摘要
为加强煤矿企业对较、重大风险重点管控,以风险分级管控与隐患排查治理的双重预防机制为研究对象,基于B/S(Browser/Server)模式,采用.NET设计框架,使用C Sharp语言开发煤矿安全风险分级管控与隐患排查治理的双重预防管理系统。对煤矿进行风险管理时,结合企业风险库中重大、较大、一般、低风险对应红、橙、黄、蓝四色图生成全矿井的风险四色图,并以2D GIS地图展示全矿风险分布情况及具体风险管控闭环情况。实际验证通过双重预防管理系统,能够使煤矿风险与隐患管理系统化、规范化,减少或避免煤矿事故发生。该系统在贵州盘江股份有限公司多个煤矿进行了较好地应用,为煤矿的风险与隐患管理工作提供了一种新的思路与方法,促使煤矿生产向科学化、数字化、可视化的方向发展。
In order to strengthen the key management and control of major risks for coal mine enterprises,this paper takes the dual prevention mechanism of risk classification management and control and hidden danger investigation and management as the research object.Based on the B/S(Browser/Server)model,using the.NET design framework,and using the C Sharp language to develop a dual prevention and management system for coal mine safety risk classification control and hidden danger investigation and governance.In the risk management of coal mines,the risk four-color map of the whole mine is generated by combining the red,orange,yellow and blue four-color maps corresponding to major,large,general and low risks in the enterprise risk database,and the 2D GIS map is used to show the risk distribution of the whole mine and the closed-loop situation of specific risk control.The actual verification:through the dual prevention management system,can be systematic and standardized coal mine risk and hidden danger management,reduce or avoid coal mine accidents.The system has been well applied in many mines of Guizhou Panjiang Co.,Ltd.,which provides a new idea and method for the risk and hidden danger management of coal mines,and promotes the scientific,digital and visual development of coal mine production.
作者
于世雷
冯黎莉
孙康
YU Shilei;FENG Lili;SUN Kang(China Coal Technology and Engineering Group Changzhou Research Institute Co. , Ltd. , Changzhou 213015,China;Tiandi (Changzhou) Automation Co. , Ltd. , Changzhou 213015,China)
出处
《陕西煤炭》
2022年第4期142-146,共5页
Shaanxi Coal
基金
中煤科工集团常州研究院有限公司科技创新重点项目(2020GY001-3)。
关键词
煤矿安全
风险分级管控
隐患排查治理
风险辨识
可视化
coal mine safety
risk classification control
hidden danger investigation and management
risk identification
visualization