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A motion magnification application in video-based vibration measurement

  • Krzysztof HolakEmail author
Conference paper
Part of the Mechanisms and Machine Science book series (Mechan. Machine Science, volume 73)

Abstract

In the field of non-destructive testing (NDT) and Structural Health Monitoring (SHM), physical properties of objects’ are studied and their states evaluated through the measurement of vibration response and subsequent analysis with a use of physical models. The usual way of obtaining a vibration data are contact sensors placed on the structure. However, an application of these methods may be difficult and take a lot of time. Measurements are limited to a finite, usually small, set of points. The main advantage of cameras in vibration measurement is a possibility of having a dense grid of measurement points. However, a practical use of these methods is difficult, mainly because of the limited spatial resolution and image noise. An application of motion estimation using phased-based optical flow makes it possible to have a vision-based measurement of small amplitude vibrations. It may be used to magnify or attenuate motion amplitude in a given frequency band which may find an application in Structural Health Monitoring systems.

In the paper, an experimental investigation of phase-based motion magnification for non-contact vibration measurement is presented. Estimation of vibration frequencies of a free-free beam structure based on high-speed camera video signal has been carried out. Next, an application of motion magnification algorithm for restoration of band-limited video signal by increasing spatial magnitude of motion is shown. Finally, a preliminary test of single frequency component extraction based on video sequence of a structure excited by a white noise signal which may find an application in direct visualization of mode shapes has been presented.

Keywords

Motion Magnification Non-contact Measurements Vibration Measurements Image and Video Processing 

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Notes

Acknowledgments

This research was financed within the scope of the project LIDER/0103/L-9/2017 supported by the National Centre for Research and Development.

References

  1. 1.
    Kohut P., Kurowski P.: The integration of vision system and modal analysis for SHM application, Proceedings of the IMAC-XXIV: a conference & exposition on Structural dynamics, January 30–February 2, 2006 St. Louis, Missouri USA, pp. 1–8, (2006)Google Scholar
  2. 2.
    Kohut P., Kurowski P.: Application of modal analysis supported by 3D vision-based measurements, Journal of Theoretical and Applied Mechanics; 47 (4), 855–870, (2009)Google Scholar
  3. 3.
    Mendrok K., Uhl T.: Modal filtration for damage detection and localization, Proceedings of the Fourth European Workshop Structural Health Monitoring 2008, DeStech Publications, Inc., Lancaster, Pennsylvania, USA, pp. 929–936, (2008)Google Scholar
  4. 4.
    Mendrok K., Uhl T.: Experimental verification of the damage localization procedure based on modal filtering, Structural Health Monitoring; 10(2), 157–171, (2011)Google Scholar
  5. 5.
    Javh J., Slavič J., Boltežar M., The subpixel resolution of optical-flow-based modal analysis, Mechanical Systems and Signal Processing 88, pp. 89-99, (2017)Google Scholar
  6. 6.
    Javh J., Slavič J., Boltežar M., High frequency modal identification on noisy high-speed camera data, Mechanical Systems and Signal Processing 98, pp. 344-351, (2018)Google Scholar
  7. 7.
    Poozesh P., Sarrafi A., Mao Z., Niezrecki C., Modal parameter estimation from optically measured data using a hybrid output-only system identification method, Measurement 110 pp. 134-145, (2017)Google Scholar
  8. 8.
    Patil K., Srivastava V., Baqersad J., A multi-view optical technique to obtain mode shapes of structures, Measurement 122, pp. 358-367, (2018)Google Scholar
  9. 9.
    Pieczonka L., Ambrozinski L., Staszewski W.J., Barnoncel D., Pérès P., Damage detection in composite panels based on mode-converted Lamb waves sensed using 3D laser scanning vibrometer, Optics and Lasers in Engineering 99, pp. 80-87, (2017)Google Scholar
  10. 10.
    Ce L., Torralba A., Freeman W.T., Durand F., Adelson E.: Motion magnification, ACM Trans. Graph., 24, 519–526, (2005)Google Scholar
  11. 11.
    W H.-Y.: Eulerian video processing and medical applications. Master’s thesis, Massachusetts Institute of Technology, (2012)Google Scholar
  12. 12.
    Simoncelli E. P., Freeman W. T.: The steerable pyramid: a flexible architecture for multi-scale derivative computation, In Proceedings of the 1995 International Conference on Image Processing, Vol. 3, pp. 3444, Washington, DC, USA, (1995)Google Scholar
  13. 13.
    Wadhwa N., Rubinstein M., Durand F., Freeman W. T.: Riesz Pyramids for Fast Phase-Based Video Magnification, IEEE International Conference on Computational Photography (ICCP), (2014)Google Scholar
  14. 14.
    Xue T., Rubinstein M., Wadhwa N., Levin A., Durand Fr., Freeman W. T.: Refraction Wiggles for Measuring Fluid Depth and Velocity from Video, Proc. of European Conference on Computer Vision (ECCV), (2014).Google Scholar
  15. 15.
    Davis A., Bouman K. L., Chen J.G., Rubinstein M., Durand F., Freeman W.T., Visual Vibrometry: Estimating Material Properties from Small Motions in Video, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), (2015)Google Scholar
  16. 16.
    Poozesh P., Sarrafi A., Mao Z., Avitabile P., Niezrecki C., Feasibility of extracting operating shapes using phase-based motion magnification technique and stereo-photogrammetry, Journal of Sound and Vibration 407, pp. 350-366, (2017)Google Scholar
  17. 17.
    Poozesh P., Sarrafi A., Mao Z., Niezrecki C., Mode extraction on wind turbine blades via phase-based video motion estimation, Smart Materials and Nondestructive Evaluation for Energy Systems, (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.AGH University of Science and Technology, Department of Robotics and MechatronicsKrakowPoland

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