摘要
为了实现对电力隧道的状态监测,提升消防安全管理能力,设计了基于NB-IoT技术的智慧消防在线监控系统。该系统以STM32L431单片机为主控CPU,靠传感器采集信息,通过NB-IoT和LoRa模块将数据传输到云平台进行数据处理,并运用粒子群算法(Particle Swarm Optimization,PSO)优化误差反向传播算法(Error Back Propagation,BP)的参数得到PSO-BP模型,能对隧道的异常状态及时预警。仿真实验表明,本文方法火灾预警的最短响应时间为0.3 s,火情响应效率高,能监测到隧道内的环境指标触发报警装置,具有一定的现实意义。
In order to realize the status monitoring of the power tunnel and improve the ability of fire safety management,the research designed an intelligent fire online monitoring system based on NB-IoT technology.The system uses STM32L431 single chip microcomputer as the main control CPU,relies on sensors to collect information,and transmits data to the cloud platform through NB-IoT and LoRa modules for data processing,and uses particle swarm optimization(PSO)algorithm optimizes the parameters of error back propagation(BP)to obtain the PSO-BP model,which can timely warn the abnormal state of the tunnel.A large number of simulation experiments show that the shortest response time of the proposed method is 0.3 s,the fire response efficiency is high,and the environmental indicators in the tunnel can be monitored to trigger the alarm device,which has certain practical significance.
作者
张源
ZHANG Yuan(State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing Power Supply Company,Nanjing,Jiangsu 210019,China)
出处
《计算技术与自动化》
2025年第4期184-189,共6页
Computing Technology and Automation
