Response prediction and excitation optimization of flight flutter tests based on a LPV model

被引：0

作者：

Kou B. ^{[1
]}

Lei M. ^{[1
]}

Lu X. ^{[1
]}

机构：

[1] Aircraft Flight Test Technology Institute, Chinese Flight Test Establishment, Xi'an

来源：

Zhendong yu Chongji/Journal of Vibration and Shock | 2022年 / 41卷 / 02期

关键词：

Excitation optimization; Flight flutter test; Response prediction; State-space model interpolation;

D O I：

10.13465/j.cnki.jvs.2022.02.013

中图分类号：

学科分类号：

摘要：

For satisfying the requirements of real-time monitoring and flight test efficiency in flight flutter tests, a local linear dynamic-pressure-varying model was established based on the frequency domain subspace identification method with pole constraint and the state-space interpolation algorithm. The process of velocity extension in the flight flutter tests combined with model iteration was designed, and the structural response prediction and excitation optimization using flight test data were realized. The accuracy of predicted responses and the effectiveness of excitation optimization were verified by simulation examples and actual flight test data. The results show that the accuracy of the predicted responses is gradually improved along with the accumulation of flight test data, and the prediction values can meet the needs of engineering real-time monitoring, compared with the actual flight test responses. The optimized excitation can improve the signal-to-noise ratio of responses and avoid the over-limit of responses, which can improve the efficiency of flight flutter tests. © 2022, Editorial Office of Journal of Vibration and Shock. All right reserved.

引用

页码：103 / 112

页数：9

共 21 条

[1] JU Lifeng, LIU Yu, LIANG Haizhou, The compositive application and investigation of many kinds of excitation methods in the flutter flight test to the X type airplane, Journal of Vibration and Shock, 35, 7, pp. 152-155, (2016)
[2] LEI Ming, YANG Fei, HUO Xingli, Research of response simulation in civil aircraft aeroservoelastic flight test excitation, China Measurement & Test, 45, 6, pp. 146-152, (2019)
[3] LEI Ming, LU Xiaodong, HUO Xingli, Simulation method of control surface impulse response of aircraft flutter flight test, Equipment Environmental Engineering, 17, 9, pp. 48-53, (2020)
[4] MCKELVEY T, AKCAY H., An efficient frequency domain state-space identification algorithm, Proceedings of 1994 33rd IEEE Conference on Decision and Control, (1994)
[5] MCKELVEY T., Frequency weighted subspace based system identification in the frequency domain, Proceedings of 1995 34th IEEE Conference on Decision and Control, (1995)
[6] PINTELON R., Frequency domain subspace system identification using non-parametric noise models, Proceedings of the 40th IEEE Conference on Decision and Control, (2001)
[7] TANG Wei, SHI Zhongke, Subspace identification in frequency-domain applied to aircraft flutter modal parameter identification, Acta Aeronautica et Astronautica Sinica, 28, 5, pp. 1175-1180, (2007)
[8] CAIGNY J, PINTELON R, CAMINO J F, Et al., Interpolated modeling of LPV systems based on observability and controllability, IFAC Proceedings Volumes, 45, 16, pp. 1773-1778, (2012)
[9] (2018)
[10] BALDELLI D H, JIE Z, LIND R, Et al., Flutter-prediction tool for flight-test-based aeroelastic parameter-varying models, Journal of Guidance Control and Dynamics, 32, 1, pp. 158-171, (2009)

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