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数字孪生−应对智能化综采工作面技术挑战

葛世荣 王世博 管增伦 王雪松 安文龙 吕渊博 陈书航

葛世荣,王世博,管增伦,等. 数字孪生−应对智能化综采工作面技术挑战[J]. 工矿自动化,2022,48(7):1-12.  doi: 10.13272/j.issn.1671-251x.17959
引用本文: 葛世荣,王世博,管增伦,等. 数字孪生−应对智能化综采工作面技术挑战[J]. 工矿自动化,2022,48(7):1-12.  doi: 10.13272/j.issn.1671-251x.17959
GE Shirong, WANG Shibo, GUAN Zenglun, et al. Digital twin: meeting the technical challenges of intelligent fully mechanized working face[J]. Journal of Mine Automation,2022,48(7):1-12.  doi: 10.13272/j.issn.1671-251x.17959
Citation: GE Shirong, WANG Shibo, GUAN Zenglun, et al. Digital twin: meeting the technical challenges of intelligent fully mechanized working face[J]. Journal of Mine Automation,2022,48(7):1-12.  doi: 10.13272/j.issn.1671-251x.17959

数字孪生−应对智能化综采工作面技术挑战

doi: 10.13272/j.issn.1671-251x.17959
基金项目: 国家自然科学基金面上项目(51874279)。
详细信息
    作者简介:

    葛世荣(1963—),男,浙江天台人,中国工程院院士,教授,博士研究生导师,主要研究方向为智能矿山装备,E-mail:gesrcumt@126.com

    通讯作者:

    王世博(1979—),男,河北新河人,教授,博士,博士研究生导师,主要研究方向为智能矿山装备,E-mail:wangshb@cumt.edu.cn

  • 中图分类号: TD67

Digital twin: meeting the technical challenges of intelligent fully mechanized working face

  • 摘要: 基于智能化综采工作面目标任务−自主完成综采工作面可靠割煤、保持工作面几何关系、顶板可靠支护,提出了综采工作面智能控制关键技术,包括采煤机定位技术、工作面可视化技术、液压支架电液控制技术(装置)、工作面通信技术、综采装备协同控制技术、采煤机自动调高技术、工作面自动调直技术和工作面围岩支护控制技术(其中前3种技术属于智能化综采工作面的感知与执行层,工作面通信技术是智能化综采工作面的传输层,后4种技术属于智能化综采工作面的决策层)。指出智能化综采工作面面临的挑战为决策层的自主决策能力不能适应复杂多变的工况、感知与执行层不能支撑决策层的信息需求和决策指令的可靠执行。针对上述挑战问题,采用基于仿真的数字孪生建模方法,提出了综采工作面数字孪生系统架构。综采工作面数字孪生系统虚拟实体包括机理模型和行为模型,利用综采装备机理模型可获得综采装备物理系统的不可测数据,行为模型可为综采工作面智能控制系统提供反映物理装备运行状态的全息信息,解决决策层数据信息匮乏问题;综采装备机理模型与其控制系统组合的离线运行模式形成综采工作面硬件在环仿真系统,为基于工艺规则的智能控制算法提供测试平台;综采装备机理模型、行为模型与其控制系统组合的离线运行模式形成综采工作面计算实验系统,为综采工作面智能控制系统真正的自主决策复杂算法开发提供测试平台。

     

  • 图  1  综采工作面装备

    Figure  1.  Equipment on fully mechanized working face

    图  2  智能化综采工作面关键技术及其逻辑关系[25]

    Figure  2.  Key technologies of intelligent fully mechanized working face and their logical relationship[25]

    图  3  PLM概念设想[29]

    Figure  3.  Conceptual ideal for product lifecycle management(PLM)[29]

    图  4  数字模型、数字影子、数字孪生模式下物理实体和虚拟实体之间的数据流[34]

    Figure  4.  Data flow between physical entity and virtual entity in digital model, digital shadow and digital twin modes[34]

    图  5  数字孪生五维概念模型[52]

    Figure  5.  Five-dimensional conceptual model of digital twins[52]

    图  6  基于仿真的数字孪生原理及其应用[59]

    Figure  6.  Principle and application of simulation-based digital twin[59]

    图  7  综采工作面数字孪生系统架构

    Figure  7.  Digital twin system architecture of fully mechanized working face

    图  8  综采工作面虚拟实体离线运行模式

    Figure  8.  Off-line run mode of virtual entities of fully mechanized working face

  • [1] 王国法,范京道,徐亚军,等. 煤炭智能化开采关键技术创新进展与展望[J]. 工矿自动化,2018,44(2):5-12.

