Stereophotogrammetry for 2-D building deformation monitoring using Kalman Filter

Odumosu, J. O.; Adeleke, O. O.; Nnam, V. C.; Avoseh, O. J.; Ogundeji, O. A.

doi:10.2478/rgg-2020-0006

Abstract

Stereo photogrammetry has been used in this study to analyse and detect movements within the Lecture theater of School of Environmental Technology of Federal University of Technology Minna via the use of Kalman filter algorithm. The essential steps for implementation of this method are herein highlighted and results obtained indicate Ins. Mov.s (velocity) ranging from ±0.0000001 m/epoch to ±0.000007 m/epoch with greater movements noticed in the horizontal direction than in the vertical direction of the building. Because the observed movements were insignificant, the building has been classified as stable. However, a longer period of observation with a bi-monthly observational interval has been recommended to enable decision on the rate of rise/sink and deformation of the building.

References

Ajibade, S. (1997). Horizontal and Vertical controls for the study and monitoring of structure movement. In Annual General Meeting of Nigerian Institution of Surveyors, Uyo, Nigeria.
Search in Google Scholar Back to article
Albert, J., Maas, H.-G., Schade, A., and Schwarz, W. (2002). Pilot studies on photogrammetric bridge deformation measurement. In Proceedings of the 2nd IAG Commission IV Symposium on Geodesy for Geotechnical and Structural Engineering, volume 21, page 24, 21–24 May, Berlin, Germany.
Search in Google Scholar Back to article
Alemdar, Z. F., Browning, J., and Olafsen, J. (2011). Photogrammetric measurements of RC bridge column deformations. engineering structures, 33(8):2407–2415, doi:10.1016/j.engstruct.2011.04.015.
Open DOI Search in Google Scholar Back to article
Chounta, I. and Ioannidis, C. (2012). High accuracy deformation monitoring of a concrete beam using automatic photo-grammetric techniques. Proceedings of the FIG Working Week 2012–Knowing to manage the territory, protect the environment, evaluate the cultural heritage.
Search in Google Scholar Back to article
Ehigiator-Irughe, R. and Ehigiator, M. (2013). Utilization of Kalman Filter Technique in Deformation Prediction of Above Surface Storage Tank. Advances in Physics theories and application, 21:18–23.
Search in Google Scholar Back to article
Erol, S., Erol, B., and Ayan, T. (2004). A General Review of the Deformation Monitoring Techniques and A Case Study: Analyzing Deformations Using GPS/Levelling. In XXth ISPRS Congress, Technical Commission VII, volume XXXV Part B7, pages 622–627, 12–23 July 2004, Istanbul, Turkey.
Search in Google Scholar Back to article
Fawzy, H. E.-D. (2015). The Efficiency of Close Range Photogrammetry Instead of Precise Terrestrial Surveying Technique for Deformation Monitoring in Unstable Buildings. International Journal of Civil Engineering and Technology (IJCIET), 6(10):176–186.
Search in Google Scholar Back to article
Fechteler, P. and Eisert, P. (2009). Adaptive colour classification for structured light systems. IET Computer Vision, 3(2):49–59, doi:10.1049/iet-cvi.2008.0058.
Open DOI Search in Google Scholar Back to article
Fraser, C. and Gruendic, L. (1985). The Analysis of Photogrammetric Deformation Measurements on Turtle Mountain. Photogrammetric Engineering and Remote Sensing, 51(2):207–216.
Search in Google Scholar Back to article
Fryer, J., Mitchell, H., and Chandler, J. H. (2007). Applications of 3D Measurement from Images. Whittles Publishing.
Search in Google Scholar Back to article
Gulal, E. (2013). Structural deformations analysis by means of Kalman-filtering. Boletim De Ciências Geodésicas, 19(1):98–113, doi:10.1590/S1982-21702013000100007.
Open DOI Search in Google Scholar Back to article
Ince, C. D. and Sahin, M. (2000). Real-time deformation monitoring with GPS and Kalman Filter. Earth, planets and space, 52(10):837–840, doi:10.1186/BF03352291.
Open DOI Search in Google Scholar Back to article
