Skip to main content
SpringerLink
Log in

Modal parameter identification in atmospheric turbulence excitation flutter test based on Hilbert-Huang transform

  • Original Article
  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

In flutter tests, particularly in wind tunnel experiments, the aircraft model is generally excited by atmospheric turbulence, which increases the difficulty in precisely identifying the modal parameters. To estimate the modal parameters under turbulence excitation for flutter boundary prediction, a technique was developed and evaluated depending on the Hilbert-Huang transform in this paper. The results of simulated flutter cases show that the developed technique can identify modal frequencies more precisely than the modal damping ratio, while the estimation of the modal damping ratio is quite good. Finally, in a wind tunnel flutter test, good flutter boundaries were predicted in advance by using the modal parameters identified from the turbulence response at low airspeeds.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

x(t):

Response

P :

Cauchy principal value

A (t):

Instantaneous amplitude

θ(t):

Instantaneous phase

ω(t):

Instantaneous frequency

ω j :

jth modal frequency

ζ j :

jth modal damping ratio

ω j :

jth modal frequency

V :

Airspeed

B :

Polynomial coefficient

C :

Polynomial coefficient

D :

Polynomial coefficient

FM :

Flutter margin

F z :

Flutter criterion

References

  1. E. H. Dowell et al., A Modern Course in Seroelasticity, Kluwer Academic, Norwell, MA (2005).

    Google Scholar 

  2. A. Kayran, Flight flutter testing and aeroelastic stability of aircraft, Aircraft Engineering and Aerospace Technology, 79(5) (2007) 494–506.

    Article  Google Scholar 

  3. R. Huang, Y. H. Zhao and H. Y. Hu, Wind-tunnel tests for active flutter control and closed-loop flutter identification, AIAA J., 54(7) (2016) 2089–2099.

    Article  Google Scholar 

  4. Y. Li and L. Zhou, A flutter boundary prediction method for the three-dof wing, J. of Vibroengineering, 17(8) (2015) 4507–4516.

    Google Scholar 

  5. N. H. Zimmerman and J. T. Weissenburger, Prediction of flutter onset speed based on flight testing at subcritical speeds, J. of Aircraft, 1(4) (1964) 190–202.

    Article  Google Scholar 

  6. H. Torii and Y. Matsuzaki, Flutter margin evaluation for discrete-time systems, J. of Aircraft, 38(1) (2001) 42–47.

    Article  Google Scholar 

  7. D. Poirel, S. Dunn and J. Porter, Flutter-margin method accounting for modal parameter uncertainties, J. of Aircraft, 42(5) (2005) 1236–1243.

    Article  Google Scholar 

  8. J. Heeg, Stochastic characterization of flutter using historical wind tunnel data, 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Honolulu, Hawaii, AIAA 2007-1769 (2007).

  9. R. Lind, Flutter margins for multimode unstable couplings with associated flutter confidence, J. of Aircraft, 46(5) (2009) 1563–1568.

    Article  Google Scholar 

  10. J. Zeng and S. L. Kukreja, Flutter prediction for flight/wind-tunnel flutter test under atmospheric turbulence excitation, J. of Aircraft, 50(6) (2013) 1696–1709.

    Article  Google Scholar 

  11. B. Zhang, Z. K. Shi and J. J. Li, Flight flutter modal parameters identification with atmospheric turbulence excitation based on wavelet transformation, Chinese J. of Aeronautics, 20(5) (2007) 394–401.

    Article  Google Scholar 

  12. Y. Li, L. Zhou and B. C. Yang, A flutter boundary prediction technique under atmospheric turbulence excitation, Asia-Pacific International Symposium on Aerospace Technology, Cairns, Australia (2015) 137–147.

  13. Y. Li and L. Zhou, A flutter boundary prediction technique based on atmospheric turbulence excitation responses, AIAA Aviation 2016, AIAA Atmospheric Flight Mechanics Conference, Washington, D.C. AIAA 2016–3858 (2016).

  14. N. E. Huang, M. J. Brennert and L. Salvino, Hilbert-Huang transform stability spectral analysis applied to flutter flight test data, AIAA J., 44(4) (2006) 772–786.

    Article  Google Scholar 

  15. Z. H. Wu and N. E. Huang, Ensemble empirical mode decomposition: a noise assisted data analysis method, Advances in Adaptive Data Analysis, 1(1) (2009) 1–41.

    Article  Google Scholar 

  16. G. H. James, T. G. Garne and J. P. Lauffer, The natural excitation technique for modal parameter extraction from operating structures, Modal Analysis: J Analytical and Experimental Modal Analysis, 10(4) (1995) 260–277.

    Google Scholar 

  17. H. Moncayo, J. Marulanda and P. Thomson, Identification and monitoring of modal parameters in aircraft structures using the natural excitation technique (NExT) combined with the eigensystem realization algorithm, J. of Aerospace Engineering, 23(2) (2010) 99–104.

    Article  Google Scholar 

  18. M. Chang and S. N. Pakzad, Modified natural excitation technique for stochastic modal identification, J. of Structural Engineering, 139(10) (2013) 1753–1762.

    Article  Google Scholar 

  19. S. C. Su, K. L. Wen and N. E. Huang, A new dynamic building health monitoring method based on the Hilbert-Huang transform, Terrestrial Atmospheric and Oceanic Sciences, 25(3) (2013) 289–318.

    Article  Google Scholar 

  20. J. N. Yang, Y. Lei, S. W. Pan and N. E. Huang, System identification of linear structures based on Hilbert-Huang spectral analysis, part 1: normal modes, Earthquake Engineering and Structural Dynamics, 32(9) (2003) 1443–1467.

    Article  Google Scholar 

  21. N. E. Huang et al., Applications of Hilbert-Huang transform to non-stationary financial time series analysis, Applied Stochastic Models in Business and Industry, 19(3) (2003) 245–268.

    Article  MathSciNet  Google Scholar 

  22. T. K. Sarkar, S. Park, J. Koh and S. M. Rao, Application of the matrix pencil method for estimating the SEM (singularity expansion method) poles of source-free transient responses from multiple look directions, IEEE Transactions on Antennas and Propagation, 48(4) (2000) 612–618.

    Article  Google Scholar 

Download references

Acknowledgments

This research is partially supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (20KJD130001, 20KJB410005) and the Science Foundation of Nanjing Vocational University of Industry Technology (YK19-03-01, YK19-03-04).

Author information

Authors and Affiliations

  1. School of Aeronautic Engineering, Nanjing Vocational University of Industry Technology, Nanjing, 210023, China

    Yang Li & Cheng Cheng

  2. State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Li Zhou

Authors
  1. Yang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cheng Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Li Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yang Li.

Additional information

Yang Li received his Ph.D. in Engineering from Nanjing University of Aeronautics and Astronautics (NUAA) in 2018. He is now an Associate Professor in Nanjing Vocational University of Industry Technology. His research interest focuses mainly on signal processing technology, modal parameter identification, structural health monitoring and flutter boundary prediction technique.

Li Zhou received her Ph.D. from Hong Kong University of Science and Technology in 2002. Currently, she is a Professor in Nanjing University of Aeronautics and Astronautics. Her main research interests are aeroelasticity and structural health monitoring.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Y., Cheng, C. & Zhou, L. Modal parameter identification in atmospheric turbulence excitation flutter test based on Hilbert-Huang transform. J Mech Sci Technol 36, 3217–3226 (2022). https://doi.org/10.1007/s12206-022-0603-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-022-0603-y

Keywords

Search

Navigation