Automated Crack Detection and Damage Index Calculation for RC Structures Using Image Analysis and Fractal Dimension

• Published in: Journal of structural engineering (New York, N.Y.) N.Y.), 2021-04, Vol.147 (4)
• Main Authors: Woods, Joshua E, Yang, Yuan-Sen, Chen, Pei-Ching, Lau, David T, Erochko, Jeffrey
• Format: Article
• Language: English
• Subjects: Automation; Containment vessels; Correlation analysis; Cyclic loads; Damage assessment; Damage detection; Digital imaging; Earthquake damage; Earthquakes; Flaw detection; Fractal analysis; Fractal geometry; Fractals; Ground motion; Image analysis; Performance evaluation; Reinforced concrete; Shear walls; Structural damage; Structural engineering; Structural members; Technical Papers
• ISSN: 0733-9445; 1943-541X
• DOI: 10.1061/(ASCE)ST.1943-541X.0002970

AbstractDamage assessment in postearthquake reconnaissance of civil structures has traditionally relied upon the judgment of experienced site inspectors. In a step toward eliminating the need for on-site inspections, this paper presents a method for automatic postdisaster structural damage assessment of reinforced concrete (RC) structures. The method uses digital image correlation to automatically detect cracks in RC structural elements and correlates the analyzed crack distributions to a damage index using fractal dimension. The method is applied in this study to track the progression of damage in a planar RC shear wall and a cylindrical RC containment vessel tested in a laboratory under reversed cyclic loading. The results from the proposed damage index are compared with quantitative and qualitative damage indices that have been used in the past to evaluate damage levels in RC structures. The results demonstrate the ability of the method to measure crack distributions and automatically correlate them to a damage index. The method is also applied to an RC shear wall tested under an actual earthquake ground motion record using hybrid simulation to evaluate its performance in a more realistic damage assessment scenario. The results show that the method is able to track the progression of damage to an RC structural element in a realistic earthquake damage scenario. Based on the results, damage grades are proposed that can be used to relate the automatically computed damage index to a specific damage level. The results show great promise for the automatic damage assessment method and is a first step towards automated postdisaster damage assessment of RC structures using digital image correlation.