Smart Structures and Systems

  • 제24권5호
  • /
  • Pages.587-595
  • /
  • 2019
  • /
  • 1738-1584(pISSN)
  • /
  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Flexible camera series network for deformation measurement of large scale structures

  • Yu, Qifeng (College of Aerospace Science and Engineering, National University of Defense Technology) ;
  • Guan, Banglei (College of Aerospace Science and Engineering, National University of Defense Technology) ;
  • Shang, Yang (College of Aerospace Science and Engineering, National University of Defense Technology) ;
  • Liu, Xiaolin (Hunan Key Laboratory of Videometrics and Vision Navigation) ;
  • Li, Zhang (College of Aerospace Science and Engineering, National University of Defense Technology)
  • 투고 : 2019.04.28
  • 심사 : 2019.07.06
  • 발행 : 2019.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

Deformation measurement of large scale structures, such as the ground beds of high-rise buildings, tunnels, bridge, and railways, are important for insuring service quality and safety. The pose-relay videometrics method and displacement-relay videometrics method have already presented to measure the pose of non-intervisible objects and vertical subsidence of unstable areas, respectively. Both methods combine the cameras and cooperative markers to form the camera series networks. Based on these two networks, we propose two novel videometrics methods with closed-loop camera series network for deformation measurement of large scale structures. The closed-loop camera series network offers "closed-loop constraints" for the camera series network: the deformation of the reference points observed by different measurement stations is identical. The closed-loop constraints improve the measurement accuracy using camera series network. Furthermore, multiple closed-loops and the flexible combination of camera series network are introduced to facilitate more complex deformation measurement tasks. Simulated results show that the closed-loop constraints can enhance the measurement accuracy of camera series network effectively.

