锻压技术

航空锻造单元数字孪生系统构建及应用

英文标题：Construction and application of digital twin system for aviation forging cell

作者：彭宇升孙勇凌云汉

分类号：TP31

出版年,卷(期):页码：2022,47(4):51-61

摘要：

为了推动数字孪生技术在航空锻造领域的应用，促进航空锻造实现高质量、高效率和高一致性的智能化生产，通过分析和比较国内外相关机构和学者对数字孪生模型和智能制造架构的研究，从宏观的智能制造角度对数字孪生在制造领域的通用模型进行了总结和归纳。在此基础上，提出了基于数字孪生的智能航空锻造单元概念，并从内涵、特征以及组成部分3个角度对其展开论述，同时整理得到基于数字孪生的智能航空锻造单元的系统架构。最后，总结了面向航空锻造的数字孪生关键技术，并且结合实际需求，对数字孪生技术在航空锻造中的相关应用进行了探索，以期为数字孪生技术在航空锻造领域的工程应用提供参考。

In order to promote the application of digital twin technology in the field of aviation forging and promote the intelligent production of aviation forging with high quality, high efficiency and high consistency, by analyzing and comparing the research on digital twin model and intelligent manufacturing architecture by relevant institutions and scholars at home and abroad, the general model of digital twin in manufacturing field was summarized from the perspective of macro intelligent manufacturing. On this basis, the concept of intelligent aviation forging cell based on digital twin was proposed, and it was discussed from three perspectives of connotation, characteristics and components. At the same time, the system architecture of intelligent aviation forging cell based on digital twin was obtained. Finally, the key technologies of digital twin for aviation forging were summarized, and combined with the actual demand, the relavant application of digital twin technology in aviation forging was explored in order to provide reference for engineering application of digital twin technology in the aviation forging field.

基金项目：

作者简介：彭宇升（1997-），男，硕士研究生 E-mail：bitys@qq.com 通信作者：孙勇(1971-)，男，博士，研究员 E-mail：sun_yong_89@163.com

参考文献：

[1]张映锋, 张党, 任杉. 智能制造及其关键技术研究现状与趋势综述[J]. 机械科学与技术, 2019, 38(3): 329-338.

Zhang Y F, Zhang D, Ren S. Survey on current research and future trends of smart manufacturing and its key technologies[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(5):329-338.

[2]贺兴, 艾芊, 朱天怡, 等. 数字孪生在电力系统应用中的机遇和挑战[J]. 电网技术, 2020, 44(6): 2009-2019.

He X, Ai Q, Zhu T Y, et al. Opportunities and challenges of the digital twin in power system applications[J]. Power System Technology, 2020, 44(6):2009-2019.

[3]唐文虎, 陈星宇, 钱瞳, 等. 面向智慧能源系统的数字孪生技术及其应用[J]. 中国工程科学, 2020, 22(4): 74-85.

Tang W H, Chen X Y, Qian T, et al. Technologies and applications of digital twin for developing smart energy systems[J]. Strategic Study of CAE, 2020, 22(4):74-85.

[4]张帆, 葛世荣, 李闯. 智慧矿山数字孪生技术研究综述[J]. 煤炭科学技术, 2020, 48(7): 168-176.

Zhang F, Ge S R, Li C. Ｒesearch summary on digital twin technology for smart mines[J]. Coal Science and Technology, 2020, 48(7):168-176.

[5]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 F, Liu W R, Zhang M, et al. Five-dimension digital twin model and its ten applications[J]. Computer Integrated Manufacturing Systems, 2019, 25(1):1-18.

[6]刘青, 刘滨, 王冠, 等. 数字孪生的模型、问题与进展研究[J]. 河北科技大学学报, 2019, 40(1): 68-78.

Liu Q, Liu B, Wang G, et al. Research on digital twin: Model, problem and progress[J]. Journal of Hebei University of Science and Technology, 2019, 40(1):68-78.

[7]Grieves M, Vickers J. Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems[M]. Berlin, Germany: Springer, Cham, 2017.

[8]Grieves M. Digital twin: Manufacturing excellence through virtual factory replication[EB/OL]. https://www.researchgate.net/publication/275211047_Digital_Twin_Manufacturing_Excellence_through_Virtual_Factory_Replication, 2015.

[9]赵敏. 基于RAMI 4.0解读新一代智能制造[J]. 中国工程科学, 2018, 20(4): 90-96.

Zhao M. Understanding of a new generation of intelligent manufacturing based on RAMI 4.0[J]. Strategic Study of CAE, 2018, 20(4):90-96.

[10]姚锡凡, 景轩, 张剑铭, 等. 走向新工业革命的智能制造[J]. 计算机集成制造系统, 2020, 26(9): 2299-2320.

Yao X F, Jing X, Zhang J M, et al. Towards smart manufacturing for new industrial revolution[J]. Computer Integrated Manufacturing Systems, 2020, 26(9):2299-2320.

