空地协同下的飞机抖振飞行试验方法研究

张武林, 刘佳璐, 田瑞, 陈浩, 雷鸣

装备环境工程 ›› 2026, Vol. 23 ›› Issue (10) : 71-81.

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装备环境工程 ›› 2026, Vol. 23 ›› Issue (10) : 71-81. DOI: 10.7643/issn.1672-9242.2026.10.008
航空航天装备

空地协同下的飞机抖振飞行试验方法研究

  • 张武林1, 刘佳璐1, 田瑞2, 陈浩1, 雷鸣3
作者信息 +

Aircraft Buffeting Flight Test Method under Air-Ground Coordination

  • ZHANG Wulin1, LIU Jialu1, TIAN Rui2, CHEN Hao1, LEI Ming3
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摘要

目的 突破飞机抖振飞行试验“机载采集-落地分析-试验点迭代”传统开环模式,提升飞行试验效率、降低试验风险,满足数字化背景下的飞机飞行试验高效高质的工程需求。方法 基于构建的“机载测试层-数据链路层-地面监控层-地面模型层”四层空地协同架构,引入空中飞行试验与地面实时预测相融合的空地协同方法,并对方法所用到技术的工程可行性论证分析,最后以飞机抖振飞行试验科目对该空地协同方法进行验证。结果 基于空地协同下的抖振预测方法可以提前识别飞机抖振等级和优化试验点,迎角预测结果误差不超过6%,试验点节约不少于75%。结论 空地协同方法可有效提升试验效率、节约试验点、降低试验风险性,并可为飞机抖振科目以及其他平台试验科目的试验协同数字化转型提供参考,具有显著的工程应用价值。

Abstract

The work aims to break through the traditional open-loop mode of “on-board collection, ground analysis and test point iteration” for aircraft buffet flight tests, improve flight test efficiency, reduce test risks, and meet the engineering requirements of high efficiency and high quality for aircraft flight tests in the digital context. Based on the constructed four-layer air-ground collaborative architecture of “on-board test layer, data link layer, ground monitoring layer and ground model layer”, an air-ground collaborative method integrating in-flight tests and real-time ground prediction was introduced, and the engineering feasibility of the technologies used in the method was demonstrated and analyzed. Finally, the air-ground collaborative method was verified through the aircraft buffet flight test subject. Based on the air-ground collaborative buffet prediction method, the aircraft buffet level could be identified in advance and the test points could be optimized, with the error of the angle of attack prediction result not exceeding 6% and the test points saved by no less than 75%. The air-ground collaborative method can effectively improve test efficiency, save test points, reduce test risks, and can provide a reference for the digital transformation of test collaboration in aircraft buffet subjects and other platform test subjects, which has significant engineering application value.

关键词

空地协同 / 抖振 / 飞行试验 / 响应预测 / 抖振等级识别 / 试验数字化

Key words

air-ground coordination / buffet / flight test / response prediction / buffet level identification / test digitization

引用本文

导出引用
张武林, 刘佳璐, 田瑞, 陈浩, 雷鸣. 空地协同下的飞机抖振飞行试验方法研究[J]. 装备环境工程. 2026, 23(10): 71-81 https://doi.org/10.7643/issn.1672-9242.2026.10.008
ZHANG Wulin, LIU Jialu, TIAN Rui, CHEN Hao, LEI Ming. Aircraft Buffeting Flight Test Method under Air-Ground Coordination[J]. Equipment Environmental Engineering. 2026, 23(10): 71-81 https://doi.org/10.7643/issn.1672-9242.2026.10.008
中图分类号: V216   

