DOI QR코드

DOI QR Code

Soil Deformation Tracking in Model Chamber by Targetless Close-Range Photogrammetry

무타겟 사진측량 기반 모형 토조 내 지반 변위 측정

  • Lee, Chang No (Dept. of Civil Engineering, Seoul National University of Science and Technology) ;
  • Oh, Jae Hong (Dept. of Civil Engineering, Korea Maritime and Ocean University)
  • Received : 2019.11.28
  • Accepted : 2019.12.05
  • Published : 2019.12.31

Abstract

This paper presents soil deformation measurement in model chamber based on photogrammetry. We created an aluminum framed acrylic model chamber with soil inside and applied photogrammetry to measure soil deformation caused by loading tests. The soil consists of 40% black and 60% regular sand to create image contrast in soil images. In preprocessing, the self camera calibration was carried out for IOPs (Interior Orientation Parameters), followed by the space resection to estimate EOPs (Exterior Orientation Parameters) using control points located along the aluminum frame. Image matching was applied to measure the soil displacement. We tested different matching window sizes and the effect of image smoothing. Experimental results showed that 65x65 pixels of window size produced better soil deformation map and the image smoothing was useful to suppress the matching outliers. In conclusion, photogrammetry was able to efficiently generated soil deformation map.

본 논문에서는 근접 사진측량에 기반하여 모형 토조 내 지반의 변위를 측정하기 위한 연구를 진행하였다. 알루미늄 프레임 및 투명 아크릴로 제작된 실내 모형 토조 내에 토사를 채워 넣고, 하중 재하 장치를 이용한 하중 재하를 통한 토사의 변위를 사진측량 기법으로 측정하였다. 토조 내의 토사는 영상 기반 자동 매칭을 위하여 검은 모래 약 40%, 일반 모래 약 60% 혼합하여 영상 대비의 정도를 높일 수 있도록 계획하였다. 전처리 과정으로서 실험실 카메라 캘리브레이션을 통해 내부표정요소를 도출하였고, 토조 프레임에 배치된 기준점을 이용한 후방교회법을 통해 외부표정요소를 예측하였다. 이후 영상 매칭을 통해 하중 전, 후의 토사 변위 패턴을 측정하였으며, 영상 매칭 시 활용되는 매칭 윈도우 크기 및 영상 스무딩 정도를 변경 적용하여 그 결과를 평가해보았다. 실험 결과, 매칭 윈도우 크기 65×65픽셀의 경우 안정적인 변위 도출이 가능하였으며, 영상 스무딩은 매칭의 과대 오차를 감소하는 효과를 보여주었다. 이를 통해 사진 측량을 통한 토조 내 지반 변위 패턴을 도출할 수 있었다.

Keywords

References

  1. Butterfield, R., Harkness, R.M., and Andrawes, K.Z. (1970), A stereo-photogrammetric technique for measuring displacement fields, Geotechnique, Vol. 20, No. 3, pp. 308-314. https://doi.org/10.1680/geot.1970.20.3.308
  2. Fraser, C.S. (1997), Digital camera self-calibration, ISPRS Journal of Photogrammetry & Remote Sensing, Vol. 52, pp. 149-159. https://doi.org/10.1016/S0924-2716(97)00005-1
  3. Jung, S.H., Lee, J.Y., and Choi, S.K. (2011), Vibration displacements measurement of slope models uisng close range photogrammetry, Korean Journal of Geomatics, Vol. 29, No. 6, pp. 561-568. (in Korean with English abstract) https://doi.org/10.7848/ksgpc.2011.29.6.561
  4. Lee, C.N. and Oh, J.H. (2013), Measurement of soil deformation around the tip of model pile by close-range photogrammetry, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 31, No, 2, pp. 173-180. (in Korean with English abstract) https://doi.org/10.7848/ksgpc.2013.31.2.173
  5. Lee, H.S. (2008), The deformation measurement of simulated ground using movable orientation board for photogrammetry, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 26, No. 4, pp. 323-331. (in Korean with English abstract)
  6. Lee, Y.J. (2006), Comparison of shallow model tunnel test using image processing and numerical analysis, Journal of the Korean Geotechnical Society, Vol. 22, No. 7, pp. 5-12. (in Korean with English abstract)
  7. Mcglone, C., Mikhail E., and Bethel, J. (2004), Manual of Photogrammetry, Fifth ed, ASPRS. pp.870-879.
  8. Mikhail, E.M., Bethel, J.S., and McGlone, J.C. (2001), Introduction to Modern Photogrammetry, John Wiley & Sons Inc., New York, pp. 136-137.
  9. Oh, J.H., Lee, C.N., and Eo, Y.D. (2006), A photogrammetric network and object field design for efficient self-calibration of non-metric digital Cameras, Korean Journal of Geomatics, Vol. 24, No. 3, pp. 281-288. (in Korean with English abstract)
  10. Roscoe, K.H., Arthur, J.R.F., and James, R.G. (1963), The determination of strains in soils by an X-ray method, Civ. Engng Public Works Rev., Vol. 58, pp. 1009-1012.
  11. Shao L., Guo X., and Zhao B. (2018), Digital image measurement system for soil specimens in triaxial tests, In: Wu, W. and Yu, H.S. (eds.), Proceedings of China-Europe Conference on Geotechnical Engineering, Springer Series in Geomechanics and Geoengineering, Springer, Cham, pp.611-614.
  12. Simonini, P. (1996), Analysis of behaviour of sand surrounding pile tips. J Geotech Geoenviron Eng, Vol. 122, No. 11, pp.897-905. https://doi.org/10.1061/(ASCE)0733-9410(1996)122:11(897)
  13. Stanier, S., Blaber, J., Take, W., and White, D. (2015), Improved image-based deformation measurement for geotechnical applications, Canadian Geotechnical Journal, Vol. 53, No. 5, pp. 727-739. https://doi.org/10.1139/cgj-2015-0253
  14. White, D., Take, W.A., and Bolton, M. (2003), Soil deformation measurement using particle image velocimetry (PIV) and photogrammetry, Geotechnique, Vol. 53, pp. 619-631. https://doi.org/10.1680/geot.2003.53.7.619