基于OLAP的煤矿通风数据分析研究  

Analysis of coal mine ventilation data based on OLAP

作　　者：石晋松 王鹏军 李向阳 程方 杨晋波 Shi Jinsong;Wang Pengjun;Li Xiangyang;Cheng Fang;Yang Jinbo(Shanxi Yamei Daning Energy Co.,Ltd.,Jincheng 048000,China)

机构地区：[1]山西亚美大宁能源有限公司,山西晋城048000

出　　处：《煤炭与化工》2024年第8期116-121,共6页Coal and Chemical Industry

摘　　要：矿井通风系统数据量庞大复杂,简单的统计形式及分析方法很难有效利用隐含信息对通风系统进行安全管理。本文首先提出了基于OLAP的煤矿通风系统数据分析方法,引入OLAP机制对煤矿通风数据进行管理,建立了通风系统数据管理模型,然后将OLAP与CNN有机融合,提出了基于OLAP的通风系统数据预测模型,最后通过大宁矿通风机风量预测加以实证分析,验证了模型的有效性和准确度,实现了大数据情境下煤矿通风系统数据的高效管理,提高了矿井通风系统管理水平。The data volume of mine ventilation system is huge and complex,and it is difficult to effectively use implicit information to manage the safety of ventilation system by simple statistical forms and analysis methods.Firstly,this paper proposes a data analysis method of coal mine ventilation system based on OLAP,introduces OLAP mechanism to manage coal mine ventilation data,and establishes a data management model of ventilation system.Then,OLAP and CNN are organically integrated,and a data prediction model of ventilation system based on OLAP is proposed.Finally,the validity and accuracy of the model are verified by the empirical analysis of the air volume prediction of the ventilator in Daning Coal Mine,which realizes the efficient management of coal mine ventilation system data in the context of big data and improves the management level of mine ventilation system.

关 键 词：煤矿通风 OLAP 神经网络 数据分析 

分 类 号：TD712[矿业工程—矿井通风与安全]