Multifractal analysis of crack patterns in reinforced concrete shear walls

Abstract

Conventionally, the assessment of reinforced concrete shear walls relies on manual visual assessment which is time-consuming and depends heavily on the skills of the inspectors. The development of automated assessment employing flying and crawling robots equipped with high-resolution cameras and wireless communications to acquire digital images and advance image processing to extract crack patterns has paved the path toward implementing an automated system which determines structural damage based on visual signals acquired from structures. Since there are few, if any, studies to correlate crack patterns to structural integrity, this article proposes to analyze crack patterns using a multifractal analysis. The approach is initially tested on synthetic crack patterns, and then it is applied to a set of experimental data collected during the testing of two large-scale reinforced concrete shear wall subjected to controlled reversed cyclic loading. The structural response data available for each specimen are used to link the multifractal parameters with the structural performance of the two specimens. A relationship between the multifractal parameters and the crack patterns’ evolution and mechanism is noted. The results show that as the crack patterns extend and grow, multifractal parameters move toward higher values. The parameters jump as the mechanical response shows severe stiffness loss. In this study, no attempt is made to automate the process of mapping cracks from images.

Strength and stiffness estimation of damaged reinforced concrete shear walls using crack patterns

“…The average carbonized depth and residual material intensity are conventional damage characteristic factors for reinforced concrete structures; Cao et al noticed that fractal damage factors have a linear correlation with the aforementioned conventional factors, and also monofractal and multifractal dimensions are indicators of damage in concentrated‐load space and even‐load space, respectively. Several studies showed that fractal dimension and multifractal dimensions are suitable parameters for damage classification and relative stiffness loss estimation of RCSWs …”

“…Several studies showed that fractal dimension and multifractal dimensions are suitable parameters for damage classification and relative stiffness loss estimation of RCSWs. 15,16 Although many researchers have indicated that fractal dimension is a strong indicator of damage, no one has yet proposed a robust predictive equation for damage assessment based on fractal dimension of the crack patterns. In this paper, using an extensive crack pattern database, a quantitative approach is developed to estimate the stiffness and strength loss by developing several predictive equations for various possible scenarios.…”

Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures

“…For instance, SDNET2018 [21], with more than 56,000 labeled images of concrete structures, covers three small lab-made bridge decks, walls of a building, and several paved sidewalks, which are significantly smaller than common inspected infrastructures in practice. Manual identification of flaws in such large image sets is time consuming and prone to inaccuracy because of inspector fatigue or human error [22][23][24][25][26]. Image processing algorithms can improve the accuracy and efficiency of autonomous inspections by either (a) enhancing images to improve ease of human detection of defects or (b) autonomously identifying defects.…”

Application of multifractal analysis to segmentation of water bodies in optical satellite images

“…In geophysics, Posadas et al [24] characterize the dynamics of preferential water flow in soils and porous media with some particular parameters of multifractal spectra of MRI data. In engineering, multifractal spectra has been proposed as a method for evaluating the integrity of concrete shear walls through the study of images of fracture patterns caused by earthquakes [25]. They concluded that multifractal parameters move toward higher values as crack patterns extend and grow.…”