基于数字孪生的飞机总装生产线建模

doi:10.3785/j.issn.1008-973X.2021.05.005

浙江大学学报(工学版)

2021, Vol. 55

Issue (5): 843-854 DOI: 10.3785/j.issn.1008-973X.2021.05.005

机械工程

基于数字孪生的飞机总装生产线建模

郑守国1(

),张勇德2,谢文添1,樊虎2,王青1,*(

)

1. 浙江大学机械工程学院浙江省先进制造技术重点实验室，浙江杭州 310027
2. 西安飞机工业（集团）有限责任公司，陕西西安 710089

Aircraft final assembly line modeling based on digital twin

Shou-guo ZHENG1(

),Yong-de ZHANG2,Wen-tian XIE1,Hu FAN2,Qing WANG1,*(

)

1. Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, College of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
2. Xi’an Aircraft Industrial (Group) Co. Ltd, Xi’an 710089, China

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摘要：

为了实现飞机制造企业总装生产线车间物理空间与信息空间的实时交互与深度融合，通过分析飞机总装生产线组成单元与生产业务逻辑，提出基于数字孪生的飞机总装生产线车间建模框架. 从“人、机、料、法、环、测”六维视角出发，阐述生产线关键要素建模与实现，并提出飞机总装生产线三维可视化及信息集成平台实现技术流程. 在CATIA中建立车间三维数字模型，基于浏览器和WebGL技术建立虚拟空间，通过采集生产现场过程数据实现物理实体向虚拟空间的实时映射. 以某型飞机总装生产线车间为例，实现总装现场与虚拟可视化的同步映射、WebServices服务、信息查询服务及装配工艺过程查询服务，有效提高作业效率并为工作人员决策提供科学参考.

关键词： 飞机总装生产线; 信息物理融合; 数字孪生技术; WebGL; 虚实映射

Abstract:

The components of the aircraft assembly line and the business logic were analyzed, and a digital twin based modeling framework for the aircraft assembly line was proposed, in order to realize the real-time interaction and deep integration of physical space and information space in the final assembly line of aircraft manufacturers. The modeling and the implementation of the key elements of assembly line were elaborated from the six-dimensional perspective of “human, machine, material, method, environment, and measurement”. Correspondingly, the technical process of the three-dimensional visualization and the information integration platform of the aircraft assembly line was proposed. A three-dimensional digital model of the workshop was established in CATIA. Then, a virtual space was built up based on the browser-based framework and WebGL technology and the real-time mapping of physical entities to virtual space was achieved by collecting process data from the shop-floor. An aircraft final assembly line was taken as an example, the synchronous mapping between the assembly workshop and virtual visualization, webServices service and information query service were realized, which improves the assembly efficiency and can provide scientific references for manual decision.

Key words: aircraft final assembly cyber-physical fusion digital twin technology WebGL virtual-real mapping

收稿日期: 2020-08-13 出版日期: 2021-06-10

CLC:

TP 391

基金资助: 国家重点研发计划资助项目（2019YFB1707501）；国家自然科学基金资助项目（51975520）

通讯作者: 王青 E-mail: sgzheng@zju.edu.cn;wqing@zju.edu.cn

作者简介: 郑守国（1989—），硕士，工程师，从事飞机数字化装配系统集成及相关方向研究. orcid.org/0000-0002-1145-1267.E-mail： sgzheng@zju.edu.cn

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引用本文:

郑守国,张勇德,谢文添,樊虎,王青. 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.

Shou-guo ZHENG,Yong-de ZHANG,Wen-tian XIE,Hu FAN,Qing WANG. Aircraft final assembly line modeling based on digital twin. Journal of ZheJiang University (Engineering Science), 2021, 55(5): 843-854.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2021.05.005 或 http://www.zjujournals.com/eng/CN/Y2021/V55/I5/843

