由于船舶装备的复杂性，受载荷多变以及海洋高盐雾环境等影响，性能退化较快且故障频发，其全寿命周期运维是制约其性能发挥，影响船舶遂行任务的主要难题。本文在对数字孪生技术发展现状，在设备全寿命周期的应用等分析的基础上，提出了基于数字孪生的船舶装置智能运维框架，并探讨了数字孪生技术在船舶装备应用中面临的挑战等，为加速数字孪生技术在船舶装备中发挥战斗力倍增器作用提供借鉴和参考。
Due to the complexity of ship equipment, the impact of variable loads and the high salt spray environment of the ocean, performance degradation was rapid and failures occurred frequently. Its full life cycle operation and maintenance was the main problem that restricts its performance and affects the ship's ability to carry out its mission. Based on the analysis of the development status of digital twin technology and its application in the full life cycle of equipment, this paper proposes a framework for intelligent operation and maintenance of marine devices based on digital twin and discusses the challenges faced by digital twin technology in the application of marine equipment, so as to provide reference and reference for accelerating the role of digital twin technology as a combat multiplier in marine equipment.
2022,44(8): 139-144 收稿日期：2021-04-29
DOI：10.3404/j.issn.1672-7649.2022.08.029
分类号：TJ05
基金项目：国家自然科学基金资助项目（51702364）
作者简介：吴文豪(1998-),男,硕士研究生,研究方向为动力工程
参考文献：
[1] ROSEN R, VON WICHERT G, LO G, et al. About the importance of autonomy and digital twins for the future of manufacturing[J]. IFAC-Papers on Line, 2015, 48(3):567-572
[2] GRIEVES M. Digital twin:manufacturing excellence through virtual factory replication[EB/OL]. http://www.apriso.com/library/Whitepaper_Dr_GrievesDigital T-win Manufacturing Excellence.[2016-12-20]
[3] GRIEVES M. Virtually perfect:driving innovative and lean products through product lifecycle management[M]. Cocoa Beach, Fla., USA:Space Coast Press, 2011.
[4] 陶飞, 张贺, 戚庆林, 等. 数字孪生十问:分析与思考[J]. 计算机集成制造系统, 2020, 26(1):1-17
[5] SHAFTO M, CONROY M, DOYLE R, et al. Modeling, simulation, information technology and processing roadmap[R]. New York, USA:NASA, 2010.
[6] TUEGEL E. The airframe digital twin:some chall-enges to realization[C]//Aiaa/asme/asce/ahs/asc Structures, Structural Dynamics & Materials Conference Aiaa/asme/ahsAdaptive Structures Conference Aiaa, 2013.
[7] GOCKEL B, TUDOR A, BRANDYBERRY M, et al. Challenges with structural life forecasting using realistic mission profiles[C]//53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA, 2012.
[8] REIFSNIDER K, MAJUMDAR P. Multiphysics stimulated Simulation digital twin methods for fleet management[C]//54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference (AIAA), 2013.
[9] QI Q, TAO F, YING Z, et al. Digital twin service towards Smart Manufacturing[J]. ProcediaCirp, 2018, 72:237-242
[10] GABOR T, BELZNER L, KIERMEIER M, et al. A Simulationbased architecture for smart cyberphysical systems[C]//IEEE International Conference on Autonomic Computing. IEEE, 2016.
[11] 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.
[12] 李浩, 陶飞, 王昊琪, 等. 基于数字孪生的复杂产品设计制造一体化开发框架与关键技术[J]. 计算机集成制造系统, 2019, 25(6):1320-1336
[13] CHENG J, ZHANG H, TAO F, et al. DT-II:digital twin enhanced Industrial Internet reference framework towards smart manufacturing[J]. Robotics and Computer-Integrated Manufacturing, 2020:62
[14] TAO F, CHENG J, QI Q, et al. Digital twin-driven product design, manufacturing and service with big data[J]. The International Journal of Advanced Manufacturing Technology, 2018, 94:9-12
[15] TAO F, SUI F, LIU A, et al. Digital twin-driven product design framework[J]. International Journal of Production Research, 2019, 57:3935-3953
[16] QI Q, TAO F. Digital twin and big data towards smart manufacturing and Industry 4.0:360 degree comparison[J]. IEEE Access, 2018, 6:3585-3593
[17] 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
[18] SCHLEICH B, ANWER N, MATHIEU L, et al. Shaping the digital twin for design and production engineering[J]. CIRP Annals-Manufacturing Technology, 2017, 66(1):141-144
[19] MAURER T. What is A Digital Twin?, 2017[EB/OL]. https://community.plm.
