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基于5G的重载铁路信号远程监测系统设计

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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.
Design of Remote Monitoring System for Heavy duty Railway Signal Based on 5G
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.

5Gheavy-haul railwayssignaling remote monitoringdeep learning

刘立辉

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国能朔黄铁路发展有限责任公司肃宁分公司,河北 沧州 062356

5G 重载铁路 信号远程监测 深度学习

2024

通信电源技术
武汉普天通信设备集团有限公司

通信电源技术

影响因子:0.389
ISSN:1009-3664
年,卷(期):2024.41(24)