摘要
当前我国煤矿都安设了安全监控系统,但总体数据质量较差,产生的大量时序数据缺乏深入挖掘,满足不了煤矿安全生产的需要。本文利用数据融合方法,从数据级、特征级和决策级等三个层级对安全监测时序数据进行了分析处理,给出了相应的数据融合模型,提高了数据准确度,得到了更多的有效信息,为煤矿安全生产管理及决策提供了支持。本文给出的各层级数据融合方法也是数字化矿山、智能矿山建设的有益参考。
Safety monitoring system is currently installed in coal mine in China, but the quality of data which generates is mostly poor. A large number of time series data generated by the system lacks of deep mining, which cannot meet the needs of coal mine safety production. In this paper, safety monitoring series data are analyzed and processed by using the data fusion method which includes three level from the data level, feature level to decision level, and corresponding data fusion models are given, which improved data accuracy and gotten more effective infor-mation, providing the support for the management and decision-making of safety production in coal mine. All levels of data fusion method which is presented in this paper are also useful reference for the intelligent digital mine construction.
出处
《煤矿现代化》
2015年第6期67-69,共3页
Coal Mine Modernization
基金
陕西省科技计划经费资助项目(2013K11-20)
陕西省教育厅科研计划项目资助(2013JK0868)
中国博士后基金资助项目(2013M542366)
关键词
信息融合
时序数据
预警
监控系统
data fusion
series data
early warning
monitoring system
