ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Modal parameter estimation based on reconstruction of digital twin sweep data in flutter flight test
Received date: 2024-12-03
Revised date: 2025-05-16
Accepted date: 2025-06-13
Online published: 2025-07-03
Supported by
Defense Industrial Technology Development Program(JCKY2019205A006)
During the digital twinning flight test， high-quality flight test data is used to fuse the digital model with the actual flight test data. In order to eliminate the effect of turbulence excitation and improve the accuracy of subsequent signal processing conclusions， a new method for estimating swept frequency response modal parameters is proposed based on the reconstruction of flutter flight test digital twinning data. First， the measured response is reconstructed in the time domain， and it is separated into two parts： the structural response caused purely by the swept and the structural response excited by turbulence. Then， the subspace algorithm is used to identify the modal parameters of the two separated response data respectively. Finally， the proposed method is verified by simulation and measured data. The results show that the proposed method can obtain high-quality test flight data that meets the requirements of virtual-real fusion in digital twins， after data reconstruction， more accurate and reliable identification results can be obtained； at the same time， due to the separation of turbulent response and the unique broadband characteristics of turbulence， the method can also effectively identify modes outside the swept frequency range.
Jialiang HU , Jiangpeng WU , Sixu HUO , Yidi GAO , Hua ZHENG . Modal parameter estimation based on reconstruction of digital twin sweep data in flutter flight test[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2025 , 46(19) : 531602 -531602 . DOI: 10.7527/S1000-6893.2025.31602
| [1] | MENDEZ C， LE CLAINCHE S， MORENO-RAMOS R， et al. A new automatic， very efficient method for the analysis of flight flutter testing data［J］. Aerospace Science and Technology， 2021， 114： 106749. |
| [2] | DJOJODIHARDJO H. Aeroelastic experiments-ground vibration and flight flutter test case studies［M］∥Introduction to Aeroelasticity. Singapore： Springer Nature Singapore， 2023： 621-653. |
| [3] | WANG J H， RAMIREZ-MENDOZA R A. Direct data-driven strategy for closed-loop aircraft flutter test［J］. Aircraft Engineering and Aerospace Technology， 2023， 95（5）： 749-756. |
| [4] | LI L N， ASLAM S， WILEMAN A， et al. Digital twin in aerospace industry： A gentle introduction［J］. IEEE Access， 2021， 10： 9543-9562. |
| [5] | ALLEN B D. Digital twins and living models at NASA［EB/OL］. NASA Technical Reports Server.（2021-11-01）［2024-12-01］. . |
| [6] | LEI M. Research on structural response modeling method for flutter flight test under sweep excitation of control surface based on Volterra series［C］∥2024 3rd International Symposium on Aerospace Engineering and Systems （ISAES）. Piscataway： IEEE Press， 2024： 454-458. |
| [7] | DUAN S Q， ZHENG H. Model parameter estimations of the multi-channel turbulence response from flutter flight tests based on autoregressive spectra［J］. Journal of Low Frequency Noise Vibration and Active Control， 2023， 42（1）： 173-191. |
| [8] | 唐炜， 史忠科. 扫频激励下的飞机颤振模态参数小波辨识研究［J］. 振动与冲击， 2009， 28（2）： 172-177， 209. |
| TANG W， SHI Z K. Wavelet identification of flight flutter modal parameters under sweep excitation［J］. Journal of Vibration and Shock， 2009， 28（2）： 172-177， 209 （in Chinese）. | |
| [9] | PEETERS B， TROYER T D， GUILLAUME P， et al. In-flight modal analysis—a comparison between sweep and turbulence excitation［C］∥Proceedings of the ISMA 2006 International Conference on Noise and Vibration Engineering. Leuven： KU Leuven，2006：1627-1642 |
| [10] | DUAN S Q， ZHENG H， ZHANG Z W， et al. Model parameter estimation method on multichannel structural response from turbulence flutter test［J］. International Journal of Aerospace Engineering， 2022， 2022（1）： 3343675. |
| [11] | DUAN S Q， ZHENG H， YU J G， et al. Modal parameter estimation of turbulence response based on self-attention generative model［J］. Journal of Vibration and Control， 2024， 30（15-16）： 3296-3309. |
| [12] | SHOKRAVI H， SHOKRAVI H， BAKHARY N， et al. Health monitoring of civil infrastructures by subspace system identification method： An overview［J］. Applied Sciences， 2020， 10（8）： 2786. |
| [13] | XU M Q， AU F T K， WANG S Q， et al. Operational modal analysis under harmonic excitation using Ramanujan subspace projection and stochastic subspace identification［J］. Journal of Sound and Vibration， 2023， 545： 117436. |
| [14] | COX P B， TóTH R. Linear parameter-varying subspace identification：A unified framework［J］. Automatica， 2021， 123： 109296. |
| [15] | ELKAFAFY M， PEETERS B. Robust identification of stable MIMO modal state space models［C］∥Topics in Modal Analysis & Parameter Identification， Volume 8. Cham： Springer International Publishing， 2022： 81-95. |
| [16] | YOU J Z， HUANG C， ZHANG H. Combined invariant subspace & frequency-domain subspace method for identification of discrete-time MIMO linear systems［J］. Systems & Control Letters， 2023， 181： 105641. |
| [17] | ZHANG E H， WU D， SHAN D S. Novel tensor subspace system identification algorithm to identify time-varying modal parameters of bridge structures［J］. Structural Health Monitoring， 2022， 21（4）： 1541-1554. |
| [18] | WANG C， HU M H， JIANG Z N， et al. A modal parameter identification method based on improved covariance-driven stochastic subspace identification［J］. Journal of Engineering for Gas Turbines and Power， 2020， 142（6）： 061005. |
| [19] | LIN C S， WU Y X. Response-only parametric estimation of structural systems using a modified stochastic subspace identification technique［J］. Applied Sciences， 2021， 11（24）： 11751. |
| [20] | O’CONNELL B J， ROGERS T J. A robust probabilistic approach to stochastic subspace identification［J］. Journal of Sound and Vibration， 2024， 581： 118381. |
| [21] | ISMAIL U， ULUC S， MERT A M， et al. Frequency-domain subspace identification of linear time-periodic （LTP） systems［J］. IEEE Transactions on Automatic Control， 2019， 64（6）： 2529-2536. |
| [22] | TRONCI E M， DE ANGELIS M， BETTI R， et al. Multi-stage semi-automated methodology for modal parameters estimation adopting parametric system identification algorithms［J］. Mechanical Systems and Signal Processing， 2022， 165： 108317. |
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