基于物联网的铀矿山通风系统优化控制

Optimization Control of Ventilation System in Uranium Mine Based on Internet of Things

针对铀矿山放射性污染物治理需要,根据物联网技术的优良性能,结合铀矿山通风降氡机理,提出了一种基于物联网架构的铀矿山通风降氡监测控制系统,并构建了氡析出自适应神经模糊推理系统模型。通过实时监控及预警,对风机发布远程调控指令,改变井下风量、风压、风流以达到降氡目的。试验分析结果表明,该系统能较好实现铀矿山氡安全监测及控制。

Aiming at the governance needs of radioactive pollutants in uranium mines and according to the excellent performance of Internet of Things technology,combined with the mechanism of uranium mine ventilation and radon reduction,a uranium mine ventilation and radon reduction monitoring control system based on the Internet of Things architecture is proposed and the adaptive neuro-fuzzy inference system(ANFIS) model of radon exhalation is constructed.Through real-time monitoring and early warning,remote control commands are issued to mine fans to change the uranium mine air volume,wind pressure and wind flow to achieve the purpose of radon reduction.The experimental analysis results shows that the system can realize the safety monitoring and control of radon in uranium mine.