Linear array ultrasonic devices such as the MIRA A1040 are highly effective at detecting subsurface defects in concrete; however, interpretation of their data is time-consuming, subjective, and requires specialized expertise. This paper proposes a quantitative signal-processing framework that computes objective subsurface-quality Multi-Metric Scores derived from ultrasonic tomography B-scans. The framework integrates the Signal-to-Background Ratio, Energy Concentration Ratio, and Spatial Dispersion into a composite 0–100 scale. Laboratory testing demonstrated clear discrimination between control samples (scores 79–100) and specimens with intentionally placed voids (8–38) or honeycombing defects (6–35). Field validation confirmed similar separation using an acceptance threshold of 70. The proposed scoring methodology offers a practical, automated approach for real-time quality assessment of concrete pavements under realistic field construction conditions.
Olavarría et al. (Thu,) studied this question.