煤矿水文灾害预警的大数据平台系统  

Big data platform system for coal mine hydrological disaster early warning

作　　者：刘若涵 李春静 Liu Ruohan;Li Chunjing(School of Electric&Information Engineering,Heilongjiang University of Science&Technology,Harbin 150022,China;Xin Heilongjiang Lianhua Information Co.Ltd.,Harbin 150090,China)

机构地区：[1]黑龙江科技大学电子与信息工程学院,哈尔滨150022 [2]黑龙江鑫联华信息股份有限公司,哈尔滨150090

出　　处：《黑龙江科技大学学报》2018年第6期702-705,717,共5页Journal of Heilongjiang University of Science And Technology

摘　　要：为评价煤矿水害的危险程度,提高煤矿应对水害的能力,应用大数据技术,通过分析煤矿水文相关数据的多源异构性,数据价值的稀疏性、不确定性,以Hadoop平台为基础构建煤矿水文灾害预警的大数据平台,通过主成分分析方法消除冗余的影响因素,根据监控数据、预兆性数据以小波神经网络和灰色预神经网络预警煤矿水文灾害。结果表明:以黑龙江某煤矿实际数据为例,Hadoop平台通过小波神经网络和灰色神经网络能够准确预测水文灾害的趋势。该研究对提高煤矿水文灾害预警的水平具有重要的参考。This paper is directed at evaluate the degree of danger of coal mine water disasters and improving the ability to cope with them.The study involves developing the big data platform designed for coal mine hydrology disaster warning by applying the big data technology,analyzing the multiple source of coal mine hydrology data heterogeneity and the data of the value of sparse,uncertainty,and drawing on the Hadoop platform;eliminating the influence factors of redundancy using the principal component analysis method;and providing an earlier warning of the disasters in coal mines according to the monitoring data and the warning data and through the wavelet neural network,and the grey prediction neural network.The results show that Hadoop platform building on wavelet neural network and gray neural network could enable an accurate prediction of the trend of hydrological disasters,as is shown by the available data from a mine in Heilongjiang province.This study could serve as a reference for improving the level of hydrological disaster warning in coal mines.

关 键 词：煤矿 水文灾害 大数据 HADOOP 预警 

分 类 号：TD742[矿业工程—矿井通风与安全]