substation Equipment

LI Huipeng; HUANG Daochun; DENG Yongqing; LI You; ZENG Zhaoqiang; RUAN Jiangjun

doi:10.3969/j.issn.1008-0198.2022.06.006

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Research Progress and Prospect of UAV Inspection of Substation Equipment

更新时间：2025-06-11

- Research Progress and Prospect of UAV Inspection of Substation Equipment
- Vol. 42, Issue 6, Pages: 32-39(2022)
- 作者机构：
  
  1. 武汉大学电气与自动化学院,湖北,武汉,430072
  2. 国网湖南省电力有限公司超高压变电公司,湖南,长沙,410004
  3. 变电智能运检国网湖南省电力有限公司实验室,湖南,长沙,410004
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1008-0198.2022.06.006
  CLC： TM63
- Published：2022
- 稿件说明：
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李慧鹏, 黄道春, 邓永清, 李游, 曾昭强, 阮江军. 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.

LI Huipeng, HUANG Daochun, DENG Yongqing, et al. Research Progress and Prospect of UAV Inspection of Substation Equipment[J]. 2022, 42(6): 32-39.
李慧鹏, 黄道春, 邓永清, 李游, 曾昭强, 阮江军. 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. DOI： 10.3969/j.issn.1008-0198.2022.06.006.

LI Huipeng, HUANG Daochun, DENG Yongqing, et al. Research Progress and Prospect of UAV Inspection of Substation Equipment[J]. 2022, 42(6): 32-39. DOI： 10.3969/j.issn.1008-0198.2022.06.006.

摘要

采用无人机巡检变电设备可实现对变电设备的多角度、精细化、高效率巡检

然而无人机巡检变电设备尚处于研究和试点应用阶段

在对相关研究现状进行综述的基础上提出了研究展望:在大范围推广前

建议制定无人机巡检变电设备方面的技术规范和标准

结合不同航迹规划算法的优势

实现全局静态航迹和局部动态航迹的智能规划

构建变电设备缺陷样本库

采用人工神经网络等算法推进隐患缺陷智能诊断;针对现有安全距离研究方面的不足

建议充分考虑变电站环境的特殊性

提出面向变电站的无人机作业安全距离确定方法

并开展电场和磁场环境下的测控性能安全距离试验

提出安全距离判据

采用机器学习、数据拟合等方式建立无人机临近异型电极/导体安全距离快速分析方法。

Abstract

The use of UAV inspection of substation equipment can achieve multi-angle

refined and high-efficiency inspection of substation equipment. However

UAV inspection of substation equipment is still at the period of research and pilot application. Research perspectives are presented based on a review of the current state of relevant research. Before large-scale promotion

it is recommended to develop technical specifications and standards for UAV inspection of substation equipment and combineing the advantages of different trajectory planning algorithms to realize the intelligent planning of global static trajectory and local dynamic trajectory. In addition

a sample library of substation equipment defects is build and algorithms such as artificial neural networks is used to promote intelligent diagnosis of hidden defects. In view of the deficiencies in the existing safety distance study

it is recommended to fully consider the special characteristics of the substation environment

and propose a safety distance determination method for UAV operations in substations. The safety distance tests of UAV measurement and control performance under electric field and magnetic field environment are carried out and the safety distance criterion is proposed. In addition

the fast analysis method of safety distance of UAV near heterogeneous electrode/conductor is established by using machine learning and data fitting.

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