图 1 飞机总装生产线业务逻辑图

图 2 基于数字孪生的飞机总装生产线建模框架

图 3 6要素关联关系

图 4 单元信息采集网络拓扑图

图 5 数据库操作流程图

图 6 飞机总装生产线三维可视化及信息集成平台技术流程图

图 7 某型飞机总装生产线三维场景展示图

表 1 不同装配阶段装配环境要求和装配对象状态的变化

图 8 MES系统文件操作界面

图 9 现场设备端文件操作界面

图 10 FP1的实时数据

图 11 FP1的历史数据

图 12 FP1的故障信息查询

1	范玉清, 梅中义, 陶剑. 大型飞机数字化制造工程[M]. 北京: 航空工业出版社, 2011: 804-891. FAN Yu-qing, MEI Zhong-yi, TAO Jian. Large aircraft digital manufacturing engineering [M]. Beijing: Aviation Industry Press, 2011: 804-891.
2	杜品圣智能工厂: 德国推进工业4.0战略的第一步(下)[J]. 自动化博览, 2014, (2): 50- 55 DU Pin-sheng Intelligent factory: the first step of germany's industrial 4.0 strategy (last of two volumes)[J]. Automation Panorama, 2014, (2): 50- 55 doi: 10.3969/j.issn.1003-0492.2014.02.032
3	LEEE A. Cyber physical systems: design challenges [C]// Proceedings of the 11th IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC 2008). Orlando: IEEE Computer Society, 2008: 363-369.
4	RAJKUMAR R R, LEE I, SHA L, et al. Cyber-physical systems: the next computing revolution [C]// Proceedings of the 47th Design Automation Conference. Anaheim: ACM, 2010: 731-736.
5	TAO F, CHENG Y, XU L, et al CCIoT-CMfg: cloud computing and internet of things-based cloud manufacturing service system[J]. IEEE Transactions on Industrial Informatics, 2014, 10 (2): 1435- 1442 doi: 10.1109/TII.2014.2306383
6	TAO F, CHENG J F, QI Q L, et al Digital twin-driven product design, manufacturing and service with big data[J]. The International Journal of Advanced Manufacturing Technology, 2017, 94 (4): 3563- 3576 doi: 10.1007%2Fs00170-017-0233-1
7	TAO F, ZHANG M Digital twin shop-floor: a new shop-floor paradigm towards smart manufacturing[J]. IEEE Access, 2017, 5: 20418- 20427 doi: 10.1109/ACCESS.2017.2756069
8	陶飞, 程颖, 程江峰, 等数字孪生车间信息物理融合理论与技术[J]. 计算机集成制造系统, 2017, 23 (8): 1603- 1611 TAO Fei, CHENG Ying, CHENG Jiang-feng, et al Theories and technologies for cyber-physical fusion in digital twin shop-floor[J]. Computer Integrated Manufacturing System, 2017, 23 (8): 1603- 1611
9	TUEGEL E J, INGRAFFEA A R, EASON T G, et al Reengineering aircraft structural life prediction using a digital twin[J]. International Journal of Aerospace Engineering, 2011, 2011 (1687–5966): 1- 14
10	KRAFT E M. The US air force digital thread/digital twin-life cycle integration and use of computational and experimental knowledge [C]// Proceeding of 54th AIAA Aerospace Sciences Meeting. San Diego: CA, 2016.
11	FOURGEAU E, GOMEZ E, ADLI H, et al. System engineering workbench for multi-views systems methodology with 3D experience platform: the aircraft radar use case [M]// Complex Systems Design and Management Asia. Berlin: Springer International Publishing, 2016.
12	庄存波, 刘检华, 熊辉, 等产品数字孪生体的内涵、体系结构及其发展趋势[J]. 计算机集成制造系统, 2017, 23 (4): 753- 768 ZHUANG Cun-bo, LIU Jian-hua, XIONG Hui, et al The connotation, architecture and development trend of product digital twin[J]. Computer Integrated Manufacturing System, 2017, 23 (4): 753- 768
13	GREYCE N S, CHARLES D, CARLOS E P, et al Digital twin data modeling with AutomationML and a communication methodology for data exchange[J]. IFAC-Papers Online, 2016, 49 (30): 12- 17 doi: 10.1016/j.ifacol.2016.11.115
14	GRIEVES M, VICKERS J. Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems [M]// Transdisciplinary Perspectives on Complex Systems. Berlin: Springer-Verlag, 2017.
15	LI C C, MAHADEVAN S, LING Y, et al Dynamic bayesian network for aircraft wing health monitoring digital twin[J]. AIAA Journal, 2017, 55 (3): 930- 941 doi: 10.2514/1.J055201
16	KAZI M A, ABDULMOTALEB E S C2PS: a digital twin architecture reference model for the cloud-based CPS[J]. IEEE Access, 2017, 5: 2050- 2062 doi: 10.1109/ACCESS.2017.2657006
17	ZHENG Y, YANG S, CHENG H C An application framework of digital twin and its case study[J]. Journal of Ambient Intelligence and Humanized Computing, 2019, 10 (3): 1141- 1153 doi: 10.1007/s12652-018-0911-3
18	陶飞, 刘蔚然, 张萌, 等数字孪生五维模型及十大领域应用[J]. 计算集成制造系统, 2019, 25 (1): 1- 18 TAO Fei, LIU Wei-ran, ZHANG Meng, et al Five dimension digital twin model and its ten applications[J]. Computational Integrated Manufacturing System, 2019, 25 (1): 1- 18
19	陶飞, 张萌, 程江峰, 等数字孪生车间: 一种未来车间运行新模式[J]. 计算集成制造系统, 2017, 23 (1): 1- 9 TAO Fei, ZHANG Meng, CHENG Jiang-feng, et al Digital twin workshop: anew mode of workshop operation in the future[J]. Computational Integrated Manufacturing System, 2017, 23 (1): 1- 9
20	陶飞, 刘蔚然, 刘检华, 等数字孪生及其应用探究[J]. 计算机集成制造系统, 2018, 24 (1): 1- 18 TAO Fei, LIU Wei-ran, LIU Jian-hua, et al Digital twin and its potential application exploration[J]. Computational Integrated Manufacturing System, 2018, 24 (1): 1- 18
21	柳林燕, 杜宏祥, 汪惠芬, 等车间生产过程数字孪生系统构建及应用[J]. 计算集成制造系统, 2019, 25 (6): 1536- 1546 LIU Lin-yan, DU Hong-xiang, WANG Hui-fen, et al Construction and application of digital twin system for production process in workshop[J]. Computational Integrated Manufacturing System, 2019, 25 (6): 1536- 1546
22	郭东升, 鲍劲松, 史恭威, 等基于数字孪生的航天结构件的制造车间建模研究[J]. 东华大学学报: 自然科学版, 2018, 44 (4): 579- 587 GUO Dong-sheng, BAO Jin-song, SHI Gong-wei, et al Research on modeling of aerospace structural parts manufacturing workshop based on digital twin[J]. Journal of DongHua University: Natural Sicence, 2018, 44 (4): 579- 587
23	郑守国, 崔雁民, 王青, 等飞机装配现场数据采集平台设计[J]. 浙江大学学报: 工学版, 2018, 52 (8): 1526- 1538 ZHENG Shou-guo, CUI Yan-min, WANG Qing, et al Design of field data acquisition platform for aircraft assembly[J]. Journal of Zhejiang University: Engineering Science, 2018, 52 (8): 1526- 1538

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