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JRM Vol.31 No.5 pp. 671-685
doi: 10.20965/jrm.2019.p0671
(2019)

Paper:

A Tandem Marker-Based Motion Capture Method for Dynamic Small Displacement Distribution Analysis

Zulhaj Aliansyah*1, Kohei Shimasaki*2, Mingjun Jiang*1, Takeshi Takaki*1, Idaku Ishii*1, Hua Yang*3, Chikako Umemoto*4, and Hiroshi Matsuda*5

*1Department of System Cybernetics, Graduate School of Engineering, Hiroshima University
1-4-1 Kagamiyama, Higashi-Hiroshima-shi, Hiroshima 739-8527, Japan

*2Digital Modozukuri (Manufacturing) Education and Research Center, Hiroshima University
3-10-32 Kagamiyama, Higashi-Hiroshima-shi, Hiroshima 739-0046, Japan

*3School of Mechanical Science and Engineering, Huazhong University of Science and Technology
1037 Luoyu Road, Wuhan, Hebei 430074, China

*4Keisoku Research Consultant Co.
1-665-1 Fukuda, Higashi-ku, Hiroshima-shi, Hiroshima 732-0029, Japan

*5Department of Structural Engineering, Nagasaki University
1-14 Bunkyo-machi, Nagasaki-shi, Nagasaki 852-8521, Japan

Received:
November 2, 2018
Accepted:
July 31, 2019
Published:
October 20, 2019
Keywords:
structure health monitoring, high-speed vision, dynamic deflection measurement, vibration analysis, retroreflective markers
Abstract

This study proposes a novel vision-based measurement method to capture small dynamic displacements at many points on a large-scale structure. The measurement points are aligned in the depth direction so that all points are observable in a single field of view with a high power zoom lens. To cope with insufficient incident light and lens blur when capturing video in a limited depth of field with large magnification, our method used highly retroreflective cubes as markers, combined with a strong coaxial lighting device for measuring image displacements with a tandem-layout in images. We conducted experiments to measure dynamic displacements of a 4 m long truss bridge model, and 18 corner cubes were attached as retroreflective markers. 752×2048 images were captured with a coaxial lighting device at 240 fps. The experimental results show that the deformation of the bridge model, its resonant frequencies, and mode shapes at a frequency of dozens of Hz can be determined by analyzing images captured from a single camera view.

