Special Issue: Aircraft Digital Twin Technology

Digital-twin’s modelling and dynamic adjustment mechanism of rudder-loop-system under fault conditions

  • Junqi LEI ,
  • Yuehua CHENG ,
  • Bin JIANG ,
  • Cheng XU ,
  • Guili XU ,
  • Tianyu SUN
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  • 1.College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China
    2.Key Laboratory of Complex System Control and Intelligent Cooperative Technology,Beijing 100074,China

Received date: 2024-09-27

  Revised date: 2024-10-21

  Accepted date: 2024-12-05

  Online published: 2024-12-10

Supported by

National Key Research and Development Program of China(2023YFB3307100)

Abstract

To address the challenges of limited and incomplete measurable data in fault detection, diagnosis, and prediction of the rudder-loop-system in long-endurance reusable aircraft, this study introduces a digital twin-based approach for health management of the system. First, a digital twin framework for the aircraft’s rudder-loop-system is proposed, incorporating high-fidelity modelling and simulation of mechanical, electrical, control, and dynamic flight load subsystems using AMESim and FLUENT. The integrated model realizes the coupling of three-phase electro-mechanical control with real-time flight dynamic loading. Subsequently, to ensure consistency between the digital twin and the physical system under various operational conditions including normal, rudder surface degradation, and loosening faults, a virtual-physical consistency perception method and a dynamic adjustment mechanism are developed. This enables the digital twin to continuously track physical system changes and maintain synchronization through online fault perception and dynamic updating. Finally, experimental results demonstrate that under both normal and faulty conditions, the digital and physical systems exhibit consistent trends and amplitudes in multiple time-domain indicators of rudder current and deflection angle. Moreover, the expanded data dimensions provided by the digital twin enhance the comprehensiveness of data available for health management. This research highlights the potential of digital twin applications in improving the reliability and maintainability of electric rudders in advanced flight systems.

Cite this article

Junqi LEI , Yuehua CHENG , Bin JIANG , Cheng XU , Guili XU , Tianyu SUN . Digital-twin’s modelling and dynamic adjustment mechanism of rudder-loop-system under fault conditions[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2025 , 46(19) : 531273 -531273 . DOI: 10.7527/S1000-6893.2024.31273