키워드

과제정보

연구 과제 주관 기관 : National Natural Science Foundation of China

참고문헌

  1. Ansar, A. and Daniilidistc, K. (2003), "Linear pose estimation from points or lines", IEEE T. Pattern Anal. Mach. Intell., 25, 578-589. DOI: 10.1109/TPAMI.2003.1195992.
  2. Candes, E.J., Li, X., Ma, Y. and Wright, J. (2011), "Robust principal component analysis", J. ACM, 58(1), 1-37. DOI: 10.1145/1970392.1970395.
  3. Chao, Z.C., Yu, Q.F., Jiang, G.W. and Fu, S.H. (2010), "Study of a pose-relay videometric method using a parallel camera series". Appl. Optics., 49(28), 5192. DOI: 10.1364/AO.49.005192.
  4. Engelkemeir, R., Khan, S.D. and Bssurke, K. (2010), "Surface deformation in Houston, Texas using GPS", Tectonophysics., 490(1), 47-54. DOI: 10.1016/j.tecto.2010.04.016.
  5. Eyers, R.D. and Mills, J.P. (2004), "Subsidence detection using integrated multi temporal airborne imagery", Inter. Archives Photogrammetry, Remote Sensing Spatial Inform. Sci., 34, 714-719.
  6. Gao, H., Cai, J.F., Shen, Z. and Zhao, H. (2011), "Robust principal component analysis-based four-dimensional computed tomography", Phys. Med. Biol., 56(11), 3181-3198. DOI: 10.1088/0031-9155/56/11/002.
  7. Guan, B.L., Shang, Y., Yu, Q.F., Lei, Z.H. and Zhang, X.H. (2015), "A simple and flexible calibration method of non-overlapping camera rig", P. SPIE. Inter. Soc. Opt. Eng., Munich, Germany, June. DOI: 10.1117/12.2184550.
  8. Guan, B.L., Yao, L.S., Liu, H.B. and Shang, Y. (2017a), "An accurate calibration method for non-overlapping cameras with double-sided telecentric lenses", Opt. Inter. J. Light Elect. Opt., 131, 724-732. DOI: 10.1016/j.ijleo.2016.11.156.
  9. Guan, B.L., Shang, Y. and Yu, Q.F. (2017b), Planar self-calibration for stereo cameras with radial distortion, Appl. Opt., 56(33), 9257. DOI: 10.1364/AO.56.009257.
  10. Hiroshi, P.S., Kaoru, A. and Osamu, O. (2003), "GPS-measured land subsidence in Ojiya City, Niigata Prefecture, Japan", Eng. Geology., 67(3), 379-390. DOI: 10.1016/S0013-7952(02)00221-1.
  11. Lu, C., Hager G. and Mjolsness, E. (2000), "Fast and globally convergent pose estimation from video images", IEEE Trans. Pattern Anal. Mach. Intell., 22, 610-622. DOI: 10.1109/34.862199.
  12. Luhmann, T., Robson, S., Kyle, S. and Harley, I. (2006), Close Range Photogrammetry, Whittles Publishing, Caithness, Scotland, UK.
  13. Ozcoban, S., Berilgen, M., Havvanur, K., Edil, T. and Kutay O. (2007), "Staged construction and settlement of a dam founded on soft clay", J. Geotech. Geoenviron. Eng., 133, 1003-1016. DOI: 10.1061/(ASCE)1090-0241(2007)133:8(1003).
  14. Park, F. and Martin, B. (1994), "Robot sensor calibration: solving AX=XB on the Euclidean group", IEEE Trans. Rob. Autom., 10, 717-721. DOI: 10.1109/70.326576.
  15. Shiu, Y. and Ahmad, H. (1989), "Calibration of wrist-mounted robotic sensors by solving homogeneous transform equations of the form AX = XB", IEEE T. Rob. Autom., 5, 16-29. DOI: 10.1109/70.88014.
  16. Shang, Y., Yu, Q.F., Yang, Z., Xu, Z.Q. and Zhang, X.H. (2014), "Displacement and deformation measurement for large scale structures by camera network", Opt. Lasers Eng., 54(1), 247-254. DOI: 10.1016/j.optlaseng.2013.07.009.
  17. Sirivachiraporn, A. and Phienwej, N. (2012), "Ground movements in EPB shield tunneling of Bangkok subway project and impacts on adjacent buildings", Tunn. Undergt. Sp. Tech., 30, 10-24. DOI: 10.1016/j.tust.2012.01.003.
  18. Ye, X.W., Ni, Y.Q., Wai, T.T., Wong, K.Y., Zhang, X.M. and Xu, F. (2013), "A vision-based system for dynamic displacement measurement of long-span bridges: algorithm and verification", Smart. Struct. Syst., 12(3), 363-379. http://dx.doi.org/10.12989/sss.2013.12.3_4.363.
  19. Ye, X.W., Yi, T.H., Dong, C.Z., Liu, T. and Bai, H. (2015a), "Multi-point displacement monitoring of bridges using a vision-based approach", Wind Struct., 20(2), 315-326. http://dx.doi.org/10.12989/was.2015.20.2.315.
  20. Ye, X.W., Yi, T.H., Wen, C. and Su, Y.H. (2015b), "Reliability-based assessment of steel bridge deck using a mesh-insensitive structural stress method", Smart. Struct. Syst., 16(2), 367-382. http://dx.doi.org/10.12989/sss.2015.16.2.367.
  21. Ye, X.W., Dong, C.Z. and Liu, T. (2016a), "Image-based structural dynamic displacement measurement using different multi-object tracking algorithms", Smart. Struct. Syst., 17(6), 935-956. http://dx.doi.org/10.12989/sss.2016.17.6.935.
  22. Ye, X.W., Yi, T.H., Dong, C.Z. and Liu, T. (2016b), "Vision-based structural displacement measurement: system performance evaluation and influence factor analysis", Measurement., 88, 372-384. DOI: 10.1016/j.measurement.2016.01.024.
  23. Yu, Q.F., Jiang, G.W., Ding, X.H. and Shang, Y. (2007), "Research on the broken-ray videogrammetric method and system for deformation measurement of large vessels", Chinese Conf. Theoretical Appl. Mech., Beijing, China, August.
  24. Yu, Q.F., Jiang, G.W., Fu, S.H. and Shang, Y. (2008a), "Measuring deformation of large vessels with innovative broken-ray videometrics", Inter. Cong. Theoretical Appl. Mech., Adelaide, Australia, August.
  25. Yu, Q.F., Jiang, G.W., Chao, Z.C., Fu, S.H., Shang, Y. and Yang, X. (2008b), "Deformation monitoring system of tunnel rocks with innovative broken-ray videometrics", P. SPIE - Inter. Society Opt. Eng., Melbourne, Australia, December.
  26. Yu, Q.F., Jiang, G.W., Fu, S.H., Chao, Z.C., Shang, Y. and Sun, X.Y. (2009), "Fold-ray videometrics method for the deformation measurement of nonintervisible large structures", Appl. Optics., 48(24), 4683-4687. DOI: 10.1364/AO.48.004683.
  27. Yu, Q.F., Shang, Y., Guan, B.L. and Liu, X.L. (2015a), "Camera series and parallel networks for deformation measurements of large scale structures", P. SPIE - Inter. Society Opt. Eng., Munich, Germany, June.
  28. Yu, Q.F., Jiang, G.W., Shang, Y., Xu, Y., Liu, X.L., Fu, S.H., Guan, B.L. and Zhu, X.W. (2015b), "A displacement-relay videometric method for surface subsidence surveillance in unstable areas", Sci. China Tech. Sci., 58(6), 1-7.