    WANG Guofa,FAN Jingdao,XU Yajun,et al. Innovation progress and prospect on key technologies of intelligent coal mining[J]. Industry and Mine Automation,2018,44(2):5-12.
    [2] 王国法,刘峰,孟祥军,等. 煤矿智能化(初级阶段)研究与实践[J]. 煤炭科学技术,2019,47(8):1-36.

    WANG Guofa,LIU Feng,MENG Xiangjun,et al. Research and practice on intelligent coal mine construction(primary stage)[J]. Coal Science and Technology,2019,47(8):1-36.
    [3] 王国法,庞义辉,任怀伟. 煤矿智能化开采模式与技术路径[J]. 采矿与岩层控制工程学报,2020,2(1):5-19.

    WANG Guofa,PANG Yihui,REN Huaiwei. Intelligent coal mining pattern and technological path[J]. Journal of Mining and Strata Control Engineering,2020,2(1):5-19.
    [4] 王国法,刘峰,庞义辉,等. 煤矿智能化−煤炭工业高质量发展的核心技术支撑[J]. 煤炭学报,2019,44(2):349-357.

    WANG Guofa,LIU Feng,PANG Yihui,et al. Coal mine intellectualization:the core technology of high quality development[J]. Journal of China Coal Society,2019,44(2):349-357.
    [5] 葛世荣. 煤矿智采工作面概念及系统架构研究[J]. 工矿自动化,2020,46(4):1-9.

    GE Shirong. Research on concept and system architecture of smart mining workface in coal mine[J]. Industry and Mine Automation,2020,46(4):1-9.
    [6] 葛世荣,郝尚清,张世洪,等. 我国智能化采煤技术现状及待突破关键技术[J]. 煤炭科学技术,2020,48(7):28-46.

    GE Shirong,HAO Shangqing,ZHANG Shihong,et al. Status of intelligent coal mining technology and potential key technologies in China[J]. Coal Science and Technology,2020,48(7):28-46.
    [7] T/CCS 002−2020 智能化采煤工作面分类、分级技术条件与评价指标体系[S].

    T/CCS 002-2020 Specification, classification and grading evaluation index for longwall face of smart coal mine[S].
    [8] 王国法,徐亚军,孟祥军,等. 智能化采煤工作面分类、分级评价指标体系[J]. 煤炭学报,2020,45(9):3033-3044.

    WANG Guofa,XU Yajun,MENG Xiangjun,et al. Specification,classification and grading evaluation index for smart longwall mining face[J]. Journal of China Coal Society,2020,45(9):3033-3044.
    [9] 李首滨. 智能化开采研究进展与发展趋势[J]. 煤炭科学技术,2019,47(10):102-110.

    LI Shoubin. Progress and development trend of intelligent mining technology[J]. Coal Science and Technology,2019,47(10):102-110.
    [10] 伍小杰,于月森,彭利明,等. 液压支架电液控技术的现状及展望[J]. 煤炭科学技术,2009,37(1):25-29. doi: 10.13199/j.cst.2009.01.59.wuxj.007

    WU Xiaojie,YU Yuesen,PENG Liming,et al. Present status and outlook of electric and hydraulic control technology for hydraulic powered support[J]. Coal Science and Technology,2009,37(1):25-29. doi: 10.13199/j.cst.2009.01.59.wuxj.007
    [11] 金静飞,王凯. 综采装备协同控制系统的设计[J]. 煤矿机械,2014,35(8):214-216.

    JIN Jingfei,WANG Kai. Design of coordinated control system of fully mechanized equipment[J]. Coal Mine Machinery,2014,35(8):214-216.
    [12] CZWALINNA J, KUBIK J, BIGBY D N, et al. New mechanization and automation of longwall and drivage equipment[R]. Luxembourg: Research Fund for Coal and Steel, 2011.
    [13] Interconnection of landmark compliant longwall mining equipment-shearer communication specification for OEM accessible inertial sensor data[R]. CSIRO Exploration and Mining Report, 2005.
    [14] 黄曾华. 煤矿综采工作面视频系统的应用研究[J]. 煤矿机电,2013(4):1-5.

