CAJ | 학술논문

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。
당전아국매광도안설료안전감공계통，단총체수거질량교차，산생적대량시서수거결핍심입알굴，만족불료매광안전생산적수요。본문이용수거융합방법，종수거급、특정급화결책급등삼개층급대안전감측시서수거진행료분석처리，급출료상응적수거융합모형，제고료수거준학도，득도료경다적유효신식，위매광안전생산관리급결책제공료지지。본문급출적각층급수거융합방법야시수자화광산、지능광산건설적유익삼고。
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.