基于数字孪生的雷达装备结构健康监测技术研究

doi:10.3901/JME.260535

摘要/Abstract

摘要： 雷达是一种集机、电、液于一体的复杂电子装备，具有结构复杂、运行环境恶劣、运行周期长等特点，其结构可靠性和稳定性直接影响着其电性能的发挥，制约着作战任务执行的成败。现有的事后维修和定期维护体制难以适应现代战争的快速发展需求，亟需采用新的技术和方法，实时、全面评估产品的结构健康状态，提升雷达装备的可靠性和使用寿命，满足雷达装备的高质量发展需求。提出了一种基于数字孪生的雷达结构健康监测系统，通过构建雷达的数字孪生体，实现物理设备与虚拟设备之间的同步状态映射和实时数据分析与交互。系统以多学科耦合仿真环境为核心，结合实时数据采集与处理模块及虚拟仿真平台，能够对雷达装备进行高置信度的实时仿真、寿命评估、故障预测和诊断，实时监测雷达关键部件的运行状态，并提供健康状况预警。研究结果表明，该系统在提升雷达的维护效率和可靠性方面具有显著效果，为雷达结构的健康状态评估提供了科学依据，具有重要的参考价值。

关键词: 数字孪生, 结构健康监测, 多学科耦合仿真, 预测性维护, 实时数据采集

Abstract: Radar is a complex electronic system integrating machinery, electronics, and hydraulics, characterized by its complex structure, harsh operating environment, and long operational cycle. Its structural reliability and stability directly affect its electrical performance and ultimately determine the success or failure of combat missions. The existing post-facto maintenance and periodic maintenance systems are unable to meet the rapid development demands of modern warfare. There is an urgent need to adopt new technologies and methods to comprehensively and real-time assess the structural health status of products, enhance the reliability and lifespan of radar equipment, and satisfy the high-quality development requirements of radar systems. A structural health monitoring system for radar equipment based on digital twin technology is proposed. By constructing a digital twin of the radar, the system achieves synchronized state mapping and real-time data analysis and interaction between physical and virtual devices. Centered on a multidisciplinary coupled simulation environment, the system integrates real-time data acquisition and processing modules, as well as virtual simulation platforms. It enables high-confidence real-time simulation, life assessment, fault prediction, and diagnosis for radar equipment. Additionally, it monitors the operational status of critical radar components in real time and provides health status warnings.The research results demonstrate that this system significantly improves the maintenance efficiency and reliability of radar equipment, providing a scientific basis for assessing the health status of radar structures. It holds important reference value for the development of radar equipment.

Key words: digital twin, structural health monitoring of radar equipment, multi-disciplinary coupling simulation, predictive maintenance, real-time data acquisition

中图分类号:

TG156

刘营, 梅启元, 程亚龙, 胡长明, 杨斌, 刘振宇. 基于数字孪生的雷达装备结构健康监测技术研究[J]. 机械工程学报, 2026, 62(12): 107-124.

LIU Ying, MEI Qiyuan, CHENG Yalong, HU Changming, YANG Bin, LIU Zhenyu. Research on Structural Health Monitoring Technology for Radar Equipment Based on Digital Twin[J]. Journal of Mechanical Engineering, 2026, 62(12): 107-124.

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链接本文: http://www.cjmenet.com.cn/CN/10.3901/JME.260535

