Vision-based measurements of deformations and cracks for RC structure tests. (1st June 2020)

• Record Type: Journal Article
• Authors: Ji, Xiaodong; Miao, Zenghui; Kromanis, Rolands
• Is Part Of: Engineering structures. Volume 212(2020)
• Publication Date: 2020-06-01
• Subjects: Vision-based measurements -- Deformation measurements -- Crack characterization -- Target tracking approach -- Morphological operations -- Connected-component labeling -- RC wall tests; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2020.110508
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Vision-based measurements of deformations and cracks are developed for RC specimens. The method accurately estimates flexural, shear and sliding deformations of RC walls. A program is developed for characterizing the pattern, width and angle of cracks. Vision-based system achieves efficient measurements of complex crack fields. Abstract: This paper develops vision-based measurement methods for experimental tests of reinforced concrete (RC) structures. The methods can measure deformations and characterize cracks from images of RC specimens. The coordinates of objects of interest (OOIs) in the specimen are measured using a target tracking approach, and then deformation components (e.g., flexural, shear and sliding deformations) of the specimen are computed from the coordinates of OOIs through geometry analysis. The cracks are (i) identified using binary images converted from color images, (ii) and then quantified using the filter-based algorithm. The morphological operations, separation algorithm and connected component labeling algorithm are used in the image processing for crack measurements. The developed vision-based measurement methods were applied to cyclic tests of RC wall specimens. The accuracy of the vision-based measurements was validated by comparison with the results of traditional measurement techniques using the displacement transducers and crack scales. The proposed vision-based measurement methods demonstrate much higher efficiency and provide more useful information than the traditional measurement techniques. The paper also discusses a few application issues such as the specimen surface requirements and resolution of the vision-based measurements.