基于Azure边云结合在煤矿安全方向应用研究  

Research on application of edgecloud combination in coal mine safety based on Azure

作　　者：崔林林 权晓光 徐昊 仝依良 王晓彬 CUI Linlin;QUAN Xiaoguang;XU Hao;TONG Yiliang;WANG Xiaobin(Zhongyuan University of Technology,Zhengzhou 450007,China)

机构地区：[1]中原工学院,河南郑州450007

出　　处：《传感器与微系统》2024年第12期37-40,共4页Transducer and Microsystem Technologies

基　　金：中原工学院青年骨干教师资助项目(2021XQG06);2022年度河南省高等学校重点科研项目(22A460034);河南省自然科学基金指导性计划项目(242300420268);研究生科研创新计划项目(中原工学院科研培育基金)(12120016);研究生教育质量提升工程(中原工学院科研培育基金)(12120009)。

摘　　要：随着煤炭工业的发展和全球对能源安全与环境保护需求的增加,煤矿安全问题日益受到关注。传统的煤矿监测方法存在实时性、准确性和可靠性方面的挑战。本文引入云边结合计算技术,利用树莓派设备和Azure IoT Edge进行数据处理和实时分析,并将数据传输至Azure云平台进行监控和管理。通过温湿度传感器监测矿井内的温湿度信息,提出了一种适用于煤矿安全的云边结合计算架构。在边缘端采用卡尔曼滤波算法以减少环境干扰对数据的影响。实验结果表明:经过边缘端处理的信息能够成功上传至云端,实现数据可视化展示。With the development of the coal industry and the increasing demand for global energy security and environmental protection the safety of coal mines has attracted much attention.The traditional coal mine monitoring methods have challenges in real-time,accuracy and reliability.Cloud-edge combined computing technology is introduced,using Raspberry Pi device and the Azure IoT Edge for data processing and analysis in realtime,and transmit the data to the Azure cloud platform for monitoring and management.The temperature and humidity information in the mine is monitored by the temperature and humidity sensors,and a cloud-edge combination computing architecture suitable for coal mine safety is proposed.The Kalman filtering algorithm is used at the edge end to reduce the impact of environmental interference on the data.Experimental result verification shows that all the information processed by edge-end can successfully uploaded to the cloud end and the data is visualized.

关 键 词：边云结合 煤炭安全 AZURE 煤矿安全检测 准确性 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TD76[自动化与计算机技术—控制科学与工程]