MarQR technology for measuring relative displacements of building structure elements with regard to joints and cracks

• Autorzy: Woźniak Marek , Woźniak Krzysztof

Identyfikatory

DOI

10.2478/rgg-2020-0005

• Języki publikacji: EN

Abstrakty

EN

The article presents an original optical system to measure displacements across joints or cracks in building structures. It describes the concept of system operation, algorithms to be followed and results of practical tests that have been performed. The proposed solution is based on digital photos taken with a non-metric digital camera, modified by defining its internal orientation elements and correction of lens distortion during calibration, constituting the measurement instrument registering the pictures of markers. QR (Quick Response) codes are proposed to be the markers. Being digitally processed, a set of registered images allow visualising the measured size of occurred displacements. Owing to this solution, it is possible to obtain data on a mutual position of two or more QR codes in the form of translation elements in 3D space and appropriate three orientation angles. Appointed elements are unequivocal in spatial interpretation and not limited by dimension. As the tests performed by the authors show, the results are more than satisfactory. The proposed measurement technology is an objective system of data acquisition, suitable for automating the whole monitoring process of displacements of building structure elements concerning joints and cracks.

Słowa kluczowe

EN

crackmeter; monitoring; QR code; photogrammetry; computer vision

PL

monitorowanie; kod QR; fotogrametria; rozpoznawanie obrazów

• Wydawca: Wydział Geodezji i Kartografii Politechniki Warszawskiej
• Czasopismo: Reports on Geodesy and Geoinformatics
• Rocznik: 2020
• Tom: Vol. 109
• Strony: 33--40
• Opis fizyczny: Bibliogr. 11 poz., rys., tab., wykr.

Twórcy

autor

Woźniak Marek

• Faculty of Geodesy and Cartography, Warsaw University of Technology, Pl. Politechniki 1, 00-661, Warsaw, Poland

autor

Woźniak Krzysztof

• Revelva Concept S.J., Poland, Cypryjska 4/5, 02-761, Warsaw, Poland

Bibliografia

• 1. Brown, J. (2011). ZBar bar code reader. Retrieved from http://zbar.sourceforge.net/index.html/.
• 2. Germanese, D., Leone, G., Moroni, D., Pascali, M., and Tampucci, M. (2018). Long-Term Monitoring of Crack Patterns in Historic Structures Using UAVs and Planar Markers: A Preliminary Study. Journal of Imaging, 4(8):99.
• 3. Germaniuk, K. (2007). Zalecenia dotyczące doboru mostowych urządzeń dylatacyjnych oraz ich wbudowywania i odbioru. INSTYTUT BADAWCZY DRÓG I MOSTÓW, Warsaw.
• 4. Hager, W. W. and Zhang, H. (2006). A survey of nonlinear conjugate gradient methods. Pacific journal of Optimization, 2(1):35–58.
• 5. Hestenes, M. R. and Stiefel, E. (1952). Methods of conjugate gradients for solving linear systems’. Journal of Research of the National Bureau of Standards, 49(6):409–436.
• 6. Jahanshahi, M., Masri, S., Padgett, C., and Sukhatme, G. (2013). An innovative methodology for detection and quantification of cracks through incorporation of depth perception. Machine Vision and Applications, 24(2):227–241.
• 7. Łakomy, T. (2018). Diagnostyka i naprawa konstrukcji budowlanych [Diagnostics and maintanance of construction]. Retrieved from http://korbet.pl/ocena-rys-wykrywanie-wad-wewnetrznych-w-konstrukcji/.
• 8. Nishiyama, S., Minakata, N., Kikuchi, T., and Yano, T. (2015). Improved digital photogrammetry technique for crack monitoring. Advanced Engineering Informatics, 29(4):851–858.
• 9. OpenCV (2018). Open Source Computer Vision Library. Retrieved from https://docs.opencv.org/4.0.0.
• 10. Strehl, A. and Ghosh, J. (2003). Cluster ensembles—a knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research, 3(3):583–617.
• 11. Valença, J., da Costa, D. D., Júlio, E., Araújo, H., and Costa, H. (2013). Automatic crack monitoring using photogrammetry and image processing. Measurement, 46(1):433–441.

Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).