[11]陶飞, 张贺, 戚庆林, 等. 数字孪生模型构建理论及应用[J]. 计算机集成制造系统, 2021, 27(1): 1-15.

Tao F, Zhang H, Qi Q L, et al. Theory of digital twin modeling and its application[J]. Computer Integrated Manufacturing Systems, 2021, 27(1):1-15.

[12]陶飞, 戚庆林, 王力翚, 等. 数字孪生与信息物理系统——比较与联系[J]. Engineering, 2019, 5(4): 132-149.

Tao F, Qi Q L, Wang L H, et al. Digital twins and cyber-physical systems toward smart manufacturing and industry 4.0: Correlation and comparison[J]. Engineering, 2019, 5(4):132-149.

[13]周济, 李培根, 周艳红, 等. 走向新一代智能制造[J]. Engineering, 2018, 4(1): 28-47.

Zhou J, Li P G, Zhou Y H, et al. Toward new-generation intelligent manufacturing[J]. Engineering, 2018, 4(1):28-47.

[14]刘强. 智能制造理论体系架构研究[J]. 中国机械工程, 2020, 31(1): 24-36.

Liu Q. Study on architecture of intelligent manufacturing theory[J]. China Mechanical Engineering, 2020, 31(1):24-36.

[15]陶飞, 戚庆林. 面向服务的智能制造[J]. 机械工程学报, 2018, 54(16): 11-23.

Tao F, Qi Q L. Service-oriented smart manufacturing[J]. Journal of Mechanical Engineering, 2018, 54(16):11-23.

[16]中国电子技术标准化研究院.信息物理系统白皮书[EB/OL]. http://www.cesi.cn/201703/2251.html,2017.

China Electron-ics Standardization Institute. White paper: Cyber-physical system[EB/OL]. http://www.cesi.cn/201703/2251. html, 2017.

[17]邹萍, 张华, 马凯蒂, 等. 面向边缘计算的制造资源感知接入与智能网关技术研究[J]. 计算机集成制造系统, 2020, 26(1): 40-48.

Zou P, Zhang H, Ma K D,et al. Perception and access of manufacturing resources and intelligent gateway technology for edge computing[J]. Computer Integrated Manufacturing Systems, 2020, 26(1):40-48.

[18]刘大同, 郭凯, 王本宽, 等. 数字孪生技术综述与展望[J]. 仪器仪表学报, 2018, 39(11): 1-10.

Liu D T, Guo K, Wang B K, et al. Summary and perspective survey on digital twin technology[J]. Chinese Journal of Scientific Instrument, 2018, 39(11):1-10.

[19]杨帆, 吴涛, 廖瑞金, 等. 数字孪生在电力装备领域中的应用与实现方法[J]. 高电压技术, 2021, 47(5): 1505-1521.

Yang F, Wu T, Liao R J, et al. Application and implementation method of digital twin in electric equipment[J]. High Voltage Engineering, 2021, 47(5):1505-1521.

[20]赵浩然, 刘检华, 熊辉, 等. 面向数字孪生车间的三维可视化实时监控方法[J]. 计算机集成制造系统, 2019, 25(6): 1432-1443.

Zhao H R, Liu J H, Xiong H, et al. 3D visualization real-time monitoring method for digital twin workshop[J]. Computer Integrated Manufacturing Systems, 2019, 25(6):1432-1443.

[21]郑守国, 张勇德, 谢文添, 等. 基于数字孪生的飞机总装生产线建模[J]. 浙江大学学报：工学版, 2021, 55(5): 843-854.

Zheng S G, Zhang Y D, Xie W T, et al. Aircraft final assembly line modeling based on digital twin[J]. Journal of Zhejiang University：Engineering Science, 2021, 55(5):843-854.

[22]郭具涛, 洪海波, 钟珂珂, 等. 基于数字孪生的航天制造车间生产管控方法[J]. 中国机械工程, 2020, 31(7): 808-814.

Guo J T, Hong H B, Zhong K K, et al. Production management and control method of aerospace manufacturing workshops based on digital twin[J]. China Mechanical Engineering, 2020, 31(7):808-814.

[23]王安邦, 孙文彬, 段国林. 基于数字孪生与深度学习技术的制造加工设备智能化方法研究[J]. 工程设计学报, 2019, 26(6): 666-674.

Wang A B, Sun W B, Duan G L. Research on intelligent method of manufacturing and processing equipment based on digital twin and deep learning technology[J]. Chinese Journal of Engineering Design, 2019, 26(6):666-674.

[24]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 F, Liu W R, Liu J H, et al. Digital twin and its potential application exploration[J]. Computer Integrated Manufacturing Systems, 2018, 24(1):1-18.

服务与反馈：

【本网站尚未开通全文下载服务】【加入收藏】