Visual multiple small displacements sensing

Visual multiple small displacements sensing

Cite this article as:
Z. Aliansyah, K. Shimasaki, M. Jiang, T. Takaki, I. Ishii, H. Yang, C. Umemoto, and H. Matsuda, “A Tandem Marker-Based Motion Capture Method for Dynamic Small Displacement Distribution Analysis,” J. Robot. Mechatron., Vol.31 No.5, pp. 671-685, 2019.
Data files:
References
  1. [1] P. C. Chang, A. Flatau, and S. C. Liu, “Review Paper: Health Monitoring of Civil Infrastructure,” Structural Health Monitoring, Vol.2, No.3, pp. 257-267, 2003.
  2. [2] C. R. Farrar and K. Worden, “An introduction to structural health monitoring,” Philosophical Trans. of the Royal Society A, Vol.365, No.1851, pp. 303-315, 2007.
  3. [3] O. S. Salawu and C. Williams, “Review of full-scale dynamic testing of bridge structures,” Engineering Structures, Vol.17, No.2, pp. 113-121, 1995.
  4. [4] P. Paultre, J. Proulx, and M. Talbot, “Dynamic testing procedures for highway bridges using traffic loads,” J. of Structural Engineering, Vol.121, No.2, pp. 362-376, 1995.
  5. [5] Q. Qin, H. B. Li, L. Z. Qian, and C.-K. Lau, “Modal Identification of Tsing Ma Bridge by Using Improved Eigensystem Realization Algorithm,” J. of Sound and Vibration, Vol.247, No.2, pp. 325-341, 2001.
  6. [6] K.-T. Park, S.-H. Kim, H.-S. Park, and K.-W. Lee, “The determination of bridge displacement using measured acceleration,” Engineering Structures, Vol.27, No.3, pp. 371-378, 2005.
  7. [7] C. Rainieri and G. Fabbrocino, “Automated output-only dynamic identification of civil engineering structures,” Mechanical Systems and Signal Processing, Vol.24, No.3, pp. 678-695, 2010.
  8. [8] C. J. Brown, R. Karuma et al., “Monitoring of structures using the global positioning system,” Proc. of the Institution of Civil Engineers – Structures and Buildings, Vol.134, No.1, pp. 97-105, 1999.
  9. [9] G. W. Roberts, X. Meng, and A. H. Dodson, “Integrating a Global Positioning System and Accelerometers to Monitor the Deflection of Bridges,” J. of Surveying Engineering, Vol.130, No.2, pp. 65-72, 2004.
  10. [10] A. Nickitopoulou, K. Protopsalti, and S. Stiros, “Monitoring dynamic and quasi-static deformations of large flexible engineering structures with GPS: Accuracy, limitations and promises,” Engineering Structures, Vol.28, No.10, pp. 1471-1482, 2006.
  11. [11] X. Meng, A. H. Dodson, and G. W. Roberts, “Detecting bridge dynamics with GPS and triaxial accelerometers,” Engineering Structures, Vol.29, No.11, pp. 3178-3184, 2007.
  12. [12] H. Xia, G. De Roeck, N. Zhang, and J. Maeck, “Experimental analysis of a high-speed railway bridge under Thalys trains,” J. of Sound and Vibration, Vol.268, No.1, pp. 103-113, 2003.
  13. [13] H. H. Nassif, M. Gindy, and J. Davis, “Comparison of laser Doppler vibrometer with contact sensors for monitoring bridge deflection and vibration,” NDT & E Int., Vol.38, No.3, pp. 213-218, 2005.
  14. [14] J. L. Valin, E. Gonçalves, F. Palacios, and J. R. Pérez, “Methodology for analysis of displacement using digital holography,” Optics and Lasers Engineering, Vol.43, No.1, pp. 99-111, 2005.
  15. [15] F. Casciati and L. Wu, “Local positioning accuracy of laser sensors for structural health monitoring,” Structural Control Health Monitoring, Vol.20, No.5, pp. 728-739, 2013.
  16. [16] M. Pieraccini, M. Fratini, F. Parrini, G. Macaluso, and C. Atzeni, “High-speed CW step-frequency coherent radar for dynamic monitoring of civil engineering structures,” Electronics Letters, Vol.40, No.14, pp. 907-908, 2004.
  17. [17] C. Gentile and G. Bernardini, “An interferometric radar for non-contact measurement of deflections on civil engineering structures: laboratory and full-scale tests,” Structure and Infrastructure Engineering, Vol.6, No.5, pp. 521-534, 2010.
  18. [18] G. A. Stephen, J. M. W. Brownjohn, and C. A. Taylor, “Measurements of static and dynamic displacement from visual monitoring of the Humber Bridge,” Engineering Structures, Vol.15, No.3, pp. 197-208, 1993.
  19. [19] P. Olaszek, “Investigation of the dynamic characteristic of bridge structures using a computer vision method,” Measurement, Vol.25, No.3, pp. 227-236, 1999.
  20. [20] A. M. Wahben, J. P. Caffrey, and S. F. Masri, “A vision-based approach for the direct measurement of displacements in vibrating systems,” Smart Materials and Structures, Vol.12, No.5, pp. 785, 2003.
  21. [21] J. J. Lee and M. Shinozuka, “Real-Time Displacement Measurement of a Flexible Bridge Using Digital Image Processing Techniques,” Experimental Mechanics, Vol.46, No.1, pp. 105-114, 2006.
  22. [22] P. Kohut, K. Holak, T. Uhl, Ł. Ortyl, T. Owerko, P. Kuras, and R. Kocierz, “Monitoring of a civil structure’s state based on noncontact measurements,” Structural Health Monitoring, Vol.12, Nos.5-6, pp. 411-429, 2013.
  23. [23] D. Ribeiro, R. Calçada, J. Ferreira, and T. Martins, “Non-contact measurement of the dynamic displacement of railway bridges using an advanced video-based system,” Engineering Structures, Vol.75, pp. 164-180, 2014.
  24. [24] D. Feng, M. Feng, E. Ozer, and Y. Fukuda, “A vision-based sensor for noncontact structural displacement measurement,” Sensors, Vol.15, No.7, pp. 16557-16575, 2015.
  25. [25] Y. F. Ji and C. C. Chang, “Nontarget image-based technique for small cable vibration measurement,” J. of Bridge Engineering, Vol.13, No.1, pp. 34-42, 2008.