References

[1] 佘文学, 刘凯, 刘晶. 空天飞行器制导控制技术发展思考[J]. 战术导弹技术2017(4): 1-10.
  SHE W X, LIU K, LIU J. Thoughts on the development of guidance and control technology for aerospace vehicle[J]. Tactical Missile Technology2017(4): 1-10 (in Chinese).
[2] 丛斌, 孟祥瑞, 张迪. 飞翼飞机新型操纵舵面故障效能影响分析[J]. 战术导弹技术2020(2): 29-33.
  CONG B, MENG X R, ZHANG D. Influences of control efficiency of flying-wing’s new-type control surface faults[J]. Tactical Missile Technology2020(2): 29-33 (in Chinese).
[3] 武天才, 王宏伦, 任斌, 等. 基于学习的高超声速飞行器分层协调容错方法[J]. 航空学报202445(22): 330191.
  WU T C, WANG H L, REN B, et al. Learning-based hierarchical coordination fault-tolerant method for hypersonic vehicles[J]. Acta Aeronautica et Astronautica Sinica202445(22): 330191 (in Chinese).
[4] 刘剑慰. 基于模型的飞行控制系统故障诊断方法研究[D]. 南京: 南京航空航天大学, 2014.
  LIU J W. Research on fault diagnosis method of flight control system based on model[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2014 (in Chinese).
[5] 朱纪洪, 和阳, 黄志毅. 舵机特征模型及其故障检测方法[J]. 航空学报201536(2): 640-650.
  ZHU J H, HE Y, HUANG Z Y. Characteristic model-based approach for actuator fault diagnosis[J]. Acta Aeronautica et Astronautica Sinica201536(2): 640-650 (in Chinese).
[6] 刘聪, 钱坤, 丁奇. 飞翼飞机非线性电动舵回路鲁棒滑模故障估计观测器设计[J/OL]. 机械科学与技术, (2023-11-24)[2025-06-03]. .
  LIU C, QIAN K, DING Q. Design of robust sliding mode fault estimation observer for nonlinear electric rudder loop of flying wing aircraft[J/OL]. (in Chinese).
[7] 杨石琳, 乔凯俐, 万晓忠, 等. 考虑多环节间隙非线性的电动舵机多学科耦合动力学建模[J/OL]. 北京航空航天大学学报, (2024-04-22)[2025-06-03]. .
  YANG S L, QIAO K L, WAN X Z, et al. Multidisciplinary coupling dynamics modeling of electric steering gear considering multi-link gap nonlinearity[J/OL]. Journal of Beijing University of Aeronautics and Astronautics, (2024-04-22)[2025-06-03]. (in Chinese).
[8] KIM S H, TAHK M J. Dynamic stiffness transfer function of an electromechanical actuator using system identification[J]. International Journal of Aeronautical and Space Sciences201819(1): 208-216.
[9] KARPENKO M, SEPEHRI N, SCUSE D. Diagnosis of process valve actuator faults using a multilayer neural network[J]. Control Engineering Practice200311(11): 1289-1299.
[10] SIMANI S, FARSONI S, CASTALDI P, et al. Actuator fault reconstruction via dynamic neural networks for an autonomous underwater vehicle model[J]. IFAC-PapersOnLine202255(6): 755-759.
[11] QIN H, YANG R F, GUO C X, et al. Fault diagnosis of electric rudder system using PSOFOA-BP neural network[J]. Measurement2021186: 110058.
[12] 崔乃刚, 郭冬子, 王瑞鸣, 等. 飞航导弹智能故障诊断与容错控制[J]. 战术导弹技术2020(4): 125-134.
  CUI N G, GUO D Z, WANG R M, et al. Intelligent fault diagnosis and fault tolerant control for cruise missile[J]. Tactical Missile Technology2020(4): 125-134 (in Chinese).
[13] 姜斌, 程月华, 孙颢, 等. 一种利用LSTM-FCN的导弹舵回路故障诊断算法[J]. 宇航学报202344(5): 687-698.
  JIANG B, CHENG Y H, SUN H, et al. A fault diagnosis algorithm of missile rudder loop using LSTM-FCN[J]. Journal of Astronautics202344(5): 687-698 (in Chinese).
[14] 曾聪. 飞控系统故障诊断方法研究与实现[D]. 成都: 电子科技大学, 2019.
  ZENG C. Research and implementation of fault diagnosis method for flight control system[D]. Chengdu: University of Electronic Science and Technology of China, 2019 (in Chinese).
[15] 郭璐, 刘晓东, 魏东涛, 等. 基于改进PCA的导弹装备健康表征参数提取方法[J]. 系统工程与电子技术202244(10): 3275-3281.
  GUO L, LIU X D, WEI D T, et al. Extraction method of missile equipment health characterization parameters based on improved PCA[J]. Systems Engineering and Electronics202244(10): 3275-3281 (in Chinese).