    HUANG Zenghua. Application research on video system at fully mechanized mining field[J]. Colliery Mechanical & Electrical Technology,2013(4):1-5.
    [15] 葛世荣,苏忠水,李昂,等. 基于地理信息系统(GIS)的采煤机定位定姿技术研究[J]. 煤炭学报,2015,40(11):2503-2508.

    GE Shirong,SU Zhongshui,LI Ang,et al. Study on the positioning and orientation of a shearer based on geographic information system[J]. Journal of China Coal Society,2015,40(11):2503-2508.
    [16] REID D C, HAINSWORTH D W, RALSTON J C, et al. Longwall shearer guidance using inertial navigation (ACARP project C9015)[R]. CSIRO, Exploration and Mining Report 832F, 2001.
    [17] 王世佳,王世博,张博渊,等. 采煤机惯性导航定位动态零速修正技术[J]. 煤炭学报,2018,43(2):578-583.

    WANG Shijia,WANG Shibo,ZHANG Boyuan,et al. Dynamic zero-velocity update technology to shearer inertial navigation positioning[J]. Journal of China Coal Society,2018,43(2):578-583.
    [18] 孔维. 基于煤层地理信息系统的采煤机截割路径规划方法[D]. 徐州: 中国矿业大学, 2019.

    KONG Wei. Cutting path planning method of shearer based on coal seam geographic information system[D]. Xuzhou: China University of Mining and Technology, 2019.
    [19] LI Wei,LUO Chengming,YANG Hai,et al. Memory cutting of adjacent coal seams based on a hidden Markov model[J]. Arabian Jouranl of Geosciences,2014,7(12):5051-5060. doi: 10.1007/s12517-013-1145-5
    [20] WANG Shibo, WANG Shijia. Longwall mining automation horizon control: coal seam gradient identification using piecewise linear fitting[J/OL]. International Journal of Mining Science and Technology, 2022[2022-05-15]. https://doi.org/10.1016/j.ijmst.2022.02.003.
    [21] 王世博,何亚,王世佳,等. 刮板输送机调直方法与试验研究[J]. 煤炭学报,2017,42(11):3044-3050.

    WANG Shibo,HE Ya,WANG Shijia,et al. Study on the alignment method and experiment of scraper conveyor[J]. Journal of China Coal Society,2017,42(11):3044-3050.
    [22] 李森. 基于惯性导航的工作面直线度测控与定位技术[J]. 煤炭科学技术,2019,47(8):169-174.

    LI Sen. Measurement & control and localisation for fully-mechanized working face alignment based on inertial navigation[J]. Coal Science and Technology,2019,47(8):169-174.
    [23] 侯刚. 互联网+液压支架智能耦合控制系统设计与实现[J]. 煤矿开采,2017,22(1):105-108.

    HOU Gang. Intelligent coupling control system design and implementation of Internet and hydraulic support[J]. Coal Mining Technology,2017,22(1):105-108.
    [24] TRUEMAN R,LYMAN G,COCKER A. Longwall roof control through a fundamental understanding of shield-strata interaction[J]. International Journal of Rock Mechanics and Mining Sciences,2009,46:371-380. doi: 10.1016/j.ijrmms.2008.07.003
    [25] 王世博,葛世荣,王世佳,等. 长壁综采工作面无人自主开采发展路径与挑战[J]. 煤炭科学技术,2022,50(2):231-243.

    WANG Shibo,GE Shirong,WANG Shijia,et al. Development and chanllege of unmanned autonomous longwall fully-mechanized coal mining face[J]. Coal Science and Technology,2022,50(2):231-243.
    [26] 黄曾华,王峰,张守祥. 智能化采煤系统架构及关键技术研究[J]. 煤炭学报,2020,45(6):1959-1972.

    HUANG Zenghua,WANG Feng,ZHANG Shouxiang. Research on the architecture and key technologies of intelligent coal mining system[J]. Journal of China Coal Society,2020,45(6):1959-1972.
    [27] ZHAO Shuanfeng,WANG Pengfei,LI Shijun. Study on the fault diagnosis method of scraper conveyor gear under time-varying load condition[J]. Applied Sciences,2020,10(15):5053. doi: 10.3390/app10155053
    [28] GELERNTER D. Mirror worlds[M]. Oxford: Oxford University Press, 1991.
    [29] GRIEVES M. Product lifecycle management:the new paradigm for enterprises[J]. International Journal of Product Development,2005,2(1/2):71-84. doi: 10.1504/IJPD.2005.006669
    [30] 方志刚. 复杂装备系统数字孪生[M]. 北京: 机械工业出版社, 2021.

