Skip to main content
Log in

A Novel In-plane Displacement Signal Generation Technique for Testing the Measurement Accuracy of Vision-Based Displacement System

  • Brief technical note
  • Published:
Experimental Techniques Aims and scope Submit manuscript

Abstract

To test the measurement accuracy of a vision-based displacement system, a physical object with a known true displacement time history is measured and the differences between measured and true displacements are evaluated. However, generating this object using conventional methods is expensive and time consuming. Benefiting from the characteristics of liquid crystal display (LCD) pixels with precise dimensions and adjustable intensities, this paper describes an LCD-based motion simulation technique (LMST) that can easily generate this object in the form of an accurately controlled in-plane displacement signal. The precision of the signal is discussed, its implementation LMST is presented and some issues that should be taken into account when using it are presented.

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

References

  1. Thai TQ, Ruesch J, Gradl PR, Truscott TT, Berke RB (2022) Speckle Pattern Inversion in High Temperature DIC Measurement. Exp Tech 46:239–247

    Article  Google Scholar 

  2. Cao D, Malakooti S, Kulkarni VN, Ren Y, Liu Y, Nie X et al (2022) The effect of resin uptake on the flexural properties of compression molded sandwich composites. Wind Energy 25:71–93

    Article  Google Scholar 

  3. Feng D, Feng MQ (2017) Experimental validation of cost-effective vision-based structural health monitoring. Mech Syst Sig Process 88:199–211

    Article  Google Scholar 

  4. Xu Y, Brownjohn J, Kong DL (2018) A non-contact vision-based system for multipoint displacement monitoring in a cable-stayed footbridge. Struct Control Heal Monit 25:2155–2177

    Article  Google Scholar 

  5. Khuc T, Catbas FN (2017) Completely contactless structural health monitoring of real-life structures using cameras and computer vision. Struct Control Heal Monit 24:1852–1868

    Article  Google Scholar 

  6. Lydon D, Lydon M, Taylor S, Del Rincon JM, Hester D, Brownjohn J (2019) Development and field testing of a vision-based displacement system using a low cost wireless action camera. Mech Syst Sig Process 121:343–358

    Article  Google Scholar 

  7. Luo L, Feng MQ, Wu ZY (2018) Robust vision sensor for multi-point displacement monitoring of bridges in the field. Eng Struct 163:255–266

    Article  Google Scholar 

  8. Luo LX, Feng MQ (2018) Edge-Enhanced Matching for Gradient-Based Computer Vision Displacement Measurement. Comput Civ Infrastruct Eng 33:1019–1040

    Article  Google Scholar 

  9. Luo L, Feng M, Wu J (2019) A comprehensive alleviation technique for optical-turbulence-induced errors in vision-based displacement measurement. Struct Control Heal Monit 27:2496–2511

    Google Scholar 

  10. Wang M, Ao WK, Bownjohn J, Xu F (2022) A novel gradient-based matching via voting technique for vision-based structural displacement measurement. Mech Syst Sig Process 171:108951

    Article  Google Scholar 

  11. Hoskere V, Park J-W, Yoon H, Spencer BF Jr (2019) Vision-based modal survey of civil infrastructure using unmanned aerial vehicles. J Struct Eng 145:04019062

    Article  Google Scholar 

  12. Weng Y, Shan J, Lu Z, Lu X, Spencer BF Jr (2021) Homography-based structural displacement measurement for large structures using unmanned aerial vehicles. Comput Civ Infrastruct Eng 36:1114–1128

    Article  Google Scholar 

  13. Yoon H, Shin J, Spencer BF Jr (2018) Structural displacement measurement using an unmanned aerial system. Comput Civ Infrastruct Eng 33:183–192

    Article  Google Scholar 

  14. Chen JG, Davis A, Wadhwa N, Durand F, Freeman WT, Büyüköztürk O (2017) Video camera-based vibration measurement for civil infrastructure applications. J Infrastruct Syst 23:B4016013

    Article  Google Scholar 

  15. Chen JG, Adams TM, Sun H, Bell ES, Büyüköztürk O (2018) Camera-Based Vibration Measurement of the World War i Memorial Bridge in Portsmouth. New Hampshire J Struct Eng 144:04018207

    Article  Google Scholar 

  16. Chen JG, Wadhwa N, Cha YJ, Durand F, Freeman WT, Buyukozturk O (2015) Modal identification of simple structures with high-speed video using motion magnification. J Sound Vibr 345:58–71

    Article  Google Scholar 

  17. Lee J, Lee K-C, Jeong S, Lee Y-J, Sim S-H (2020) Long-term displacement measurement of full-scale bridges using camera ego-motion compensation. Mech Syst Sig Process 140:106651

    Article  Google Scholar 

  18. Xu Y, Brownjohn JMW (2018) Vision-based systems for structural deformation measurement: case studies. Proc Inst Civ Eng Struct Build 171:917–930

    Article  Google Scholar 

  19. Tian L, Pan B (2016) Remote Bridge Deflection Measurement Using an Advanced Video Deflectometer and Actively Illuminated LED Targets. Sensors 16:13

    Article  Google Scholar 

  20. Xu Y, Zhang J, Brownjohn J (2021) An accurate and distraction-free vision-based structural displacement measurement method integrating Siamese network based tracker and correlation-based template matching. Measurement 179:109506

    Article  Google Scholar 

  21. Chang CC, Ji YF (2007) Flexible Videogrammetric Technique for Three-Dimensional Structural Vibration Measurement. J Eng Mech 133:656–664

    Article  Google Scholar 

  22. Ye XW, Yi TH, Dong CZ, Liu T (2016) Vision-based structural displacement measurement: System performance evaluation and influence factor analysis. Measurement 88:372–384

    Article  Google Scholar 

  23. Minami H, Matsumoto F, Suzuki S (2007) Prospects of lcd panel fabrication and inspection equipment amid growing demand for increased size. Hitachi Rev 56:63

    Google Scholar 

  24. Minami H, Mori J, Iwai S, Moriya H, Watanabe N (2011) Manufacturing and inspection equipment for efficient production of large LCDs. Hitachi Rev 60:228–232

    Google Scholar 

  25. V-Technology (2021) Color filter manufacturing. V-Technology Co., Ltd. https://www.vtec.co.jp/en/tech/process/process_filter.html. Accessed 16 June 2022

  26. Adam P, Bertolino P, Lebowsky F (2007) Mathematical modeling of the LCD response time. J Soc Inf Disp 15:571–577

    Article  Google Scholar 

  27. Brown Elliott, CH, Higgins MF, Hwang S, Han S, Botzas A, Hsu B-S, Nishimura S (2008) PenTile RGBW® color processing. In: SID symposium digest of technical papers 39:1112. https://doi.org/10.1889/1.3069331

  28. Brownjohn JMW, Xu Y, Hester D (2017) Vision-Based Bridge Deformation Monitoring. Front Built Environ 3:23

    Article  Google Scholar 

Download references

Acknowledgements

This work was financially supported by the China National Funds for Distinguished Young Scientists (52125805).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to F. Xu.

Ethics declarations

Competing Interest

The authors declared 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.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, M., Bownjohn, J., Xu, F. et al. A Novel In-plane Displacement Signal Generation Technique for Testing the Measurement Accuracy of Vision-Based Displacement System. Exp Tech 47, 921–927 (2023). https://doi.org/10.1007/s40799-022-00593-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40799-022-00593-2

Keywords

Navigation