Jung, I. K. (2004). Simultaneous localization and mapping in 3D environments with stereovision. PhD thesis, Institut National Polytechnique de Toulouse-INP, France.
Search in Google Scholar Back to article
Lee, H. and Han, D. (2018). Deformation measurement of a railroad bridge using a photogrammetric board without control point survey. Journal of Sensors, 2018:1–10, doi:10.1155/2018/6851252.
Open DOI Search in Google Scholar Back to article
Lee, S.-C., Hwang, E., and Han, J.-G. (2006). Efficient image retrieval based on minimal spatial relationships. Journal of information science and engineering, 22(2):447–459.
Search in Google Scholar Back to article
Luhmann, T., Robson, S., Kyle, S., and Harley, I. (2007). Close Range Photogrammetry: Principles, Techniques and Applications. John Wiley & Sons, New York.
Search in Google Scholar Back to article
Maas, H.-G. and Hampel, U. (2006). Photogrammetric techniques in civil engineering material testing and structure monitoring. Photogrammetric Engineering & Remote Sensing, 72(1):39–45, doi:10.14358/PERS.72.1.39.
Open DOI Search in Google Scholar Back to article
Mills, J. and Barber, D. (2004). Geomatics techniques for structural surveying. Journal of Surveying Engineering, 130(2):56–64, doi:10.1061/(ASCE)0733-9453(2004)130:2(56).
Open DOI Search in Google Scholar Back to article
Mokroš, M., Liang, X., Surový, P., Valent, P., Čerňava, J., Chudý, F., Tunák, D., Saloň, Š., and Merganič, J. (2018). Evaluation of close-range photogrammetry image collection methods for estimating tree diameters. ISPRS International Journal of Geo-Information, 7(3), doi:10.3390/ijgi7030093.
Open DOI Search in Google Scholar Back to article
Mustafin, M., Valkov, V., and Kazantsev, A. (2017). Monitoring of Deformation Processes in Buildings and Structures in Metropolises. Procedia engineering, 189:729–736, doi:10.1016/j.proeng.2017.05.115.
Open DOI Search in Google Scholar Back to article
Nwadialor, I. J. (2001). Monitoring of small displacements in large Engineering structures in Nigeria: A justified necessity. Journal of Science Technology, Mathematics Education, 4(4):19–27.
Search in Google Scholar Back to article
Odumosu, J. and Ajayi, O. (2014). Comparative Analysis of some 2-D Transformation Models for Third Order Planimetric Mapping. International Journal of Advanced Scientific and Technical Research, 2(4):385–404.
Search in Google Scholar Back to article
Olagunju, R., Aremu, S., and Ogundele, J. (2013). Incessant collapse of buildings in Nigeria: an architect's view. Civil and Environmental Research, 3(4):49–54.
Search in Google Scholar Back to article
Rüther, H., Smit, J., and Kamamba, D. (2012). A comparison of close-range photogrammetry to terrestrial laser scanning for heritage documentation. South African Journal of Geomatics, 1(2):149–162.
Search in Google Scholar Back to article
US Army Corps of Engineers (2002). Structural Deformation Surveying (EM-1110-2-1009). Washington, DC, USA.
Search in Google Scholar Back to article
Wan, A. A. (2002). The Deformation Study of High Rise Building Using Repeated GPS Measurements. Research Report for Ministry of Science & Technology Malaysia.
Search in Google Scholar Back to article
Wan Aziz, W., Zulkarnaini, M., and Shu, K. (2005). The deformation study of high building using RTK-GPS: A first experience in Malaysia. In FIG Working Week 2005 and GSDI-8, ‘From Pharaohs to Geoinformatics FIG Working Week’, 16–21 April 2005, Cairo, Egypt.
Search in Google Scholar Back to article
Wang, C.-H., Mills, J. P., Gosling, P. D., Bridgens, B., and Grisdale, R. J. (2010). Monitoring the testing, construction and as-built condition of membrane structures by close range photogrammetry. In Proceedings of the ISPRS Commission V Mid-Term Symposium ‘Close Range Image Measurement Techniques’, volume XXXVIII, pages 592–596, 21–24 June 2010, Newcastle upon Tyne, Unted Kingdom.
Search in Google Scholar Back to article

Stereophotogrammetry for 2-D building deformation monitoring using Kalman Filter

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