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A generalised force equivalence-based modelling method for a dry wind-tunnel flutter test system

Published online by Cambridge University Press:  09 March 2021

Z. Zhang ,
B. Gao ,
J. Wang ,
D. Xu ,
G. Chen Open the ORCID record for G. Chen [Opens in a new window]  and
W. Yao
Z. Zhang
Affiliation:
Science and Technology on Reliability and Environment Engineering Laboratory, Beijing Institute of Structure and Environment Engineering, Beijing100076, China
B. Gao
Affiliation:
Science and Technology on Reliability and Environment Engineering Laboratory, Beijing Institute of Structure and Environment Engineering, Beijing100076, China
J. Wang
Affiliation:
Science and Technology on Reliability and Environment Engineering Laboratory, Beijing Institute of Structure and Environment Engineering, Beijing100076, China
D. Xu
Affiliation:
Shaanxi Province Key Laboratory for Service Environment and Control of Advanced Aircraft school of Aerospace Engineering, Xi’an Jiaotong University, Xi’an710049, China State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi’an Jiaotong University, Xi’an710049, China
G. Chen*
Affiliation:
Shaanxi Province Key Laboratory for Service Environment and Control of Advanced Aircraft school of Aerospace Engineering, Xi’an Jiaotong University, Xi’an710049, China State Key Laboratory for Strength and Vibration of Mechanical Structures, Xi’an Jiaotong University, Xi’an710049, China
W. Yao
Affiliation:
Faculty of Computing Engineering and Media, De Montfort University, Queens Building The Gateway, Leicester, LE1 9BH, UK
*
[email protected]
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Abstract

Dry wind-tunnel (DWT) flutter test systems model the unsteady distributed aerodynamic force using various electromagnetic exciters. They can be used to test the aeroelastic and aeroservoelastic stability of smart aircraft or high-speed flight vehicles. A new parameterised modelling method at the full system level based on the generalised force equivalence for DWT flutter systems is proposed herein. The full system model includes the structural dynamic model, electromechanical coupling model and fast aerodynamic computation model. An optimisation search method is applied to determine the best locations for measurement and excitation by introducing Fisher’s information matrix. The feasibility and accuracy of the proposed system-level numerical DWT modelling method have been validated for a plate aeroelastic model with four exciters/transducers. The effects of key parameters including the number of exciters, the control time delay, the noise interference and the electrical parameters of the electromagnetic exciter model have also been investigated. The numerical and experimental results indicate that the proposed modelling method achieves good accuracy (with deviations of less than 1.5% from simulations and 4.5% from experimental test results for the flutter speed) and robust performance even in uncertain environments with a 10% noise level.

Keywords

AeroelasticityDry wind-tunnel systemGeneralised forceControl time delayOptimisation
Type
Research Article
Information
The Aeronautical Journal , Volume 125 , Issue 1286 , April 2021 , pp. 720 - 741
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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Footnotes

A version of this paper was first presented at the International Symposium on Smart Aircraft, Xi’an, China, 2019.

