李全生,刘举庆,李军,等. 矿山生态环境数字孪生:内涵、架构与关键技术[J]. 煤炭学报,2023,48(10):3859−3873. doi: 10.13225/j.cnki.jccs.2022.1850
引用本文: 李全生,刘举庆,李军,等. 矿山生态环境数字孪生:内涵、架构与关键技术[J]. 煤炭学报,2023,48(10):3859−3873. doi: 10.13225/j.cnki.jccs.2022.1850
LI Quansheng,LIU Juqing,LI Jun,et al. Digital twin of mine ecological environment: Connotation, framework and key technologies[J]. Journal of China Coal Society,2023,48(10):3859−3873. doi: 10.13225/j.cnki.jccs.2022.1850
Citation: LI Quansheng,LIU Juqing,LI Jun,et al. Digital twin of mine ecological environment: Connotation, framework and key technologies[J]. Journal of China Coal Society,2023,48(10):3859−3873. doi: 10.13225/j.cnki.jccs.2022.1850

矿山生态环境数字孪生:内涵、架构与关键技术

Digital twin of mine ecological environment: Connotation, framework and key technologies

  • 摘要: 在双碳国家战略和新一代信息技术广泛应用的时代背景下,体系化、精准化和智能化是矿山生态环境治理的重要发展方向。我国矿山生态环境治理长期以来开展了较为丰富的信息化建设,但仍然面临缺乏综合性监测体系、生态演变建模不准确、生态治理依赖专家经验、无信息化决策工具等问题。据此,提出了矿山生态环境数字孪生(Digital Twin of Mine Ecological Environment, DTME)的科学内涵,并介绍了其总体架构、功能特点与系统构建关键技术。定义了矿山生态环境数字孪生是以天−空−地多源监测、人工智能建模为基础,在虚拟空间建立与现实矿山生态环境要素一一对应、演变过程相互映射、作用机制相互匹配的孪生系统,进而通过方案优化或反馈控制支持矿山生态环境全过程科学治理。详细介绍了DTME的总体架构,包括物理矿山生态环境、监测终端、孪生数据、信息链路、云边端服务、虚拟矿山生态环境和控制终端7个组成部分。DTME以现实应用需求为导向,具有矿山生态质量动态监测与体检、生态演变模拟与影响因子解析、生态变化过程预测、生态风险预警、智能分级分区生态修复、生态修复效果评价和生态环境监管等功能。最后,归纳了构建矿山生态环境数字孪生系统涉及矿山生态数字底座搭建、矿山生态数字场景构建、矿山生态演变过程模拟与预测、矿山生态治理智能决策4方面关键技术。DTME的应用将支撑矿山生态全过程治理的感知、表达、监测、模拟、仿真、预测与控制,有望大幅提高治理质量和效率。

     

    Abstract: Under the background of dual-carbon national strategy and the widespread application of new-generation information technologies, systematization, precision, and intellectualization are the important development directions for the governance of mine ecological environment. Informatization of the governance of mine ecological environment in China has been carried out in a relatively rich and long-term way, but there are still problems such as lack of comprehensive monitoring system, inaccurate modeling of ecological evolution, ecological governance relying on expert experience, and no decision-making tools on informatization. Accordingly, in this study, the digital twin of mine ecological environment (DTME) is proposed, and its general framework, functional features and key technologies for system construction are introduced. The DTME is formally defined as a twin system of the physical mine ecosystem in virtual space by mapping three aspects: ecological elements, evolutionary processes, and impact mechanisms. The DTME utilizes spaceborne, airborne, and ground multi-source monitoring devices to dynamically detect the changes of ecological elements in the mine area, and constructs the complex driving models of the ecological evolution based on the artificial intelligence. The DTME supports the whole process of the scientific governance of mine ecological environment through program optimization or feedback control. Furthermore, the general framework of the DTME is introduced, including physical mine ecological environment (physical entity), monitoring terminal, twin data, information link, cloud-edge-terminal service, virtual mine ecological environment (virtual entity), and control terminal. Guided by real-life application requirements, the DTME can achieve mine ecological quality dynamic monitoring and health examination, mine ecological evolution simulation and impact factor analysis, prediction of mine ecological changes, mine ecological risk warning, intelligent grading and zoning of ecological restoration, mine ecological restoration effect evaluation, and mine ecological environment supervision. Finally, it is illustrated that the construction of the digital twin system of mine ecological environment involves four key technologies: digital base of mine ecosystem, digital scene of mine ecosystem, simulation and prediction of mine ecological evolution, and intelligent decision of mine ecological governance. The application of DTME can support the sensing, representation, monitoring, simulation, emulation, prediction, and control of the whole governance process of mine ecological environment, which is promising to significantly improve the quality and efficiency of governance.

     

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