Combination of non-destructive tests and image processing for assessment of the compressive strength of concrete

Compressive strength (fc) evaluation of concrete traditionally relies on non-destructive tests (NDT) such as ultrasonic pulse velocity and rebound hammer number, or their combination, known as SonReb. However, the accuracy of these methods is influenced by concrete conditions. Digital image processing (DIP) techniques have emerged as less sensitive alternatives to these conditions. In this paper, a novel approach that combines NDT and DIP to establish a reliable and generalizable relationship for estimating the fc of concrete is presented. 135 cylindrical samples were prepared, allowing NDT, compressive tests, and DIP feature extraction from their cut surfaces. The results were used to train and validate a regression model for estimating fc. Additionally, similar tests were conducted on cores, with a diameter of 95 mm, drilled from three levels of two column specimens, with a dimension of 1800x300x300 mm, to test the generalizability of the proposed equations in structural elements. The findings revealed that the innovative combination of conventional NDT and DIP outperforms SonReb in estimating fc, with R2 values of 0.90 and 0.94 for training and validation, respectively, compared to SonReb's R2 values of 0.83 and 0.91. Furthermore, the proposed model estimated the fc of cores with R2=0.88.