Digital Application of Equipment System Test and Evaluation Based on Digital Twin and Parallel Experiment Theory

doi:10.16182/j.issn1004731x.joss.23-0433

Abstract

Abstract:

With the development of equipment systematization,traditional test with real equipment can not meet the requirements of Test and Evaluation(T&E), especially for complex equipment. As the main digital methods in current, digital twins and parallel experiments can support the digital application in the field of equipment Test and Evaluation. This paper makes a comparative analysis of the two digital technology means, extracts their technical connotation and characteristics, and then integrates them to explore the application mode, application time and application occasions in the field of equipment T&E. Taking the satellite for example, by constructing the digital architecture of equipment systemT&E based on digital twin and parallel tests, the feasible digital application scheme is designed. The confidence and reliability of the digital model in the equipment system test and evaluation model library are verified through two typical test scenarios. Furthermore, it provides data support for the future on-orbit mission embodiment design and performance evaluation and provides an overall idea for the development of equipment system T&E.

Key words: equipment system, test and evaluation (T&E), digital twin, parallel experiment theory, digital applications

CLC Number:

TP391.9

Dang Hongjie, Yu Wenguang, Yang Huahui. Digital Application of Equipment System Test and Evaluation Based on Digital Twin and Parallel Experiment Theory[J]. Journal of System Simulation, 2024, 36(7): 1729-1736.

Figures/Tables 5

References 13

1	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.
	Zhang Lin, Lu Han. Discussing Digital Twin from of Modeling and Simulation[J]. Journal of System Simulation, 2021, 33(5): 995-1007.
2	迈克尔·格里夫斯. 智能制造之虚拟完美模型: 驱动创新与精益产品[M]. 方志刚, 张振宇, 译. 北京: 机械工业出版社, 2017: 74-75.
	Grieves M. Virtually Perfect: Driving Innovative and Lean Products Through Product Lifecycle Management[M]. Translated by Fang Zhigang, Zhang Zhenyu. Beijing: China Machine Press, 2017: 74-75.
3	Glaessgen E H, Stargel D S. The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles[C]//53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Reston, VA, USA: AIAA, 2012: AIAA 2012-1818.
4	王飞跃. 平行系统方法与复杂系统的管理和控制[J]. 控制与决策, 2004, 19(5): 485-489, 514.
	Wang Feiyue. Parallel System Methods for Management and Control of Complex Systems[J]. Control and Decision, 2004, 19(5): 485-489, 514.
5	王晓, 要婷婷, 韩双双, 等. 平行车联网:基于ACP的智能车辆网联管理与控制[J]. 自动化学报, 2018, 44(8): 1391-1404.
	Wang Xiao, Yao Tingting, Han Shuangshuang, et al. Parallel Internet of Vehicles: The ACP-based Networked Management and Control for Intelligent Vehicles[J]. Acta Automatica Sinica, 2018, 44(8): 1391-1404.
6	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 Fei, Zhang He, Qi Qinglin, et al. Theory of Digital Twin Modeling and Its Application[J]. Computer Integrated Manufacturing Systems, 2021, 27(1): 1-15.
7	胡权. 数字孪生体: 第四次工业革命的通用目的技术[M]. 北京: 人民邮电出版社, 2021: 190-199.
	Hu Quan. Digital Twin: General-purpose Technologies (GPT) of the Fourth Industrial Revolution[M]. Beijing: Posts & Telecom Press, 2021: 190-199.
8	曹建平, 王晓, 贺邓超, 等. 基于ACP方法的平行战场情报系统 [J]. 指挥与控制学报, 2022, 8(3): 332-340.
	Cao Jianping, Wang Xiao, He Dengchao, et al. Parallel Battlefield Intelligence Surveillance and Reconnaissance System Based on ACP Methodology[J]. Journal of Command and Control, 2022, 8(3): 332-340.
9	阳东升, 王坤峰, 陈德旺, 等. 平行航母：从数字航母到智能航母[J]. 指挥与控制学报, 2018, 4(2): 101-110.
	Yang Dongsheng, Wang Kunfeng, Chen Dewang, et al. Parallel Carrier Fleets: From Digital Architectures to Smart Formations[J]. Journal of Command and Control, 2018, 4(2): 101-110.
10	张玉良, 张佳朋, 王小丹, 等. 面向航天器在轨装配的数字孪生技术[J]. 导航与控制, 2018, 17(3): 75-82.
	Zhang Yuliang, Zhang Jiapeng, Wang Xiaodan, et al. Digital Twin Technology for Spacecraft On-orbit Assembly[J]. Navigation and Control, 2018, 17(3): 75-82.
11	刘蔚然, 陶飞, 程江峰, 等. 数字孪生卫星：概念、关键技术及应用[J]. 计算机集成制造系统, 2020, 26(3): 565-588.
	Liu Weiran, Tao Fei, Cheng Jiangfeng, et al. Digital Twin Satellite: Concept, Key Technologies and Applications[J]. Computer Integrated Manufacturing Systems, 2020, 26(3): 565-588.
12	杨林瑶, 陈思远, 王晓, 等. 数字孪生与平行系统：发展现状、对比及展望[J]. 自动化学报, 2019, 45(11): 2001-2031.
	Yang Linyao, Chen Siyuan, Wang Xiao, et al. Digital Twins and Parallel Systems: State of the Art, Comparisons and Prospect[J]. Acta Automatica Sinica, 2019, 45(11): 2001-2031.
13	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.

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