    FANG Zhigang. Digital twin of complex equipment system[M]. Beijing: China Machine Press, 2021.
    [31] GLAESSGEN E H, STARGEL D S. The digital twin paradigm for future NASA and US air force vehicles[C]//The 53rd AIAA/ASME/ASCE/AHS/ASC Structural Dynamics and Materials Conference: Special Session on the Digital Twin, Honolulu, 2012.
    [32] 陶飞,刘蔚然,刘检华,等. 数字孪生及其应用探索[J]. 计算机集成制造系统,2018,24(1):1-18.

    TAO Fei,LIU Weiran,LIU Jianhua,et al. Digital twin and its potential application exploration[J]. Computer Integrated Manufacturing Systems,2018,24(1):1-18.
    [33] 刘亚威. 面向飞行器结构健康管理的数字孪生及应用研究综述[J]. 测控技术,2022,41(1):1-10. doi: 10.19708/j.ckjs.2021.03.220

    LIU Yawei. Review on digital twin and its application research for aircraft structure health management[J]. Measurement & Control Technology,2022,41(1):1-10. doi: 10.19708/j.ckjs.2021.03.220
    [34] KRITZINGER W,KARNER M,TRAAR G,et al. Digital twin in manufacturing:a categorical literature review and classification[J]. IFAV PapersOnLine,2018,51(11):1016-1022. doi: 10.1016/j.ifacol.2018.08.474
    [35] 蔡武,陈果,朱志敏,等. 基于3D Max和Virtools的矿井虚拟仿真系统设计[J]. 煤炭工程,2011(1):111-113,116.

    CAI Wu,CHEN Guo,ZHU Zhimin,et al. Design of mine virtual simulation system based on 3D Max and Virtools[J]. Coal Engineering,2011(1):111-113,116.
    [36] 沙同震. 矿井虚拟仿真系统设计中3DMax和Virtools的应用[J]. 煤炭技术,2014,33(1):183-185.

    SHA Tongzhen. Application of 3DMax and Virtools in design of mine virtual simulation system[J]. Coal Technology,2014,33(1):183-185.
    [37] 王鹏,宿国瑞,贾宝山,等. 基于VR技术的虚拟矿井仿真平台建设[J]. 煤矿安全,2020,51(1):122-125.

    WANG Peng,SU Guorui,JIA Baoshan,et al. Construction of virtual mine simulation platform based on VR technology[J]. Safety in Coal Mines,2020,51(1):122-125.
    [38] 王学文,谢嘉成,郝尚清,等. 智能化综采工作面实时虚拟监测方法与关键技术[J]. 煤炭学报,2020,45(6):1984-1996.

    WANG Xuewen,XIE Jiacheng,HAO Shangqing,et al. Key technologies of real-time virtual monitoring method for an intelligent fully mechanized coal-mining face[J]. Journal of China Coal Society,2020,45(6):1984-1996.
    [39] BRANDTSTATEDER H, LUDWIG C, HÜBNER L, et al. Digital twins for large electric drive trains[C]//Petroleum and Chemical Industry Conference Europe, Antwerp, 2018: 1-5.
    [40] ZHANG Yong, BAI Jiangpo, LYU Kehong, et al. Key problems of virtual testability demonstration based on digital twin technology[C]//The 11th International Conference on Prognostics and System Health Management, Jinan, 2020.
    [41] WANG Jinjiang,YE Lunkuan,GAO R X,et al. Digital twin for rotating machinery fault diagnosis in smart manufacuturing[J]. International Journal of Production Research,2019,57(11/12):3920-3934.
    [42] FRAZZON E M,ALBRECHT A,HURTADO P A. Simulation-based optimization for the integrated scheduling of production and logistic systems[J]. IFAC-PapersOnline,2016,49(12):1050-1055. doi: 10.1016/j.ifacol.2016.07.581
    [43] JAIN S,CHOONG N F,AYE K M. Virtual factory:an integrated approach to manufacturing systems modeling[J]. International Journal of Operations & Production Management,2001,21(5/6):594-608.
    [44] 孙学民,刘世民,申兴旺,等. 数字孪生驱动的高精密产品智能化装配方法[J]. 计算机集成制造系统,2022,28(6):1704-1716.

