Optimizing the Fault Localization Path of Distribution Network UAVs Based on a Cloud-Pipe-Side-End Architecture

被引：0

作者：

Liu, Lan ^{[1
]}

Qin, Ping ^{[1
]}

Wu, Xinqiao ^{[1
]}

Zhang, Chenrui ^{[1
]}

机构：

[1] China Southern Power Grid Digital Grid Technol Gua, Digital Power Transmiss Grid Dept, Guangzhou 510000, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2024年 / 15卷 / 12期

关键词：

Cloud-pipe-edge-end architecture; distribution network UAV; cloud-edge collaboration; edge computing; OPTIMIZATION;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The currently proposed optimization algorithm for cooperative fault inspection of distribution network UAVs struggles to accurately detect fault points quickly, leading to low inspection efficiency. To address these issues, we investigate a new fault localization path optimization algorithm for distribution network UAVs based on a cloud-pipe-edge-end architecture. This architecture employs multiple drones for coordinated control, allowing for the simultaneous detection of suspected fault areas. Communication links facilitate interaction at both the drone and system levels, enabling the transmission of fault diagnosis information. Fault defects are identified, and the information is analyzed within an edge computing framework to achieve precise fault localization. Experimental results demonstrate that the proposed algorithm significantly enhances detection speed and accuracy, providing robust technical support for UAV operations.

引用

页码：338 / 346

页数：9