[20] WEYER S, MEYER T, OHMER M, et al. Future modeling and simulation of CPS based factories:an example from the automotive industry[J]. IFAC-Papers on Line, 2016, 49(31):97-102
[21] ZHAO P, LIU J, JING X, et al. The modeling and using strategy for the digital twin in process planning[J]. IEEE Access 2020, 8:41229−41245.
[22] TAO F, ZHANG M. Digital twin shop-floor:a new shop-floor paradigm towards smart manufacturing[J]. IEEE Access, 2017, 5:20418-20427
[23] WANG Y, WU Z. Digital twin-based production sche-duling system for heavy truck frame shop[J]. Journal of Mechanical Engineering Science. 2020
[24] ZHANG H, ZHANG G, YAN Q. Digital twin-driven cyber-physical production system towards smart shopfloor[J]. Journal of Ambient Intelligence and Humanized Computing, 2019, 10(11):4439-4453
[25] LI J, TAO F, CHENG Y, et al. Big data in product lifecycle management[J]. International Journal of Advanc-ed Manufacturing Technology, 2015, 81(1):667-684
[26] ZHANG H, LIU Q, CHEN X, et al. A digital twin-based approach for designing and multi-objective optimization of hollow glass production line[J]. IEEE Access, 2017, 5:26901-26911
[27] LYNN R, CHEN A, LOCKS S, et al. Intelligent and accessible data flow architectures for manufacturing system optimization[J]. Springer, Cham, 2015, 459:27−35.
[28] LUO W, HU T, ZHANG C, et al. Digital twin for CNC machine tool:modeling and using strategy[J]. Journal of Ambient Intelligence and Humanized Computing, 2019, 10(3):1129-1140
[29] BOSCHERT S, ROSEN R. Digital twin-the simulation aspect[M]. Springer International Publishing, 2016.
[30] WANG J, YE L, GAO R X, et al. Digital twin for rotating machinery fault diagnosis in smart manufacturing[J]. International Journal of Production Research, 2019, 57(12):3920-3934
[31] SIVALINGAM K, SEPULVEDA M, SPRING M, et al. A review and methodology development for remaining useful life prediction of offshore fixed and floating wind turbine power converter with digital twin technology perspective[C]//2018 2nd International Conference on Green Energy and Applications (ICGEA). IEEE, 2018.
[32] SOARES R M, MAURÍCIO M CMARA, FEITAL T, et al. Digital twin for monitoring of industrial multi-effect evaporation[J]. Processes, 2019, 7(8):537
[33] SESHADRI B R, KRISHNAMURTHY T. Structural health management of damaged aircraft structures using digital twin concept[C]//25TH AIAA/AHS ADAP-TIVE Structures Conference. 2017.
[34] BAZILEVS Y, DENG X, KOROBENKO A, et al. Isogeometric fatigue damage prediction in largescale composite structures driven by dynamic sensor data[J]. J-ournal of Applied Mechanics, 2015, 82(9):091008
[35] YERATAPALLY S, LESER P, HOCHHALTER J, et al. A digital twin feasibility study (Part I):Non-determini-sticpredictions of fatigue life in aluminum alloy 7075-T651 using amicrostructurebased multi-scale model[J]. Engineering Fracture Mechanics, 2020, 228:106888.
[36] LESER P, WARNER J, LESER W, et al. A digital twin feasibility study (Part II):non-deterministic predictions of fatigue life using insitu diagnostics and prognostics[J], Engineering Fracture Mechanics, 2020, 229:106903.
[37] ZAKRAJSEK A J, MALL S. The development and use of a digital twin model for tire touchdown health monitoring[C]//58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2017.
[38] KRISHNAN M, VENKATESAN S, NAGENDRAN V, et al. Health monitoring and prognosis of electric vehicle motor using intelligent-digital twin[J]. IET Electric Power Applications, 2019, 13(9):1328-1335
[39] AIVALIOTIS P, GEORGOULIAS K, CHRYSSOLOURIS G. The use of digital twin for predictive maintenance in manufacturing[J]. International Journal of Compu-ter Integrated Manufacturing, 2019, 32(11):1067-1080
[40] BOOYSE W, WILKE D N, HEYNS S. Deep digital twins for detection, diagnostics and prognostics[J]. Mechanical Systems and Signal Processing, 2020, 140(6):1-25
[41] BAGHERI B, LEE J. Big future for cyber-physical manufacturing systems, design world (2015)[EB/OL], https://www.designworldonline.com/big-future-for-cyber-physicalmanufac-turing-systems/