    SUN Xuemin,LIU Shimin,SHEN Xingwang,et al. Digital twin-driven intelligent assembly method for high precision products[J]. Computer Integrated Manufacturing Systems,2022,28(6):1704-1716.
    [45] GUO Jinyan,YANG Zhaojun,CHEN Chuanhai,et al. Real-time prediction of remaining useful life and preventive maintenance strategy based on digital twin[J]. Journal of Computing and Information Science in Engineering,2021,21:031003-1. doi: 10.1115/1.4049153
    [46] LEE J,NI Jun,DJURDJANOVIC D,et al. Intelligent prognostics tools and e-maintenance[J]. Computers in Industry,2006,57(6):476-489. doi: 10.1016/j.compind.2006.02.014
    [47] TAO Fei,ZHANG Meng,LIU Yushan,et al. Digital twin driven prognostics and health management for complex equipment[J]. CIRP Annals-Manufacturing Technology,2018,67(1):169-172. doi: 10.1016/j.cirp.2018.04.055
    [48] ZHUANG Cunbo,LIU Jianhua,XIONG Hui. Digital twin-based smart production management and control framework for the complex product assembly shop-floor[J]. The International Journal of Advanced Manufacture Technology,2018,96(2):1149-1163.
    [49] SHAO Guodong,HELU M. Framework for a digital twin in manufacturing:scope and requirements[J]. Manufacturing Letters,2020,24:105-107. doi: 10.1016/j.mfglet.2020.04.004
    [50] REED S,LÖFSTRAND M,ANDREWS J. Modelling cycle for simulation digital twins[J]. Manufacturing Letters,2021,28:54-58. doi: 10.1016/j.mfglet.2021.04.004
    [51] 陶飞,马昕,胡天亮,等. 数字孪生标准体系[J]. 计算机集成制造系统,2019,25(10):2405-2418. doi: 10.13196/j.cims.2019.10.001

    TAO Fei,MA Xin,HU Tianliang,et al. Research on digital twin standard system[J]. Computer Integrated Manufacturing Systems,2019,25(10):2405-2418. doi: 10.13196/j.cims.2019.10.001
    [52] 陶飞,刘蔚然,张萌,等. 数字孪生五维模型及十大领域应用[J]. 计算机集成制造系统,2019,25(1):1-18.

    TAO Fei,LIU Weiran,ZHANG Meng,et al. Five-dimension digital twin model and its ten applications[J]. Computer Integrated Manufacturing Systems,2019,25(1):1-18.
    [53] 张霖,陆涵. 从建模仿真看数字孪生[J]. 系统仿真学报,2021,33(5):995-1007. doi: 10.16182/j.issn1004731x.joss.21-0262

    ZHANG Lin,LU Han. Discussing digital twin from of modeling and simulation[J]. Journal of System Simulation,2021,33(5):995-1007. doi: 10.16182/j.issn1004731x.joss.21-0262
    [54] TAO Fei, ZHANG Meng, NEE A Y C. Digital twin driven smart manufacturing[M/OL]. [2022-05-16]. https://www.sciencedirect.com/book/9780128176306/digital-twin-driven-smart-manufacturing#book-description.
    [55] STOJANOVIC N, MILENOVIC D. Data-driven digital twin approach for process optimization: an industry use case[C]//IEEE International Conference on Big Data, Seattle, 2018: 4202-4211.
    [56] CORADDU A,ONETO L,BALDI F,et al. Data-driven ship digital twin for estimating the speed loss caused by the marine fouling[J]. Ocean Engineering,2019,186:106063. doi: 10.1016/j.oceaneng.2019.05.045
    [57] PAN Yue,ZHANG Limao. A BIM-data mining integrated digital twin framework for advanced project management[J]. Automation in Construction,2021,124:103564. doi: 10.1016/j.autcon.2021.103564
    [58] WRIGHT L,DAVIDSON S. How to tell the difference between a model and a digital twin[J]. Advanced Modeling and Simulation in Engineering Sciences,2020,7(1):13. doi: 10.1186/s40323-020-00147-4
    [59] MARTÍNEZ G S, SIERLA S, KARHELA T, et al. Automatic generation of simulation-based digital twin of an industrial process plant[C]//The 44th Annual Conference of the IEEE Industrial Electronics Society, Washington, 2018.
    [60] 葛世荣,张帆,王世博,等. 数字孪生智采工作面技术架构研究[J]. 煤炭学报,2020,45(6):1925-1936. doi: 10.13225/j.cnki.jccs.ZN20.0327

