| 平行矿山:从数字孪生到矿山智能 |
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| 引用本文： | 陈龙, 王晓, 杨健健, 艾云峰, 田滨, 李宇宸, 滕思宇, 王健, 曹东璞, 葛世荣, 王飞跃. 平行矿山: 从数字孪生到矿山智能. 自动化学报, 2021, 47(7): 1633−1645 doi: 10.16383/j.aas.2021.y000001 |
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| 作者姓名： | 陈龙 王晓 杨健健 艾云峰 田滨 李宇宸 滕思宇 王健 曹东璞 葛世荣 王飞跃 |
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| 作者单位： | 1.中国科学院自动化研究所复杂系统管理与控制国家重点实验室 北京 100190 中国;;2.中山大学计算机学院 广州 510006 中国;;3.青岛慧拓智能机器有限公司 青岛 266109 中国;;4.青岛智能产业技术研究院 青岛 266109 中国;;5.中国矿业大学(北京) 北京 100083 中国;;6.中国科学院大学人工智能学院 北京 100049 中国;;7.吉林大学计算机科学与技术学院 长春 130012 中国;;8.滑铁卢大学机械与机电工程系 滑铁卢 ON N2L 3G1 加拿大 |
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| 基金项目： | 广东省重点领域研发计划(2020B090921003), 英特尔智能网联汽车大学合作研究中心项目(“ICRI-IACV”)资助 |
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| 摘 要： | 针对新时代下我国矿区智能化发展诉求与矿山无人化进程中遇到的复现难、协同难的技术问题,本文融合智慧矿山理念、ACP(Artificial societies+computational experiments+parallel execution)平行智能理论和新一代智能技术,设计并实现了智慧矿山操作系统(Intelli...
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| 关 键 词： | 无人矿山 平行矿山 平行智慧矿山框架 数字孪生 数字四胞胎 矿山智能 |
| 收稿时间： | 2020-11-08 |
Parallel Mining Operating Systems: From Digital Twins to Mining Intelligence |
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| Chen Long, Wang Xiao, Yang Jian-Jian, Ai Yun-Feng, Tian Bin, Li Yu-Chen, Teng Si-Yu, Wang Jian, Cao Dong-Pu, Ge Shi-Rong, Wang Fei-Yue. Parallel mining operating systems: From digital twins to mining intelligence. Acta Automatica Sinica, 2021, 47(7): 1633−1645 doi: 10.16383/j.aas.2021.y000001 |
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| Authors: | CHEN Long WANG Xiao YANG Jian-Jian AI Yun-Feng TIAN Bin LI Yu-Chen TENG Si-Yu WANG Jian CAO Dong-Pu Ge Shi-Rong WANG Fei-Yue |
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| Affiliation: | 1. State Key Laboratory for Management and Control of Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;;2. School of Data and Computer Science, Sun Yat-sen University, Guangzhou 510006, China;;3. Vehicle Intelligence Pioneers, Inc., Qingdao 266109, China;;4. Qingdao Academy of Intelligent Industries, Qingdao 266109, China;;5. China University of Mining and Technology−Beijing, Beijing 100083, China;;6. School of Artificial Intelligence, University of Chinese Academy of Sciences Beijing 100049, China;;7. College of Computer Science and Technology, Jilin University, Changchun 130012, China;;8. Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo ON N2L 3G1, Canada |
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| Abstract: | In view of the development of coal mine industries in China, the requests to unmanned mines are urgently and immediately. In this paper, the parallel management and control of mining operating infrastructure that integrates the smart mine theories, the ACP (artificial societies + computational experiments + parallel execution) based parallel intelligence approaches and the new generation of artificial intelligence (AI) technologies (including data fusion, knowledge graph, edge computing, etc.) is proposed. The intelligent mine operation system (IMOS) that realizes parallel mining is designed. This paper analyzes the development trends of open-pit coal mines industries, the stages of current researches on intelligentization of open-pit mines at home and abroad, and deeply integrates with digital quadruple theory to design the IMOS architecture. Besides, the IMOS subsystems are introduced in details, including: the single-vehicle operating subsystem, multi-vehicle collaboration subsystem, vehicle-road collaboration subsystem, unmanned intelligent subsystem, dispatch management subsystem, parallel management and control subsystem, supervisory subsystem, remote takeover subsystem and communication subsystem; and the key technologies in IMOS are discussed. The smart mine operating system presented in this paper is the first systemic integrative solution for unmanned and intelligent mine, which covered all scenarios in open-pit mine intelligence, and taking social development factors as the measurement for mining area sustainable development. |
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| Keywords: | Unmanned mines parallel mining parallel smart mine infrastructure digital twins digital quadruplets mining intelligence |
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