Abstract

An experimental morphology-based information extraction methodology is presented for locating reinforcing bars and estimating their effective ultrasonic scattering diameters in reinforced concrete (RC) members using ultrasonic pitch–catch (UPC) non-destructive testing combined with synthetic aperture focusing technique (SAFT) reconstruction. Reinforced concrete slab specimens with known reinforcement layouts were constructed and tested using a commercial ultrasonic device equipped with dry point contact shear wave transducers in a pitch–catch configuration. The collected ultrasonic data were post-processed using an in-house software package to reconstruct two-dimensional (2D) SAFT images of the specimens. In the reconstructed images, embedded rebars consistently produced characteristic bipolar scattering responses composed of dominant trough–crest waveform pairs. Based on these repeatable scattering response features, an empirical morphology-based procedure was developed in which rebar depth was estimated from the midpoint of the dominant trough–crest pair, while the effective ultrasonic scattering diameter was characterized using their vertical separation. The experimental results obtained from twelve reinforced concrete slab specimens demonstrated reliable depth estimation and a strong monotonic relationship between reconstructed scattering response width and nominal rebar diameter under the investigated testing conditions. Regression analysis indicated that larger rebars generally produced broader reconstructed bipolar scattering responses due to cylindrical wave interaction, diffraction, interference, finite transducer aperture effects, and SAFT reconstruction characteristics. The proposed methodology does not attempt to reconstruct the exact physical boundary of the reinforcement or solve the full elastodynamic inverse problem. Instead, the proposed methodology provides a practical and computationally efficient morphology-based information extraction framework that transforms reconstructed ultrasonic scattering responses into quantitative morphological descriptors for embedded reinforcement characterization. By extracting repeatable scattering response features from SAFT-reconstructed images and establishing an empirical mapping between these descriptors and reinforcement characteristics, the proposed approach enables the quantitative interpretation of ultrasonic images without requiring computationally intensive full waveform inversion.

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