参考文献

[1] 米毅, 连光册. 空地一体化技术在IFTD试飞中的应用[J]. 民用飞机设计与研究, 2020(4): 92-96.
MI Y, LIAN G C.Application of Air-to-Ground Integration Technology in IFTD Flight Test[J]. Civil Aircraft Design & Research, 2020(4): 92-96.
[2] 沈玙, 肖刚, 鲁岱晓, 等. 虚拟试飞关键技术及应用研究[J]. 民用飞机设计与研究, 2021(4): 9-14.
SHEN Y, XIAO G, LU D X, et al.Critical Virtual Flight Test Technology and Application Research[J]. Civil Aircraft Design & Research, 2021(4): 9-14.
[3] Federal Aviation Administration.1-g Stall Speed as the Basis for Compliance with Part 25 of the Federal Aviation Regulations: Amendment 25-108, 67 FR 70812[S]. Washington: Federal Aviation Administration, 2002.
[4] 袁冲, 修忠信, 田海玲, 等. 民用飞机试飞规划与管理技术研究[J]. 民用飞机设计与研究, 2014(3): 1-4.
YUAN C, XIU Z X, TIAN H L, et al.Research on Flight Test Planning and Management for Civil Aircraft[J]. Civil Aircraft Design and Research, 2014(3): 1-4.
[5] HEWETT M, TARTT D, DUKE E L, et al.The Development of an Automated Flight Test Management System for Flight Test Planning and Monitoring[C]// Proceedings of the First International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems-IEA/AIE '88. Tullahoma: ACM, 1988.
[6] 孙碧晴, 杨旭, 吴双, 等. 贝叶斯网络在科研试飞安全风险评估中的应用[J]. 飞行力学, 2019, 37(2): 92-96.
SUN B Q, YANG X, WU S, et al.Application of Bayesian Network in the Safety Risk Assessment of Flight Test[J]. Flight Dynamics, 2019, 37(2): 92-96.
[7] LU Y, ZHANG S G, ZHANG Z J, et al.Multiple Hierarchy Risk Assessment with Hybrid Model for Safety Enhancing of Unmanned Subscale BWB Demonstrator Flight Test[J]. Chinese Journal of Aeronautics, 2019, 32(12): 2612-2626.
[8] 山寿, 郝明哲, 孙伟. 基于数据分发服务和WPF技术的试飞实时监控系统设计[J]. 计算机测量与控制, 2020, 28(3): 119-122.
SHAN S, HAO M Z, SUN W.Design of Real-Time Monitoring System for Flight Test Based on DDS and WPF Technology[J]. Computer Measurement & Control, 2020, 28(3): 119-122.
[9] 米毅, 李爱军, 陈俊平, 等. 一种基于飞行仿真的空地一体化试飞技术框架[J]. 西北工业大学学报, 2024, 42(4): 689-696.
MI Y, LI A J, CHEN J P, et al.An Air-Ground Integrated Flight Test Technical Framework Based on Flight Simulation[J]. Journal of Northwestern Polytechnical University, 2024, 42(4): 689-696.
[10] LIAN G C, FAN Z P, WEN Y J, et al.Application of Air-to-Ground Integration Technology in Civil Aircraft Engine AirStart Flight Test[C]// 2024 3rd International Symposium on Aerospace Engineering and Systems (ISAES). Nanjing: IEEE, 2024.
[11] MILLAR R C, LALIBERTÉ J, MAHMOODI A, et al.Designing an Uncrewed Aircraft Systems Control Model for an Air-to-Ground Collaborative System[J]. SAE International Journal of Aerospace, 2024, 17(2): 225-241.
[12] XIA X J, XIANG N, ZOU D, et al.An Air-Ground Cooperative Situation Fusion Algorithm Based on Multi-Unmanned Ground Vehicle and Multi-Unmanned Aerial Vehicle[C]//Proceedings of 4th 2024 International Conference on Autonomous Unmanned Systems (4th ICAUS 2024). Singapore: Springer Nature Singapore, 2025: 454-467.
[13] 王岩韬, 赵昕颐. 空地数据实时传输下的飞机着陆风险预警方法[J]. 工程科学学报, 2023, 45(10): 1759-1770.
WANG Y T, ZHAO X Y.Advanced Warning Method for Aircraft Landing Risk under Air-Ground Data Real-Time Transmission Conditions[J]. Chinese Journal of Engineering, 2023, 45(10): 1759-1770.
[14] 陈家益, 刘涛, 冯灿, 等. 基于卫星通信的民机试飞数据实时监控系统设计与研发[J]. 民用飞机设计与研究, 2024(4): 76-83.
CHEN J Y, LIU T, FENG C, et al.Design and Development of Real-Time Monitoring System for Civil Aircraft Flight Test Data Based on Satellite Communications[J]. Civil Aircraft Design & Research, 2024(4): 76-83.
[15] Federal Aviation Administration.Flight Test Guide for Certification of Transport Category Airplanes: AC25-7D[S]. Washington: Federal Aviation Administration, 2018.
[16] 高文涛, 张武林. 一种运输类飞机初始抖振判定方法[J]. 现代机械, 2020(6): 37-41.
GAO W T, ZHANG W L.A Method to Determine the Buffet Onset of a Transport Airplane[J]. Modern Machinery, 2020(6): 37-41.
[17] 高文涛, 张武林, 寇宝智. T型尾翼飞机抖振试飞研究[J]. 实验流体力学, 2020, 34(6): 45-51.
