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1 April 2019 Machine vision-based concrete beam crack pattern identification using fractal theory
Kaoshan Dai, Desheng Li, Mingyan Luo, Yuanfeng Shi, Songhan Zhang, Zhenhua Huang
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Proceedings Volume 10971, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIII; 109710W (2019) https://doi.org/10.1117/12.2514124
Event: SPIE Smart Structures + Nondestructive Evaluation, 2019, Denver, Colorado, United States
Abstract
Based on the modern image recognition technology, this study used the fractal theory to examine the surface cracks of concrete and the fractal dimension was used as an index to identify the bearing capability of concrete components. Through processing and simulating the experimental data obtained by other researchers, the relationship of crack fractal dimension D and the loading-ratio ξ of the concrete component was calculated. The D-ξ relationship of concrete beams is D = 0.1684 ξ + 1.0307. Based on this relationship, a fast evaluation method based on the fractal dimension of the crack surface to judge the bearing capacity of concrete components was proposed in this study, and its accuracy was verified by the analysis of experimental results.
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Kaoshan Dai, Desheng Li, Mingyan Luo, Yuanfeng Shi, Songhan Zhang, and Zhenhua Huang "Machine vision-based concrete beam crack pattern identification using fractal theory", Proc. SPIE 10971, Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XIII, 109710W (1 April 2019); https://doi.org/10.1117/12.2514124
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KEYWORDS
Fractal analysis
Civil engineering
Failure analysis
Analytical research
Statistical methods
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