2025 scenarios and development path of intelligent coal mine
WANG Guofa1,2,3 ,WANG Hong2 ,REN Huaiwei1,3 ,ZHAO Guorui1,3 ,PANG Yihui3 , DU Yibo1,3 ,ZHANG Jinhu1,3 ,HOU Gang1,3
智慧矿山是煤炭行业转变发展方式、提升行业发展质量的核心驱动力,是矿山技术发展的最高形式。基于数字矿山技术发展现状,结合生产系统智慧化特征及要求,给出了智慧矿山概念及内涵:将物联网、云计算、大数据、人工智能、自动控制、移动互联网、机器人化装备等与现代矿山开发技术融合,形成矿山感知、互联、分析、自学习、预测、决策、控制的完整智能系统;到2025年,实现煤矿单个系统智能化向多系统智慧化方向发展,建立智慧生产、智慧安全及智慧保障系统的基本运行框架,初步形成空间数字化、信息集成化、设备互联化、虚实一体化和控制网络化的智慧煤矿第二阶段目标。实现矿井开拓、采掘、运通、洗选、安全保障、生态保护、生产管理等全过程智能化运行。资源开发利用水平显著提高,煤矿职业健康和工作环境根本改善,矿山生态恢复和保护全面实施。
The intelligent mine is the core driving force for the coal industry to change the way of development and to improve the quality of the industry. It is the highest form of the development of coal mine technology. Based on the de- velopment of mining technology and combined with intelligent generation system with characteristics and requirements, the concept and interconnection of the wisdom of mine are given. Based on digital mine,networking,cloud computing, big data,artificial intelligence and modern mining technology as the core technology,it will achieve the wisdom of self- learning,prediction,decision,control of the whole intelligent system. By 2025,the intelligent system will run from sin- gle system to multi-system intelligent level,the basic operating framework of wisdom production,wisdom security and wisdom guarantee system will be established. The spatial digitization,integration of information,internet,virtual equip- ment integration and control network will be formed initially as the goal of intelligent coal mine for the second stage. It will realize the intelligent operation of coal mine development,mining,transportation,washing,safety,ecological protec- tion,production management and so on. The level of exploitation and utilization of resources will be greatly improved,the occupational health and working environment of coal mines will be fundamentally improved,and the ecological res- toration and protection of mines will be fully implemented.
intelligent coal mine;digital mine;scene target;large data;artificial intelligence
主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会