GAO W T, ZHANG W L, KOU B Z.Study on Buffet Flight Test of Aircraft with T-Tail[J]. Journal of Experiments in Fluid Mechanics, 2020, 34(6): 45-51.
[18] 国防科学技术工业委员会.人体全身振动暴露的舒适性降低限和评价准则: GJB966—90[S]. 北京: 中国标准出版社, 1990.
Commission of Science, Technology and Industry for National Defence., Reduced Comfort Boundary and Evaluation Criteria for Human Exposure to Whole-body Vibration: GJB966—90[S]. Beijing: China Standards Press, 1990.
[19] WANG J, LIU W, XIE H R, et al.Advancing Buffet Onset Prediction: A Deep Learning Approach with Enhanced Interpretability for Aerodynamic Engineering[J]. Complex & Intelligent Systems, 2024, 11(1): 3.
[20] ZAHN R, WEINER A, BREITSAMTER C.Prediction of Wing Buffet Pressure Loads Using a Convolutional and Recurrent Neural Network Framework[J]. CEAS Aeronautical Journal, 2024, 15(1): 61-77.
[21] LIU Z Y, HAN R K, ZHANG M, et al.An Enhanced Hybrid Deep Neural Network Reduced-Order Model for Transonic Buffet Flow Prediction[J]. Aerospace Science and Technology, 2022, 126: 107636.
[22] YANG Y J, LI R Z, ZHANG Y F, et al.Fast Buffet-Onset Prediction and Optimization Method Based on Pretrained Flowfield Prediction Model[J]. AIAA Journal, 2024, 62(8): 2979-2995.
[23] GOC K A, AGRAWAL R, BOSE S T, et al.Studies of Transonic Aircraft Flows and Prediction of Initial Buffet Using Large-Eddy Simulation[J]. Journal of Aircraft, 2025, 62(3): 530-550.
[24] YANG Y J, LI R Z, ZHANG Y F, et al.Buffet Onset Optimization for Supercritical Airfoils with Prior-Based Pressure Profile Prediction Model[C]// AIAA Sci Tech 2024 Forum. Orlando: AIAA, 2024.
[25] CANDON M J, LEVINSKI O, ALTAF A, et al.Aircraft Transonic Buffet Load Prediction Using Artificial Neural Networks[C]// AIAA Scitech 2019 Forum. San Diego: AIAA, 2019.
[26] 王雨润, 吴伟. 基于神经网络的直升机非线性模型辨识研究[J]. 飞行力学, 2024, 42(3): 33-39.
WANG Y R, WU W.Research on Nonlinear Helicopter Model Identification Base on Neural Network[J]. Flight Dynamics, 2024, 42(3): 33-39.
[27] 高健桐. 基于BP神经网络的直升机飞行状态识别[J]. 直升机技术, 2022(1): 25-28.
GAO J T.Helicopter Flight Status Recognition Based on BP Neural Network[J]. Helicopter Technique, 2022(1): 25-28.
[28] 邓晨, 陈功, 王文正, 等. 基于飞行试验和风洞试验数据的融合算法研究[J]. 空气动力学学报, 2022, 40(6): 45-50.
DENG C, CHEN G, WANG W Z, et al.Research on the Data Fusion Algorithm Based on Flight Test Data and Wind Tunnel Test Data[J]. Acta Aerodynamica Sinica, 2022, 40(6): 45-50.
[29] 徐子昱, 胡轩玮, 刘崇, 等. 大型舱段强度试验数字孪生超前预报方法[J]. 宇航学报, 2025, 46(9): 1915-1922.
XU Z Y, HU X W, LIU C, et al.Digital Twin-Based Advanced Forecasting Method for Strength Testing of Large-Scale Cabin Segments[J]. Journal of Astronautics, 2025, 46(9): 1915-1922.
[30] 何西旺. 面向局部非线性结构数字孪生的动力学降阶和在线优化方法[D]. 大连: 大连理工大学, 2024.
HE X W.Dynamic Reduction and Online Optimization Methods for Digital Twins of Local Nonlinear Structures[D]. Dalian: Dalian University of Technology, 2024.
[31] 娄能闯. 基于模态降阶的结构动力学拓扑优化方法及其程序实现[D]. 大连: 大连理工大学, 2024.
LOU N C.Structural Dynamic Topology Optimization Method Based on Mode order Reduction and Program implementation[D]. Dalian: Dalian University of Technology, 2024.
[32] 王紫浩, 李滚, 刘大伟, 等. 基于LSTM的超临界机翼抖振边界预测方法[J]. 空气动力学学报, 2024, 42(6): 56-65.
WANG Z H, LI G, LIU D W, et al.Buffeting Boundary Prediction Method of Supercritical Wing Using LSTM[J]. Acta Aerodynamica Sinica, 2024, 42(6): 56-65.
[33] 陈星伊, 李勐, 薛景锋, 等. 基于神经网络的飞机结构载荷预测技术研究进展[J/OL]. 航空工程进展, 2026, 17(0):1-8. (2025-11-19). https://link.cnki.net/urlid/61.1479.V.20251118.1014.002.
CHEN X Y, LI M, XUE J F, et al. Research Progress on Aircraft Structural Load Prediction Technology Based on Neural Networks[J/OL]. Advances in Aeronautical Science and Engineering, 2026,17(0):1-8. (2025-11-19). https://link.cnki.net/urlid/61.1479.V.20251118.1014.002.

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