基于5G的重载铁路信号远程监测系统设计
Design of Remote Monitoring System for Heavy duty Railway Signal Based on 5G
刘立辉1
作者信息
- 1. 国能朔黄铁路发展有限责任公司肃宁分公司,河北 沧州 062356
- 折叠
摘要
为保障重载铁路信号系统的安全高效运行,文章设计一种基于 5G的重载铁路信号远程监测系统.该系统采用模块化架构,利用5G的大带宽和低时延特性,实时采集与传输信号设备状态数据.通过部署智能传感器,采用卷积神经网络(Convolutional Neural Networks,CNN)与长短期记忆网络(Long Short-Term Memory,LSTM)深度学习模型,准确监测信号设备状态并预测剩余寿命.实验结果表明,文章系统在数据采集实时性、传输可靠性、检测准确率以及处理能力方面表现出色.
Abstract
To ensure the safe and efficient operation of the heavy-duty railway signal system,this article designs a 5G based remote monitoring system for heavy-duty railway signals.The system adopts a modular architecture,utilizing the high bandwidth and low latency characteristics of 5G to collect and transmit real-time signal equipment status data.By deploying intelligent sensors and using Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM)deep learning models,we can accurately monitor the status of signal devices and predict their remaining lifespan.The experimental results show that the article system performs well in real-time data collection,transmission reliability,detection accuracy,and processing capability.
关键词
5G/重载铁路/信号远程监测/深度学习Key words
5G/heavy-haul railways/signaling remote monitoring/deep learning引用本文复制引用
出版年
2024
NETL
NSTL
万方数据