摘要
煤矿企业的安全管理长期以来是煤矿管理工作中的重中之重。通过环境监测设备、设备管理系统、人员管理系统等对煤矿数据进行梳理,但各系统之间独立运行,存在数据异构、预控能力不足、人工数据处理能力有限等问题。基于数据挖掘技术,结合安全管理、系统工程以及数据挖掘等理论和方法,对煤矿安全管理系统现状进行深入分析,研究并设计了以数据挖掘为技术支撑的煤矿安全管理平台的大数据模型、功能框架、技术框架;基于数据挖掘的煤矿安全管理大数据平台能够有效的提高煤矿企业的风险防控能力和决策效率。
The safety management of coal mine enterprises has long been the top priority in coal mine management.Coal mining enterprises store and sort out all kinds of data by investing in environmental monitoring equipment,equipment management system,personnel management system and other systems.However,there are still great limitations,such as independent operation between systems,heterogeneous data,insufficient pre-control ability,limited manual data processing ability and so on.The purpose of this study is to deeply analyze the current situation of coal mine safety management system by using data mining technology,combined with the theories and methods of safety management,system engineering and data mining.The result is that the big data model,functional framework and technical framework of coal mine safety management platform supported by data mining are studied and designed.The conclusion is that the value of this platform can effectively improve the risk prevention and control ability and decision-making efficiency of coal mining enterprises.
作者
高晶
赵良君
吕旭阳
GAO Jing;ZHAO Liangjun;LYU Xuyang(North China University of Science and Technology,Tangshan 063210,China)
出处
《煤矿安全》
CAS
北大核心
2022年第6期121-125,共5页
Safety in Coal Mines
基金
河北省社科基金资助项目(HB18YJ065)。