References

REFERENCES

Dowell, E., Bendiksen, O., Edwards, J. and Strganac, J. Transonic Nonlinear Aeroelasticity. John Wiley & Sons, Ltd, 2010.CrossRefGoogle Scholar
Schuster, D.M., Liu, D.D. and Huttsell, L.J.L.J. Computational aeroelasticity: success, progress, challenge, J. Aircr, 2003, 40, pp 843–856.CrossRefGoogle Scholar
Yang, N., Wang, N., Zhang, X. and Liu, W. Nonlinear flutter wind tunnel test and numerical analysis of folding fins with freeplay nonlinearities. Chin. J. Aeronaut., 2016, 29, (1), pp 144–59.CrossRefGoogle Scholar
Xuan, C.W., Han, J.L., Zhang, B., Yun, H.W. and Chen, X.M. Hypersonic flutter and flutter suppression system of a wind tunnel model. Chin. J. Aeronaut., 2019, 32, (9), pp 2121–2132.CrossRefGoogle Scholar
Kearns, J.P. Flutter simulator. AD650981, 1967.Google Scholar
Pan, S.X. and Qi, P.Q. Studies on ground thermal flutter simulation test. Struct. Eng. Environ., 1984, 11, (2), pp 10–14.Google Scholar
Naryzhny, A.G., Pedora, A. and Smyslov, V.I. Vibration tests with airflow simulation in the aeroelastic investigations on dynamically scaled models. Uchenye Zapiski TsAGI, 2001, V32, pp 1–2.Google Scholar
Zeng, J., Kingsbury, D.W., Ritz, E., Chen, P.C., Lee, D.H. and Mignolet, M.l. GVT-based ground flutter test without wind tunnel. 52nd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Colorado Denver, 2011, AIAA 2011-1942.CrossRefGoogle Scholar
Wu, Z.G., Chu, L.F., Yuan, R.Z., Yang, C. and Tang, C.H. Studies on aeroservoelasticity semi-physical simulation test for missiles. Sci. China Technol. Sci., 2012, 55, (9), pp 2482–2488.CrossRefGoogle Scholar
Xu, Y.T., Wu, Z.G. and Yang, C. Simulation of the unsteady aerodynamic forces for ground flutter simulation test. Acta Aeronaut. Astronaut. Sin., 2012, 33, (11), pp 1947–1957.Google Scholar
Song, Q.Z. Multi exciting force control system design based on robust control. Northwestern Polytech. Univ., 2014.Google Scholar
Zhang, R.J., Wu, Z.G. and Yang, C. Dynamic stiffness testing-based flutter analysis of a fin with an actuator. Chin. J. Aeronaut., 2015, 28, (5), pp 1400–1407.CrossRefGoogle Scholar
Wu, Z.G., Ma, C.J. and Yang, C. New approach to the ground flutter simulation test. J. Aircr., 2016, 53, (5), pp 1575–1580.CrossRefGoogle Scholar
Song, Q.Z., Yang, Z.C. and Wang, W. Robust control of exciting force for vibration control system with multi-exciters. Sci. China Technol. Sci., 2013, 56, (10), pp 2516–2524.CrossRefGoogle Scholar
Overschee, V.P. and Moor, D.B. Subspace identification of linear systems: Theory, Implementation, Applications. Kluwer Academic Publishers, 1996, Netherlands.CrossRefGoogle Scholar
Favoreel, W., Moor, D.B. and Overschee, V.P. Subspace state space system identification for industrial processes. J. Process Control, 2000, 10, pp 149–155.CrossRefGoogle Scholar
Li, Y.F., Su, H.Y. and Yan, J. A review of subspace model identification method. J. Chem. Ind. Eng., 2006, 57, (3), pp 473–479.Google Scholar
Tang, W., Wu, J. and Shi, Z.K. Identification of reduced-order model for an aeroelastic system from flutter test data. Chin. J. Aeronaut., 2017, 30 (1), pp 337–347.CrossRefGoogle Scholar
Zhang, Z., Zhang, Z.P., Li, H.B., Ren, F. and Han, L. Measurement method of interface force between shaker and load for swept sine vibration test. J. Vib. Measure. Diagnosis, 2017, 37 (1), pp 158–162.Google Scholar
Gao, Y.N., Tan, S.G. and Pu, L.D. Research on factors affecting precision of rational function aerodynamic approximation based on minimum-state method. Aeronaut. Sci. Technol., 2014, 25 (03), pp 54–58.Google Scholar
Cheng, J.Q., Yan, W.M., Chen, Y.J., He, H.X. and Zhang, Y.B. Optimal sensor placement for bridge structure based on improved effective independence. J. Vib. Measure. Diagnosis, 2012, 32 (5), pp 812–816.Google Scholar
Kammer, D.C. Sensor placement for on-orbit modal identification and correlation of large space structures. J. Guid. Control Dyn., 1991, 14 (2), pp 251–259.CrossRefGoogle Scholar