    GE Shirong,ZHNAG Fan,WANG Shibo,et al. Digital twin for smart coal mining workface:technological frame and construction[J]. Journal of China Coal Society,2020,45(6):1925-1936. doi: 10.13225/j.cnki.jccs.ZN20.0327
    [61] 丁恩杰,俞啸,夏冰,等. 矿山信息化发展及以数字孪生为核心的智慧矿山关键技术[J]. 煤炭学报,2022,47(1):564-578. doi: 10.13225/j.cnki.jccs.yg21.1930

    DING Enjie,YU Xiao,XIA Bing,et al. Development of mine informatization and key technologies of intelligent mines[J]. Journal of China Coal Society,2022,47(1):564-578. doi: 10.13225/j.cnki.jccs.yg21.1930
    [62] 谢嘉成,王学文,杨兆建. 基于数字孪生的综采工作面生产系统设计与运行模式[J]. 计算机集成制造系统,2019,25(6):1381-1391. doi: 10.13196/j.cims.2019.06.007

    XIE Jiacheng,WANG Xuewen,YANG Zhaojian. Design and operation mode of production system of fully mechanized coal mining face based on digital twin theory[J]. Computer Integrated Manufacturing Systems,2019,25(6):1381-1391. doi: 10.13196/j.cims.2019.06.007
    [63] 张旭辉,张超,杨文娟,等. 数字孪生驱动采掘工作面远程控制技术分析及发展趋势[J]. 智能矿山,2020,1(1):112-124.

    ZHANG Xuhui,ZHANG Chao,YANG Wenjuan,et al. Current status analysis and development trend of remote control technology of digital twin-driven mining face[J]. Journal of Intelligent Mine,2020,1(1):112-124.
    [64] 张旭辉,张超,王妙云,等. 数字孪生驱动的悬臂式掘进机虚拟操控技术[J]. 计算机集成制造系统,2021,27(6):1617-1628. doi: 10.13196/j.cims.2021.06.008

    ZHANG Xuhui,ZHANG Chao,WANG Miaoyun,et al. Digital twin-driven virtual control technology of cantilever roadheader[J]. Computer Integrated Manufacturing Systems,2021,27(6):1617-1628. doi: 10.13196/j.cims.2021.06.008
    [65] 丁华,杨亮亮,杨兆建,等. 数字孪生与深度学习融合驱动的采煤机健康状态预测[J]. 中国机械工程,2020,31(7):815-823. doi: 10.3969/j.issn.1004-132X.2020.07.007

    DING Hua,YANG Liangliang,YANG Zhaojian,et al. Health prediction of shearers driven by digital twin and deep learning[J]. China Mechanical Engineering,2020,31(7):815-823. doi: 10.3969/j.issn.1004-132X.2020.07.007
    [66] 王世博,葛世荣,邹文才,等. 综采工作面半实物仿真系统技术架构[J]. 智能矿山,2020,1(1):125-131.

    WANG Shibo,GE Shirong,ZOU Wencai,et al. Hardware-in-the-loop simulation system of longwall mining face:technological frame and construction[J]. Journal of Intelligent Mine,2020,1(1):125-131.
    [67] 王飞跃,刘德荣,熊刚,等. 复杂系统的平行控制理论及应用[J]. 复杂系统与复杂性科学,2012,9(3):1-12. doi: 10.3969/j.issn.1672-3813.2012.03.001

    WANG Feiyue,LIU Derong,XIONG Gang,et al. Parallel control theory of complex systems and applications[J]. Complex Systems and Complexity Science,2012,9(3):1-12. doi: 10.3969/j.issn.1672-3813.2012.03.001
    [68] SCHLUSE M, ROSSMANN J. From simulation to experimentable digital twins: simulation-based development and operation of complex technical systems[C]//IEEE International Symposium on Systems Engineering, Edinburgh, 2016.
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  • 收稿日期:  2022-05-30
  • 修回日期:  2022-07-08
  • 网络出版日期:  2022-08-09

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