Sharif Digital Repository

This study proposes predictive equations for estimating the peak-experienced drift ratio of unreinforced masonry walls based on the visual characteristic of the damages. In this regard, a comprehensive database comprised of 190 images associated with 30 unreinforced masonry walls at different drift ratios between 0.0 and 1.1 percent is collected, and the visual features of the progressive damages are extracted. Various image processing filters are implemented to the images to quantify the cracking length and crushing areas. The filters are capable of distinguishing different crack patterns, such as joint cracking and block cracking. In the following, four scenarios are introduced based on... 

This paper proposes a damage assessment framework based on the visual features of a damaged reinforced concrete shear wall, such as crack pattern distribution, crushing areal density, aspect ratio, and the presence of the boundary condition. The study contains two parts including: identifying the performance level of the damaged walls (i.e., Immediate Occupancy, Life Safety, and Collapse Prevention) and estimating the residual strength and drift ratio of the walls. The research database contains 236 images of 72 reinforced concrete shear walls tested in the laboratory under the quasi-static cyclic loadings at various drift ratios between 0 and 4%. To identify the performance level of a... 

This paper introduces a probabilistic framework to quantify the spatial distribution of cracking and crushing in rectangular reinforced concrete shear walls at different drift ratios. In this research, a comprehensive probabilistic spatial analysis is conducted on an extensive collected database of reinforced concrete shear walls tested under the quasi-static cyclic loading. The database includes 235 images of 72 damaged walls with various geometry and material properties at different drift ratios between 0.0 and 4.0%. Various image processing filters are implemented to the images to highlight the wall areas that are more prone to cracking and crushing. Then, advanced statistical analysis is... 

This paper presents a novel computer vision-based methodology for assessment of the seismic damage in reinforced concrete moment frames using visual characteristics of surface damage following an earthquake. An extensive collected database comprising 974 images associated with 256 cyclic-loaded damaged beam-column joints, providing a set of cracking and crushing progression with increasing the evolution of damage level, is collected and used for the development and validation of the methodology. Employing image processing techniques, the characteristics of the surface damage, including the cracking length and crushing areas, are measured and used in a scenario-based assessment for the... 

After a significant earthquake, the updated status of the structural elements is usually determined based on a qualitative visual inspection. Although visual inspection provides a prompt assessment of the damaged elements, the output of this subjective method is influenced by the experience and decision of a trained inspector, which may vary from case to case. In this study, an innovative machine learning-based procedure is developed to automate damage state identification of non-ductile reinforced concrete moment frames (RCMFs) utilizing visual indices of crack patterns of the concrete surface. An extensive database including 264 surface crack patterns is constructed corresponding to 61... 

Although manual crack inspection has been widely used for structural health monitoring over the last decades, the development of computer vision methods allows continuous monitoring and compensates the human judgment inaccuracy. In this study, an image-based method entitled Arc Length method is introduced for extracting crack pattern characteristics, including crack width and crack length. The method contains two major steps; in the first step, the crack zones are estimated in the whole image. Afterwards, the algorithm finds the start point, follows the crack pattern, and measures the crack features, such as crack width, crack length, and crack pattern angle. The efficiency of the method is...