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作 者:翟庆龙 代存海 Zhai Qinglong;Dai Cunhai(Huafeng Coal Mine,Xinwen Mining Industry Group Co.,Ltd.,Tai'an 271413,China)
机构地区:[1]新汶矿业集团有限责任公司华丰煤矿,山东泰安271413
出 处:《山东煤炭科技》2025年第4期184-188,共5页Shandong Coal Science and Technology
摘 要:针对华丰煤矿监控精度低、实时性差和覆盖范围有限等安全监测难题,为提升安全管理水平,研究构建了一种基于物联网的煤矿安全监控系统。系统设计融合多传感器网络、无线通信技术以及云计算和大数据分析,实现对矿井内瓦斯浓度、CO浓度和粉尘浓度等环境参数的实时采集和远程传输,通过机器学习算法进行数据深度分析。系统可自动发出预警,提示矿井管理人员采取应急措施。实验表明,该监控系统显著提高了数据采集精度和响应速度,降低了潜在事故风险,为煤矿安全生产提供了有效支持。In response to the difficult problems of safety monitoring such as low monitoring accuracy,poor real-time performance,limited coverage area and others in Huafeng Coal Mine,a coal mine safety monitoring system based on Internet of Things is studied and constructed to improve safety management level.The system design integrates multisensor network,wireless communication technology,cloud computing,and big data analysis to achieve real-time collection and remote transmission of environmental parameters such as gas concentration,CO concentration,dust concentration and so on in the mine.In-depth data analysis is conducted through machine learning algorithms.The system can automatically issue early warnings,prompting mine management personnel to take emergency measures.The experiment shows that this monitoring system significantly improves data collection accuracy and response speed,reduces potential accident risks,and provides effective support for coal mine safety production.
分 类 号:TD76[矿业工程—矿井通风与安全]
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