Skip to main content
Log in

Modal Parameter Estimation of a Compliant Panel Using Phase-based Motion Magnification and Stereoscopic Digital Image Correlation

  • S.I. : Computer Vision and Scanning Laser Vibrometry Methods
  • Published:
Experimental Techniques Aims and scope Submit manuscript

Abstract

This paper demonstrates the use of broad-band phase based motion magnification (PMM) to improve the modal parameter estimation from high-speed stereoscopic digital image correlation (DIC). PMM is used as a diagnostic technique to investigate the free vibration response of a panel. The compliant panel, consisting of a thin polycarbonate sheet, forms a test section wall in a supersonic blow-down wind tunnel, where it is used to investigate supersonic fluid-structure interaction in the presence of shock wave boundary layer interaction. The panel is excited by an impact hammer and the transient deformation is captured using high-speed cameras. The original and motion-magnified images are input to a digital image correlation algorithm to calculate the out-of-plane deformation of the panel. The measured deformation is used to extract the modal parameters of the compliant panel. By using PMM as a preprocessing tool in a broad frequency band containing multiple structural modes, the signal to noise ratio of the measured deformation is improved. The use of PMM improves the estimated mode shapes, increasing the MAC value of the first mode compared to FEM predictions from 0.29 to 0.99. Motion magnification also improves the coherence between measured input force and panel deformation by up to 13% if suitable parameters are chosen.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data Availability

All data is available.

References

  1. Dolling DS (2001) Fifty years of shock-wave/boundary-layer interaction research: What next? AIAA J 39(8):1517–1531. https://doi.org/10.2514/2.1476

    Article  CAS  Google Scholar 

  2. Neet MC, Austin JM (2020) Effects of surface compliance on shock boundary layer interaction in the caltech mach 4 ludwieg tube. In: AIAA Scitech 2020 forum, pp 0816. https://doi.org/10.2514/6.2020-0816

  3. Peltier SJ, Rice BE, Szmodis J, Ogg DR, Hofferth JW, Sellers ME, Harris AJ (2019) Aerodynamic response to a compliant panel in mach 4 flow. In: AIAA Aviation 2019 forum, pp 3541. https://doi.org/10.2514/6.2019-3541

  4. Beberniss TJ, Ehrhardt D (2020) Visible light refraction effects on high-speed 3-dimensional digital image correlation measurement of a thin panel in mach 2 flow. In: International modal analysis conference 38

  5. Spottswood S, Eason T, Beberniss T (2012) Influence of shock-boundary layer interactions on the dynamic response of a flexible panel. In: ISMA 2012 International conference on noise and vibration engineering. Katholieke Universiteit Leuven Leuven, Belgium, pp 603–617

  6. Wadhwa N, Rubenstein M, Fredo D, Freeman WT (2013) Phase-based video motion processing. ACM Trans Graphics 32(4):80:1–80:10. https://doi.org/10.1145/2461912.2461966

    Article  Google Scholar 

  7. Fleet DJ, Jepson AD (1990) Computation of component image velocity from local phase information. Int J Comput Vis 5:77–104. https://doi.org/10.1007/BF00056772

    Article  Google Scholar 

  8. Harmanci YE, Gülan U, Holzner M, Chatzi E (2019) A novel approach for 3d-structural identification through video recording: magnified tracking. Sensors 19(5):1229. https://doi.org/10.3390/s19051229

    Article  Google Scholar 

  9. Molina-viedma ÁJ, López-alba E, Felipe-sesé L, Díaz FA (2019) Operational deflection shape extraction from broadband events of an aircraft component using 3D-DIC, in magnified images. Shock Vib 2019:9. https://doi.org/10.1155/2019/4039862

    Article  Google Scholar 

  10. Poozesh P, Sarrafi A, Mao Z, Avitabile P, Niezrecki C (2017) Feasibility of extracting operating shapes using phase-based motion magnification technique and stereo-photogrammetry. J Sound Vib 407:350–366. https://doi.org/10.1016/j.jsv.2017.06.003

    Article  Google Scholar 

  11. Sarrafi A, Mao Z (2017) Wind turbine blade damage detection via 3-dimensional phase-based motion estimation. In: The 11th international workshop on structural health monitoring. https://doi.org/10.12783/shm2017/14154

  12. Rohe DP (2020) Experimental modal analysis using phase quantities from phase-based motion processing and motion magnification. In: International modal analysis conference 38

  13. Eitner MA, Miller BG, Sirohi J, Tinney CE (2019) Operational modal analysis of a thin-walled rocket nozzle using phase-based image processing and complexity pursuit. In: Niezrecki C, Baqersad J, Di Maio D (eds) Rotating machinery, optical methods & scanning LDV methods. Springer International Publishing, pp 19–29. https://doi.org/10.1007/978-3-030-12935-4_3

  14. Simoncelli E, Freeman WT (1995) The steerable pyramid: a flexible architecture for multi-scale derivative computation. In: Proceedings of the 1995 international conference on image processing. https://doi.org/10.1109/ICIP.1995.537667

  15. Stone JV (2001) Blind source separation using temporal predictability. Neural Comput 13 (7):1559–1574. https://doi.org/10.1162/089976601750265009

    Article  CAS  Google Scholar 

  16. Antoni J, Castiglione R, Garibaldi L (2017) Interpretation and generalization of complexity pursuit for the blind separation of modal contributions. Mech Syst Signal Process 85:773–788. https://doi.org/10.1016/j.ymssp.2016.09.009

    Article  Google Scholar 

  17. Eitner MA, Sirohi J, Tinney CE (2019) Modal parameter estimation of a reduced-scale rocket nozzle using blind source separation. Measurement Sci Technol 30(9):095401. https://doi.org/10.1088/1361-6501/ab228f

    Article  CAS  Google Scholar 

  18. Yang Y, Dorn C, Mancini T, Talken Z, Kenyon G, Farrar C, Mascareñas D (2017) Blind identification of full-field vibration modes from video measurements with phase-based video motion magnification. Mech Syst Signal Process 85:567–590. https://doi.org/10.1016/j.ymssp.2016.08.041

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank Jeremy Jagodzinski for assistance with the measurements.

Funding

The work was supported by the National Science Foundation under award #1913587.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to M. Eitner.

Ethics declarations

Conflict of interests

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Code availability

Custom Matlab code and DAVIS digital image correlation software.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Eitner, M., Musta, M., Vanstone, L. et al. Modal Parameter Estimation of a Compliant Panel Using Phase-based Motion Magnification and Stereoscopic Digital Image Correlation. Exp Tech 45, 287–296 (2021). https://doi.org/10.1007/s40799-020-00393-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40799-020-00393-6

Keywords

Navigation