http://www.cjmenet.com.cn/CN/Y2026/V62/I12/107

参考文献

[1] 房芳，郑辉，汪玉，等. 机械结构健康监测综述[J]. 机械工程学报，2021，57(16):269-292. FANG Fang ，ZHENG Hui ，WANG Yu，et al. Mechanical structural health monitoring:A review[J]. Journal of Mechanical Engineering，2021，57(16):269-292.
[2] HU Y，LIU S，LU H，et al. Remaining useful life model and assessment of mechanical products:A brief review and a note on the state space model method[J]. Chinese Journal of Mechanical Engineering，2019，32(1):11-30.
[3] 袁慎芳. 结构健康监控[M]. 北京:国防工业出版社，2007. YUAN Shenfang. Structural health monitoring[M]. Beijing:National Defense Industry Press，2007.
[4] 韩润奇，刘伟松，林伯韬，等. 航天器结构健康监测技术研究进展[J]. 遥测遥控，2025，46(3):1-24. HAN Runqi，LIU Weisong，LIN Botao，et al. Research progress on spacecraft structural health monitoring technology[J]. Journal of Telemetry，Tracking and Command，2025，46(3):1-24
[5] MCCOLLOM N N，BROWN E R. PHM on the F-35 fighter[C]//Institute of Electrical and Electronics Engineers. 2011 IEEE Conference on Prognostics and Health Management，June 20-23，2011，Denver，USA: IEEE，2011:1-10.
[6] PAGET C，SPECKMANN H，KRICHEL T，et al. Validation of SHM sensors in airbus A380 full-scale fatigue test[M]. New Jersey:John Wiley & Sons， Ltd，2009.
[7] BOTTI J. SHM in the airbus group[C]//Stanford University. Proceedings of 10th International Workshop on Structural Health Monitoring，September 1-4，2015， Stanford，CA，USA:Stanford University，2015:7:18.
[8] BUTTERWORTH-HAYES P. Europe seeks 7E7 work[J]. Aerospace America，2003，41(11):4-6.
[9] 袁慎芳，邱雷，王强，等. 压电-光纤综合结构健康监测系统的研究及验证[J]. 航空学报，2009，30(2):348-356. YUAN Shenfang，QIU Lei，WANG Qiang，et al. Application research of a hybrid piezoelectric-optic fiber integrated structural health monitoring system[J]. Acta Aeronautica et Astronautica Sinica，2009，30(2):348-356.
[10] 卿新林，王奕首，赵琳. 结构健康监测技术及其在航空航天领域中的应用[J]. 实验力学，2012，27(5):517-526. QING Xinlin，WANG Yishou，ZHAO lin. Structural health monitoring technology and its application in aeronautics and astronautics[J]. Journal of Experimental Mechanics，2012，27(5):517-526.
[11] 孙侠生，肖迎春. 飞机结构健康监测技术的机遇与挑战[J]. 航空学报，2014，35(12):3199-3212. SUN Xiasheng，XIAO Yingchun. Opportunities and challenges of aircraft structural health monitoring[J]. Acta Aeronautica et Astronautica Sinica，2014，35(12):3199-3212.
[12] 陈雪峰，郭艳婕，许才彬，等. 风电装备故障诊断与健康监测研究综述[J]. 中国机械工程，2020，31(2):175-189. CHEN Xuefeng，GUO Yanjie，XU Caibin，et al. Review of fault diagnosis and health monitoring for wind power eqripment[J]. Chinese Mechanical Engineering，2020，31(2):175-189.
[13] 梁建英. 高速列车智能诊断与故障预测技术研究[J]. 北京交通大学学报，2019，43(1):63-70. LIANG Jianying. Research on intelligent diagnosis and fault prediction technology for high speed trains[J]. Journal of Beijing Jiaotong University，2019，43(1):63-70.
[14] 刘雪蓉，曹贺，张宝珍. 飞机结构健康监测技术发展研究[J]. 计测技术，2024，44(2):13-24. LIU Xuerong，CAO He，ZHANG Baozhen. Research on the development of aircraft structural health monitoring technology[J]. Metrology & Measurement Technology，2024，44(2):13-24.
[15] 白生宝，肖迎春，刘国强，等.飞机结构健康监测策略研究[J]. 兵器装备工程学报，2024，45(2):24-36. BAI Sshengbao，XIAO Yingchun，LIU Guoqiang，et al. Research on aircraft structural health monitoring strategy[J]. Journal of ordnance Equipment Engineering，2024，45(2):24-36.
