基于YOLOv3目标识别的无人值守光伏电站防火在线监测系统设计
Design of an Unmanned Photovoltaic Power Station Fire Prevention Online Monitoring System Based on YOLOv3 Target Recognition
王斌 1陈宏 1曾峥 2张建林 1周凯1
作者信息
- 1. 中电(福建)电力开发有限公司,福建南平 353000
- 2. 中电投绿能科技有限公司,上海虹口 200000
- 折叠
摘要
文章针对光伏电站火灾多发、监测困难的问题,提出了一种基于YOLOv3目标识别算法的无人值守光伏电站防火在线监测系统.该系统通过多传感器数据融合、异构网络通信等关键技术,实现了对光伏电站火情的早期预警和准确定位.试验结果表明,该系统在火情检测准确率、数据传输效率、用户交互体验等方面均达到了优异水平,可显著提升光伏电站运维的智能化程度.
Abstract
This article proposes an unmanned online fire prevention monitoring system for photovoltaic power stations based on the YOLOv3 target recognition algorithm to address the issues of frequent fire incidents and difficult monitoring.The system achieves early warning and accurate positioning of photovoltaic power plant fires through key technologies such as multi-sensor data fusion and heterogeneous network communication.The experimental results show that the system has achieved excellent levels in fire detection accuracy,data transmission efficiency,and user interaction experience,which can significantly improve the intelligence level of photovoltaic power station operation and maintenance.
关键词
光伏电站/火灾监测/YOLOv3/多传感器数据融合Key words
photovoltaic power station/fire monitoring/YOLOv3/multi sensor data fusion引用本文复制引用
出版年
2024
NETL
NSTL
万方数据