[16] 刘笑炎, 陈立平, 丁建完, 等. 迁移学习在变工况方向舵故障诊断中的应用[J]. 航天控制202442(3): 75-81.
  LIU X Y, CHEN L P, DING J W, et al. Application of transfer learning in rudder fault diagnosis under variable operating conditions[J]. Aerospace Control202442(3): 75-81 (in Chinese).
[17] 马兴瑞, 马嵩华, 胡天亮. 基于数字孪生模型的故障特征生成与诊断[J]. 组合机床与自动化加工技术2022(8): 94-98, 104.
  MA X R, MA S H, HU T L. Fault feature generation and fault diagnosis based on digital twin model[J]. Modular Machine Tool & Automatic Manufacturing Technique2022(8): 94-98, 104 (in Chinese).
[18] GRIEVES M, VICKERS J. Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems[M]∥Transdisciplinary Perspectives on Complex Systems. Cham: Springer International Publishing, 2016: 85-113.
[19] GLAESSGEN E, STARGEL D. 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: AIAA, 2012.
[20] ROJEK I, MIKO?AJEWSKI D, DOSTATNI E. Digital twins in product lifecycle for sustainability in manufacturing and maintenance[J]. Applied Sciences202111(1): 31.
[21] FULLER A, FAN Z, DAY C, et al. Digital twin: Enabling technologies, challenges and open research[J]. IEEE Access20208: 108952-108971.
[22] 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201925(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 Systems201925(1): 1-18 (in Chinese).
[23] 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202127(1): 1-15.
  TAO F, ZHANG H, QI Q L, et al. Theory of digital twin modeling and its application[J]. Computer Integrated Manufacturing Systems202127(1): 1-15 (in Chinese).
[24] 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202026(1): 1-17.
  TAO F, ZHANG H, QI Q L, et al. Ten questions towards digital twin: Analysis and thinking[J]. Computer Integrated Manufacturing Systems202026(1): 1-17 (in Chinese).
[25] TSITSILONIS K M, THEOTOKATOS G, PATIL C, et al. Health assessment framework of marine engines enabled by digital twins[J]. International Journal of Engine Research202324(7): 3264-3281.
[26] 周标, 谢诚语, BATTIATO G, 等. 面向结构动力学测试的整体叶盘数字孪生技术[J/OL]. 航空动力学报, (2024-05-23)[2025-06-03]. .
  ZHOU B, XIE C Y, BATTIATO G, et al. Digital twinning technology of integral bladed disk for structural dynamics test[J/OL]. Journal of Aerospace Dynamics, (2024-05-23)[2025-06-03]. (in Chinese).
[27] 付洋, 曹宏瑞, 郜伟强, 等. 数字孪生驱动的航空发动机涡轮盘剩余寿命预测[J]. 机械工程学报202157(22): 106-113.
  FU Y, CAO H R, GAO W Q, et al. Digital twin driven remaining useful life prediction for aero-engine turbine discs[J]. Journal of Mechanical Engineering202157(22): 106-113 (in Chinese).
[28] 项浩圆. 基于数字孪生的电静液作动器热特性研究[D]. 杭州: 浙江大学, 2023.
  XIANG H Y. Study on thermal characteristics of electrohydrostatic actuator based on digital twin[D]. Hangzhou: Zhejiang University, 2023 (in Chinese).
[29] 郭丞皓, 于劲松, 宋悦, 等. 基于数字孪生的飞机起落架健康管理技术[J]. 航空学报202344(11): 227629.
  GUO C H, YU J S, SONG Y, et al. Application of digital twin-based aircraft landing gear health management technology[J]. Acta Aeronautica et Astronautica Sinica202344(11): 227629 (in Chinese).
[30] 董雷霆, 周轩, 赵福斌, 等. 飞机结构数字孪生关键建模仿真技术[J]. 航空学报202142(3): 023981.
  DONG L T, ZHOU X, ZHAO F B, et al. Key technologies for modeling and simulation of airframe digital twin[J]. Acta Aeronautica et Astronautica Sinica202142(3): 023981 (in Chinese).
[31] 陈健, 孟义兴, 袁慎芳, 等. 融合导波监测的搭接结构裂纹扩展寿命孪生预测[J]. 机械工程学报202460(16): 34-42.
  CHEN J, MENG Y X, YUAN S F, et al. Digital twins prediction of crack growth life for the lap joint structure combined with guided wave monitoring data[J]. Journal of Mechanical Engineering202460(16): 34-42 (in Chinese).
