Title:
AUTOMATED DETECTION AND MEASUREMENT OF CRACKS IN REINFORCED CONCRETE COMPONENTS
Author(s):
Jonathan P. Rivera, Goran Josipovic, Emma Lejeune, Bismarck N. Luna, and Andrew S. Whittaker
Publication:
Structural Journal
Volume:
112
Issue:
3
Appears on pages(s):
397-406
Keywords:
automated crack detection and measurement; damage assessment; imaging
DOI:
10.14359/51687424
Date:
5/1/2015
Abstract:
Damage and loss assessment of reinforced concrete elements are based in part on the length, width, and areal density of cracks. Crack information is traditionally collected using a crack width card and transferred to drawing sheets, which is both approximate and labor-intensive. An automated procedure involving digital image processing was developed and deployed to collect and process crack data. The procedure was developed and validated using data from the cyclic testing of nine reinforced concrete shear walls of varying aspect and reinforcement ratios.
Related References:
1. Gulec, C. K.; Whittaker, A. S.; and Hooper, J. D., “Fragility Functions for Low Aspect Ratio Reinforced Concrete Walls,” Engineering Structures, V. 32, No. 9, Nov. 2010, pp. 2894-2901. doi: 10.1016/j.engstruct.2010.05.008
2. Abdel-Qader, I.; Abudayyeh, O.; and Kelly, M., “Analysis of Edge-Detection Techniques for Crack Identification in Bridges,” Journal of Computing in Civil Engineering, ASCE, V. 17, No. 4, 2003, pp. 255-263. doi: 10.1061/(ASCE)0887-3801(2003)17:4(255)
3. Fujita, Y.; Mitani, Y.; and Hamamoto, Y., “A Method for Crack Detection on a Concrete Structure,” Proceedings of the 18th International Conference on Pattern Recognition, Aug. 2006, pp. 901-904.
4. Miyamoto, A.; Konno, M. A.; and Brühwiler, E., “Automatic Crack Recognition System for Concrete Structures Using Image Processing Approach,” Asian Journal of Information Technology, V. 6, No. 5, 2007, pp. 553-561.
5. Yamaguchi, T.; Nakamura, S.; Saegusa, R.; and Hashimoto, S., “Image-Based Crack Detection for Real Concrete Surfaces,” IEEJ Transactions on Electrical and Electronic Engineering, V. 3, No. 1, 2008, pp. 128-135. doi: 10.1002/tee.20244
6. Choudhary, G. K., and Dey, S., “Crack Detection in Concrete Surfaces using Image Processing, Fuzzy Logic, and Neural Networks,” IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI), Oct. 2012, pp. 404-411.
7. Mathworks, MATLAB version 8.1.0.604 (R2013a), 2013, Natick, MA.
8. Luna, B. N.; Rivera, J. P.; Rocks, J. F.; Goksu, C.; and Whittaker, A. S., “Seismic Performance of Low Aspect Ratio Reinforced Concrete Shear Walls,” Proceedings of the 22nd International Conference on Structural Mechanics in Reactor Technology, San Francisco, CA, Aug. 2013.
9. GigaPan Systems, “GigaPan Stitch.EFX,” GigaPan Systems, Portland, OR, 2013, http://www.gigapan.com/cms/shop/software/gigapan-stitch-efx. (last accessed April 30, 2015)
10. FastStone Soft, FastStone Image Viewer for Windows version 4.7, 2013, http://www.faststone.org/FSViewerDetail.htm. (last accessed April 30, 2015)
11. CTLGroup, “Crack Comparator Card,” CTLGroup, Skokie, IL.