Videogrammetric method for measuring of concrete beam deformations under dynamic vertical loading

Building constructions, buildings and structures
Authors:
Abstract:

Many studies have examined their use in civil and close-range applications, including building structural monitoring due to advances in videogrammetric systems. However, the videogrammetric system's ability to reliably identify concrete beam dynamic deformations under vertical loads has not been fully studied. This study aims to examine the efficacy of the videogrammetric system in detecting the dynamic deformation of various concrete beams through the utilization of the videogrammetry technique. The researchers utilized PhotoModeler software to generate a three-dimensional stereo model of concrete beams. This was done both before and after applying a vertical load. The primary objective of this research is to determine the deflection values exhibited by these beams. The videogrammetric system employs a pair of stationary video cameras to record the dynamic deformations of loaded beams. This study involves the selection and calibration of two identical model video cameras, specifically the Canon IXUS. In the practical trials, three distinct types of concrete beam sections of identical length are employed. The beams possess cross-sectional dimensions of 10×13×300 cm and have been chosen with varying compositions. In the laboratory setting, the apparatus is utilized to apply a consistent load to each of the three beams. The video results are subsequently examined based on the civil design calculations. The study provides evidence that the utilization of videogrammetric system approaches enables accurate and efficient measurement of deformation in various types of concrete beams, achieving precision at the millimeter level. Based on the aforementioned findings, it is evident that this particular technique holds the potential for effective implementation and utilization in the context of conducting destructive inspections on critical civil structural components

  • References
    1. Tong, X, Luan, K, Liu, X, Liu, S, Chen, P, Jin, Y, Lu, W, Huang, B. Tri-Camera High-Speed Videogrammetry for Three-Dimensional Measurement of Laminated Rubber Bearings Based on the Large-Scale Shaking Table. Remote Sensing. 2018. 10(12). Article no. 1902. DOI: 10.3390/rs10121902
    2. Galloway, T., Cole, M., & Lewis, C. (2017). Interactions of microplastic debris throughout the marine ecosystem. Journal of Cleaner Production, 169, 41-48. DOI: 10.1016/j.jclepro.2017.05.011.
    3. Olsson, K., Pettersson, J. Fatigue Assessment Methods for Reinforced Concrete Bridges in Eurocode: Comparative study of design methods for railway bridges. Master of Science Thesis in the Master’s Programme Structural Engineering and Building Performance Design. Chalmers University of Technology. Göteborg, 2010. 167 p.
    4. Alaloul, W.S., Qureshi, A.H., Musarat, M.A., Saad, S. Evolution of close-range detection and data acquisition technologies towards automation in construction progress monitoring. Journal of Building Engineering. 2021. 43(3). Article no. 102877. DOI: 10.1016/j.jobe.2021.102877
    5. Radi, F.M., Al-Baghdadi, J.A.A. The possibility of using a digital camera and videogrammetric techniques for monitoring of objects moving at different speeds. International Journal of Civil Engineering and Technology. 2018. 9(8). Pp. 318–331.
    6. Fathi, H., Brilakis, I. Automated sparse 3D point cloud generation of infrastructure using its distinctive visual features. Advanced Engineering Informatics. 2011. 25(4). Pp. 760–770. DOI: 10.1016/j.aei.2011.06.001
    7. Ortiz-Coder, P., Sánchez-Ríos, A. An Integrated Solution for 3D Heritage Modeling Based on Videogrammetry and V-SLAM Technology. Remote Sensing. 2020. 12(9). Article no. 1529. DOI: 10.3390/rs12091529
    8. Gruen, A. Fundamentals of videogrammetry – A review. Human Movement Science. 1997. 16(2–3). Pp. 155–187. DOI: 10.1016/S0167-9457(96)00048-6
    9. Shi, H., Chen, P., Zhang, D., Yang, J., Xu, Z., Tong, X. High-speed videogrammetric measurement of the displacement of suspendome structure node. Proceedings of The Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023). 2024. 12980. DOI: 10.1117/12.3020958.
    10. Maas, H.G., Kersten, T.P. Experiences with a high resolution still video camera in digital photogrammetric applications on a shipyard. Intercongress Symposium. Vol. 30. Part V. Melbourne, 1994. Pp. 250–255.
    11. Hu, H., Liang, J., Xiao, Z.Z., Tang, Z.Z., Asundi, A.K., Wang, Y.X. A four-camera videogrammetric system for 3-D motion measurement of deformable object. Optics and Lasers in Engineering. 2012. 50(5). Pp. 800–811. DOI: 10.1016/j.optlaseng.2011.12.011
    12. Black, J.T., Pappa, R.S. Photogrammetry and Videogrammetry Methods for Solar Sails and Other Gossamer Structures. Collection of Technical Papers – AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 2003. 3. 1–11. DOI: 10.2514/6.2004-1662
    13. Whiteman, T., Lichti, D.D., Chandler I. Measurement of deflections in concrete beams by close-range digital photogrammetry. Symposium on Geospatial Theory, Proceedings and Applications. Ottawa, 2002. 9 p.
    14. Dai, F., Lu, M. Assessing the Accuracy of Applying Photogrammetry to Take Geometric Measurements on Building Products. Journal of Construction Engineering and Management. 2010. 136(2). Pp. 242–250. DOI: 10.1061/(ASCE)CO.1943-7862.0000114
    15. Ji, Y., Chang, C.C. Identification of structural dynamic behavior for continuous system based on videogrammetric technique. Smart Structures and Materials 2006: Smart Structures and Integrated Systems. SPIE, 2006. Pp. 447–458.
    16.  Ganshkevich, Yu.A., Shikhov, N.S., Stoyantsov, N.M. Estimation of deformations of steel constructions of cranes based on photogrammetry. Journal of Physics: Conference Series. 2021. 1926(1). Article no. 012061. DOI: 10.1088/1742-6596/1926/1/012061
    17. Chong, A.K., Al-Baghdadi, J.A.A., Alshadli, D. High definition video cameras for measuring movement of vibrating bridge structure. Int Conf Vib Vibro-acoustics. 2014. 1–10. 
    18. Chen, X., Davis, J., Slusallek, P. Wide area camera calibration using virtual calibration objects. Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662). Vol. 2. Hilton Head, SC, 2000. Pp. 520–527. DOI: 10.1109/CVPR.2000.854901 
    19. Qandil, A., Zaid, A.I.O. Considerations in the design and manufacturing of a load cell for measuring dynamic compressive loads. 2015 Power Generation System and Renewable Energy Technologies (PGSRET). Islamabad, 2015. Pp 1–6. DOI: 10.1109/PGSRET.2015.7312209 
    20. Hastawan, A.F., Haryono, S., Utomo, A.B., Hangga, A., Setiyawan, A., Septiana, R., Hafidz, C.M., Triantino, S.B. Comparison of testing load cell sensor data sampling method based on the variation of time delay. IOP Conference Series: Earth and Environmental Science. 2021. 700(1). Article no. 012018. DOI: 10.1088/1755-1315/700/1/012018
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Previous articleNext article