首页|一种输电线路边、端协同检测方法和系统实现

一种输电线路边、端协同检测方法和系统实现

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输电线路在日常运行中受环境等因素影响会出现不同程度的配件老化、破损,导致输电、负载能力无法满足运营安全需求。为解决传统人工桥检作业难度大、检测时间长、工作空间受限等问题,提出一种基于无人机和深度学习的一体化输电线路巡检系统。系统基于卷积神经网络技术,采用YOLOv7 目标检测算法对无人机采集的图像进行检测。首先通过事先设计的飞行路径和实时拍摄采集图像,其次传送到事先部署于无人机边缘盒子中的目标检测模型进行检测,最后将检测结果通过边缘盒子发送至使用者的APP。
A Method for Edge and End Collaborative Detection of Transmission Lines and System Implementation
The transmission lines may experience varying degrees of aging and damage to their accessories due to environmental and other factors in daily operation,resulting in transmission and load capacity not meeting operational safety needs.To address the challenges of traditional manual bridge inspection,such as high difficulty,long detection time,and limited workspace,captured by UAV.Firstly,the system collects images through pre-designed flight paths and real-time shooting.Second,it transmits them to the target detection model deployed in the edge box of the UAV for detection.Finally,it sends the detection results to the user's APP through the edge box.

edge and end collaborationUAVelectric power inspection

孙仝、邓浩光、程昭荣、范亮、陆林

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广东电网有限责任公司肇庆供电局,广东 肇庆 526000

广州中科智巡科技有限公司,广东 广州 510623

边端协同 无人机 电力巡检

中国南方电网有限责任公司科技项目资助

031200KK52210032

2024

现代信息科技
广东省电子学会

现代信息科技

ISSN:2096-4706
年,卷(期):2024.8(1)
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