[16] 陈雪峰，李兵，杨志勃，等. 风电装备变转速监测诊断技术及应用[M]. 西安:西安交通大学， 2015. CHEN Xuefeng， LI Bin， YANG Zhibo， et al. Monitoring and diagnosis technology of wind power equipment with variable speed[M]. Xi’an:Xi’an Jiaotong University，2015.
[17] WANG Tianyu，XU Chao，GUO Ning. A novel frequency-labeled adaptive sparse grid collocation method for uncertainty quantification of the frequency response of general viscoelastic damping structures[J]. International Journal of Mechanical Sciences， 2021，193:106168.
[18] 孙仕林，王天杨，褚福磊. 基于振动及声学测量的风电叶片结构健康监测研究综述[J]. 机械工程学报，2024，60(7):79-92. SUN Shilin，WANG Tianyang，CHU Fulei. Review of structural health monitoring of wind turbine blades based on vibration and acoustic measurement[J]. Journal of Mechanical Engineering，2024，60(7):79-92.
[19] 赵阳，徐田华，周玉平，等. 基于贝叶斯网络的高铁信号系统车载设备故障诊断方法的研究[J]. 铁道学报，2014，36(11):48-53. ZHAO Yang，XU Tianhua，ZHOU Yuping，et al. Bayesian network based fault diagnosis system for vehicle on-board equipment of high-speed railway[J]. Journal of the China Railway Society，2014，36(11):48-53.
[20] KOSOVA F，ALTAY Ö，ÜNVER H Ö. Structural health monitoring in aviation:A comprehensive review and future directions for machine learning[J]. Nondestructive testing and evaluation，2025，40(1):1-60.
[21] 雷亚国，贾峰，孔德同，等. 大数据下机械智能故障诊断的机遇与挑战[J]. 机械工程学报，2018，54(5):94-104. LEI Yaguo，JIA Feng，KONG Detong，et al. Opportunities and challenges of machinery intelligent fault diagnosis in big data era[J]. Journal of Mechanical Engineering，2018，54(5):94-104.
[22] 雷亚国，许学方，蔡潇，等. 面向机械装备健康监测的数据质量保障方法研究[J]. 机械工程学报，2021，57(4):1-9. LEI Yaguo，XU Xuefang，CAI Xiao，et al. Research on data quality assurance for health condition monitoring of machinery[J]. Journal of Mechanical Engineering，2021，57(4):1-9.
[23] 高士根，周敏，郑伟，等. 基于数字孪生的高端装备智能运维研究现状与展望[J]. 计算机集成制造系统，2022，28(7):1953-1965. GAO Shigen，ZHOU Min，ZHENG Wei，et al. Intelligent operation and maintenance for advanced equipment based on digital twin:challenges and future[J]. Computer Integrated Manufacturing System，2022，28(7):1953-1965.
[24] WANG Q，HUANG B，GAO Y，et al. Current status and prospects of digital twin approaches in structural health monitoring[J]. Buildings，2025，15(7):1021.
[25] 金杰，夏超，肖士利，等. 基于数字孪生的火箭起飞安全系统设计[J]. 计算机集成制造系统，2019，25(6):1337-1347. JIN Jie，XIA Chao，XIAO Shili，et al. Rocket launch safety system design scheme based on digital twins[J]. Computer Integrated Manufacturing System，2019，25(6):1337-1347.
[26] 周军华，薛俊杰，李鹤宇，等. 关于武器系统数字孪生的若干思考[J]. 系统仿真学报，2020，32(4):539-552. ZHOU Junhua，XUE Junjie，LI Heyu，et al. Thinking on digital twin for weapon system[J]. Journal of System Simulation，2020，32(4):539-552.
[27] WANG A，WANG Z Y，MA J R，et al. Digital twin models in aircraft engine operation and maintenance[J]. Equipment Intelligent Operation and Maintenance. CRC Press，2025，2025:279-288.
[28] HU Y，GUO R，WANG H，et al. Gear-fault monitoring and digital twin demonstration of aircraft engine based on piezoelectric vibration sensor for engine health management[J]. Nano Energy，2025，133:110448.
[29] CHEN L，MENG F，GU Y. Research on damage identification method and application for key aircraft components based on digital twin technology[J]. Engineering Proceedings，2025，80(1):44.
[30] DOLLI V，JALLY S V，RAWAL Y，et al. A review on tool condition monitoring in CNC turning process using digital twin technology[C]//AIP Publishing LLC. AIP Conference Proceedings，Oct 3，2025:040034.
