摘要
针对煤矿物联网状态监测系统存在网络延迟、煤矿设备状态数据缺少真实性和时效性导致预警不及时的问题,运用多项式拟合和牛顿插值算法建立了延迟补偿预警算法,同时设计了基于物联网的煤矿井下状态监测系统结构,开发了嵌入式设备端和Web端人机交互界面。实验结果表明,经算法处理后Web端得到的温湿度拟合曲线更接近于实际的温湿度曲线,手机APP端平均预警时间提前0.8 s。
Aiming at the problems of network delay in the coal mine internet of things condition monitoring system,being lack of authenticity and timeliness of equipment status data,and untimely warning,a delay compensation early warning algorithm was established using polynomial fitting and Newton interpolation algorithm.At the same time,the design of the underground mine condition monitoring system structure based on the internet of things was developed,and the human-machine interaction interfaces of the embedded device terminal and the Web terminal were developed.The experimental results show that the temperature and humidity fitting curve obtained by the Web terminal after the algorithm processing is closer to the actual temperature and humidity curve,and the average early warning time of the mobile APP terminal is 0.8 s earlier.
作者
冯鹏辉
武利生
Feng Penghui;Wu Lisheng(College of Mechanical Engineering and Vehicle Engineering,Taiyuan University of Technology,Taiyuan 030024,China)
出处
《煤矿机械》
北大核心
2020年第3期190-193,共4页
Coal Mine Machinery
基金
国家自然科学基金项目(51675364)。
关键词
物联网
延迟补偿预警算法
牛顿插值多项式
多项式拟合
internet of things
delay compensation early warning algorithm
Newton interpolation polynomial
polynomial fitting
