基于5G的火力发电厂电气设备故障预警系统设计  

Design of Electrical Equipment Fault Warning System in Thermal Power Plant Based on 5G Communication Technology

作　　者：鞠文斐 邵财原 龙淼 JU Wenfei;SHAO Caiyuan;LONG Miao(Shantou Huadian Power Generation Co.,Ltd.,Shantou 515132,China)

机构地区：[1]汕头华电发电有限公司,广东汕头515132

出　　处：《通信电源技术》2024年第22期31-33,共3页Telecom Power Technology

摘　　要：针对火力发电厂电气设备故障频发的问题,提出一种基于5G的故障预警系统。该系统采用3层架构设计,综合运用卷积神经网络、长短期记忆网络等算法,实现了设备运行数据的实时采集、智能诊断与预警。通过在某火电厂的实测,系统在典型设备上的故障诊断准确率均超95.0%,响应时延低至102 ms,为设备安全运行提供了可靠保障。Aiming at the frequent faults of electrical equipment in thermal power plants,this paper proposes a fault early warning system based on 5G.The system adopts three-layer architecture design,and comprehensively uses convolution neural network,long-term and short-term memory network and other algorithms to realize real-time collection,intelligent diagnosis and early warning of equipment operation data.Through the actual measurement in a thermal power plant,the fault diagnosis accuracy of the system on typical equipment is over 95.0%,and the response time delay is as low as 102 ms,which provides a reliable guarantee for the safe operation of equipment.

关 键 词：火力发电厂 5G 深度学习 

分 类 号：TN929.5[电子电信—通信与信息系统]