[31] SUN Z，LIU H，YAN B，et al. CNC Machine tool operation status monitoring system based on digital twins[C]//IEEE 2025 International Conference on Electrical Automation and Artificial Intelligence (ICEAAI)，Jan 10，2025:381-385
[32] ZHANG X. Fault diagnosis model of digital twin technology for CNC machine tool feed system based on CA-GRU-PINN[J]. The International Journal of Advanced Manufacturing Technology，2025，2025:1-19.
[33] HU X，OLGUN G，ASSAAD R H. An intelligent BIM-enabled digital twin framework for real-time structural health monitoring using wireless IoT sensing，digital signal processing，and structural analysis[J]. Expert Systems with Applications，2024，252:124204.
[34] SUN Z，JAYASINGHE S，SIDIQ A，et al. Approach towards the development of digital twin for structural health monitoring of civil infrastructure:A comprehensive review[J]. Sensors，2024，25(1):59.
[35] WANG L，LIU H，ZHANG F，et al. Spatial structure digital twins:Application in intelligent health monitoring of cable dome structures[J]. Automation in Construction，2024，165:105489.
[36] JIRAWATTANASOMKUL T，HANG L，SRIVARANUN S，et al. Digital twin-based structural health monitoring and measurements of dynamic characteristics in balanced cantilever bridge[J]. Resilient Cities and Structures，2025，4(3):48-66.
[37] RAN X，CHEN S，HU X，et al. Digital twin modelling of heavy-haul train for longitudinal impulse simulation[J]. Vehicle System Dynamics，2025，2025:1-22.
[38] BIANCHI G，FREDDI F，GIULIANI F，et al. Implementation of an AI-based predictive structural health monitoring strategy for bonded insulated rail joints using digital twins under varied bolt conditions[J]. Railway Engineering Science，2025，33(4):1-8.
[39] NWAMEKWE C O，CHIKWENDU O C Machine learning-augmented digital twin systems for predictive maintenance in highspeed rail networks[J]. International Journal of Multidisciplinary Research and Growth Evaluation，2025，6(1):1783-1795.
[40] 陶飞，张辰源，张贺，等. 未来装备探索:数字孪生装备[J]. 计算机集成制造系统，2022，28(1):1-16. TAO Fei，ZHANG Chenyuan，ZHANG He，et al. Future equipment exploration:Digital twin equipment[J]. Computer Integrated Manufacturing System，2022，28(1):1-16.
[41] 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 technology and applications[J]. Computer Integrated Manufacturing System，2020，26(3):565-588.
[42] 宋学官，来孝楠，何西旺，等. 重大装备形性一体化数字孪生关键技术[J]. 机械工程学报，2022，58(10):298-325. SONG Xueguan，LAI Xiaonan，HE Xiwang，et al. Key technologies of shape-performance integrated digital twin for major equipment[J]. Journal of Mechanical Engineering，2022，58(10):298-325.
[43] 程五四，陈帝江，张祥祥，等. 基于数字孪生的雷达天线测量调控系统设计[J]. 无线互联科技，2023，20(7):78-80. CHENG Wusi，CHEN Dijiang，ZHANG Xiangxiang，et al. Design of radar antenna measurement and control system based on digital twins[J]. Wireless Internet Technology，2023，20(7):78-80.
[44] 程五四，陈帝江，张祥祥，等. 数字孪生在雷达天线阵面装配中的应用[J]. 机械，2022，49(7):8-13. CHENG Wusi，CHEN Dijiang，ZHANG Xiangxiang，et al. Application of digital twin in radar antenna array assembly[J]. Machinery，2022，49(7):8-13.
[45] 薛勇杰，虞庆庆，薛飞. 健康监测技术在机载雷达结构上的应用分析[J]. 电子机械工程，2022，38(5):33-37，45. XUE Yongjie，YU Qingqing，XUE Fei. Application analysis of PHM technology in airborne radar structure[J]. Electro-Mechanical Engineering，2022，38(5):33-37，45.