Vision-based measurements of deformations and cracks for RC structure tests

Xiaodong Ji*, Zenghui Miao, Rolands Kromanis

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Article number110508
JournalEngineering Structures
Volume212
Early online date20 Mar 2020
DOIs
Publication statusE-pub ahead of print/First online - 20 Mar 2020

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Keywords

  • UT-Hybrid-D
  • Crack characterization
  • Deformation measurements
  • Morphological operations
  • RC wall tests
  • Target tracking approach
  • Vision-based measurements
  • Connected-component labeling

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