[32] 陶飞, 马昕, 戚庆林, 等. 数字孪生连接交互理论与关键技术[J]. 计算机集成制造系统202329(1): 1-10.
  TAO F, MA X, QI Q L, et al. Theory and key technologies of digital twin connection and interaction[J]. Computer Integrated Manufacturing Systems202329(1): 1-10 (in Chinese).
[33] 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201839(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 Instrument201839(11): 1-10 (in Chinese).
[34] 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201824(1): 1-18.
  TAO F, LIU W R, LIU J H, et al. Digital twin and its potential application exploration[J]. Computer Integrated Manufacturing Systems201824(1): 1-18 (in Chinese).
[35] 陈墨, 胡昌华, 张伟, 等. 新型无刷直流电动伺服机构设计与分析[J]. 电机与控制应用201542(5): 6-10, 16.
  CHEN M, HU C H, ZHANG W, et al. Design and analysis of A new BLDCM servomechanism[J]. Electric Machines & Control Application201542(5): 6-10, 16 (in Chinese).
[36] 黄璐, 文军, 姜杰. 电动舵机系统建模与仿真研究[J]. 自动化与仪器仪表2020(12): 237-239, 244.
  HUANG L, WEN J, JIANG J. Research on modeling and simulation of electric servo system[J]. Automation & Instrumentation2020(12): 237-239, 244 (in Chinese).
[37] 卢晋, 吴志刚, 杨超. 电动舵机模块化建模及动刚度仿真[J]. 北京航空航天大学学报202147(4): 765-778.
  LU J, WU Z G, YANG C. Modular modeling and dynamic stiffness simulation of electromechanical actuator[J]. Journal of Beijing University of Aeronautics and Astronautics202147(4): 765-778 (in Chinese).
[38] 李朋, 高智刚, 周军, 等. 高性能电动舵机系统高保真建模方法研究[J]. 西北工业大学学报201836(1): 7-12.
  LI P, GAO Z G, ZHOU J, et al. High fidelity modeling method of high performance electromechanical actuator[J]. Journal of Northwestern Polytechnical University201836(1): 7-12 (in Chinese).
[39] 韩强. 小型高精度弹载舵机系统设计[D]. 西安: 西安石油大学, 2021.
  HAN Q. Design of small and high precision missile-borne steering gear system[D]. Xi’an: Xi’an Shiyou University, 2021 (in Chinese).
[40] 白滢. 小型高精度电动舵机伺服控制系统设计[D]. 大连: 大连理工大学, 2018.
  BAI Y. Design of servo control system for small high precision electric steering gear[D]. Dalian: Dalian University of Technology, 2018 (in Chinese).
[41] 高翔. 基于强化学习的X舵AUV控制分配与故障诊断[D]. 哈尔滨: 哈尔滨工程大学, 2023.
  GAO X. Control allocation and fault diagnosis of X-rudder AUV based on reinforcement learning[D]. Harbin: Harbin Engineering University, 2023 (in Chinese).
[42] 王小平. X舵AUV控制分配优化与容错控制方法研究[D]. 哈尔滨: 哈尔滨工程大学, 2020.
  WANG X P. Research on control allocation optimization and fault-tolerant control method of X rudder AUV[D]. Harbin: Harbin Engineering University, 2020 (in Chinese).
[43] 彭钱诚, 裴扬, 王文宽. 飞机舵面易损特性与毁伤评估方法研究综述[J]. 空天防御20247(3): 14-26.
  PENG Q C, PEI Y, WANG W K. Review of vulnerability characteristics and damage assessment methods of aircraft rudder surface[J]. Air & Space Defense20247(3): 14-26 (in Chinese).
[44] 顾君垚, 丁强, 夏宇栋, 等. 基于UMAP-AdamDD的冷水机组故障诊断方法[J]. 低温与超导202250(1): 81-87.
  GU J Y, DING Q, XIA Y D, et al. An effective fault diagnosis method for water chillers using UMAP-AdamDD[J]. Cryogenics & Superconductivity202250(1): 81-87 (in Chinese).
[45] 易灿灿, 庹帅, 涂闪, 等. 基于UMAP辅助的模糊C聚类方法进行太赫兹光谱识别[J]. 光谱学与光谱分析202242(9): 2694-2701.
  YI C C, TUO S, TU S, et al. UMAP-assisted fuzzy C-clustering method for recognition of terahertz spectrum[J]. Spectroscopy and Spectral Analysis202242(9): 2694-2701 (in Chinese).
[46] 万琦, 刘更, 马尚君. 舵机传动系统动力学联合仿真建模及实验研究[J]. 机床与液压202452(11): 132-137.
  WAN Q, LIU G, MA S J. Research on co-simulation modeling and experiments of rudder transmission system[J]. Machine Tool & Hydraulics202452(11): 132-137 (in Chinese).
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