  26. [26] S. W. Kim, B.-G. Jeon, N.-S. Kim, and J. C. Park, “Vision-based monitoring system for evaluating cable tensile forces on a cable-stayed bridge,” Structural Health Monitoring, Vol.12, Nos.5-6, pp. 440-456, 2013.
  27. [27] G. Busca, A. Cigada, P. Mazzoleni, and E. Zappa, “Vibration Monitoring of Multiple Bridge Points by Means of a Unique Vision-Based Measuring System,” Experimental Mechanics, Vol.54, No.2, pp. 255-271, 2014.
  28. [28] L. Tian and B. Pan, “Remote bridge deflection measurement using an advanced video deflectometer and actively illuminated LED targets,” Sensors, Vol.16, No.9, pp. 1-13, 2016.
  29. [29] Y.-Z. Song, C. R. Bowen, A. H. Kim, A. Nassehi, J. Padget, and N. Gathercole, “Virtual visual sensors and their application in structural health monitoring,” Structural Health Monitoring, Vol.13, No.3, pp. 251-264, 2014.
  30. [30] J.-J. Lee, H.-N. Ho, and J.-H. Lee, “A vision-based dynamic rotational angle measurement system for large civil structures,” Sensors, Vol.12, No.6, pp. 7326-7336, 2012.
  31. [31] Y. Fukuda, M. Q. Feng, Y. Narita, S. Kaneko, and T. Tanaka, “Vision-Based Displacement Sensor for Monitoring Dynamic Response Using Robust Object Search Algorithm,” IEEE Sensors J., Vol.13, No.12, pp. 4725-4732, 2013.
  32. [32] P. Kohut and P. Kurowski, “Application of modal analysis supported by 3D vision-based measurements,” J. of Theoretical Applied Mechanics, Vol.47, No.4, pp. 855-870, 2009.
  33. [33] J. Morlier and G. Michon, “Virtual Vibration Measurement Using KLT Motion Tracking Algorithm,” J. of Dynamic Systems, Measurement, and Control, Vol.132, No.1, 011003, 2010.
  34. [34] P. Avitabile, C. Niezrecki, M. Helfrick, C. Warren, and P. Pingle, “Noncontact Measurement Techniques for Model Correlation,” J. of Sound and Viration, Vol.44, pp. 8-12, 2010.
  35. [35] E. Caetano, S. Silva, and J. Bateira, “A vision system for vibration monitoring of civil engineering structures,” Experimental Techniques, Vol.35, No.4, pp. 74-82, 2011.
  36. [36] H. Yang, Q. Gu, T. Aoyama, T. Takaki, and I. Ishii, “Dynamics-Based Stereo Visual Inspection Using Multidimensional Modal Analysis,” IEEE Sensors J., Vol.13, No.12, pp. 4831-4843, 2013.
  37. [37] J. G. Chen, N. Wadhwa, Y.-J. Cha, F. Durand, W. T. Freeman, and O. Buyukozturk, “Modal identification of simple structures with high-speed video using motion magnification,” J. of Sound and Viration, Vol.345, pp. 58-71, 2015.
  38. [38] D. Zhang, J. Guo, X. Lei, and C. Zhu, “A high-speed vision-based sensor for dynamic vibration analysis using fast motion extraction algorithms,” Sensors, Vol.16, No.4, doi:10.3390/s16040572, 2016.
  39. [39] H. A. Bruck, S. R. McNeil, M. A. Sutton, and W. H. Peters III, “Digital image correlation using Newton-Raphson method of partial differential correction,” Experimental Mechanics, Vol.29, No.3, pp. 261-267, 1989.
  40. [40] C. Q. Davis and D. M. Freeman, “Statistics of subpixel registration algorithms based on spatiotemporal gradients or block matching,” Optical Engineering, Vol.37, No.4, pp. 1290-1298, 1998.
  41. [41] H. Foroosh, J. B. Zerubia, and M. Berthod, “Extension of phase correlation to subpixel registration,” IEEE Trans. on Image Processing, Vol.11, No.3, pp. 188-200, 2002.
  42. [42] A. Pilch, A. Mahajan, and T. Chu, “Measurement of Whole-Field Surface Displacements and Strain Using a Genetic Algorithm Based Intelligent Image Correlation Method,” J. of Dynamic Systems, Measurement, and Control, Vol.126, No.3, pp. 479-488, 2004.
  43. [43] B. Pan, H.-M. Xie, B.-Q. Xu, and F.-L. Dai, “Performance of sub-pixel registration algorithms in digital image correlation,” Measurement Science and Technology, Vol.17, No.6, pp. 1615-1621, 2006.
  44. [44] Y. Shang, Q. Yu, Z. Yang, Z. Xu, and X. Zhang, “Displacement and deformation measurement for large structures by camera network,” Optics and Lasers in Engineering, Vol.54, pp. 247-254, 2014.
  45. [45] C. A. Santos, C. O. Costa, and J. Batista, “A vision-based system for measuring the displacements of large structures: Simultaneous adaptive calibration and full motion estimation,” Mechanical Systems and Signal Processing, Vols.72-73, pp. 678-694, 2016.
  46. [46] M. Malesa, K. Malowany, J. Pawlicki, and M. Kujawinska, “Non-destructive testing of industrial structures with the use of multi-camera Digital Image Correlation method,” Engineering Failure Analysis, Vol.69, pp. 122-134, 2016.
  47. [47] J. M. Franco, B. M. Mayag, J. Marulanda, and P. Thomson, “Static and dynamic displacement measurements of structural elements using low cost RGB-D cameras,” Engineering Structures, Vol.153, pp. 97-105, 2017.
  48. [48] K. Malowany, M. Malesa, T. Kowaluk, and M. Kujawinska, “Multi-camera digital image correlation method with distributed fields of view,” Optics and Lasers in Engineering, Vol.98, pp. 198-204, 2017.
  49. [49] T. Aoyama, L. Li, M. Jiang, K. Inoue, T. Takaki, I. Ishii, H. Yang, C. Umemoto, H. Matsuda, M. Chikaraishi, and A. Fujiwara, “Vibration Sensing of a Bridge Model Using a Multithread Active Vision System,” IEEE/ASME Trans. on Mechatronics, Vol.23, No.1, pp. 179-189, 2017.
  50. [50] H. Yang, T. Takaki, and I. Ishii, “Simultaneous Dynamics-Based Visual Inspection Using Modal Parameter Estimation,” J. Robot. Mechatron., Vol.23, No.1, pp. 180-195, 2011.

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