A Data-Driven Framework for Monitoring Localized Pitting in Low-Carbon Steel Using Pulse-Echo Ultrasound

Abstract

Pitting corrosion is a localized degradation mechanism that can significantly affect the structural integrity of steel components while remaining difficult to detect and characterize using conventional monitoring approaches. This work investigates the use of pulse-echo ultrasound and data-driven signal analysis for the observability and characterization of localized pitting in low-carbon steel. The ultrasonic response of two 20 MHz single-element contact transducers was investigated through laboratory measurements on artificial pits and physics-based k-Wave simulations spanning a wider range of pit sizes and morphologies. The results show that localized pits modify the received signal through attenuation, scattering, waveform distortion, and the generation of secondary reflections, with the observed ultrasonic response strongly dependent on pit morphology and transducer aperture. A signal-processing and feature-extraction framework was developed to analyze these changes and to evaluate pit observability prior to characterization. Using pit-free measurements, observability limits were quantified with an autoencoder trained on signal descriptors, demonstrating that pit observability is influenced predominantly by pit geometry, normalized pit width, and pit volume rather than by depth alone. For signals exhibiting sufficiently observable and specular pit reflections, time-of-flight measurements enabled pit-depth estimation for defects deeper than 300 µm. To account for propagation-path distortions affecting pit-related echoes, an empirically derived cross-path delay compensation approach was developed using Random Forest models trained on synthetic signals, reducing systematic depth-estimation errors in the synthetic dataset and providing a physics-informed framework for future quantitative characterization studies. Additional Random Forest models employing waveform descriptors and reflection-amplitude indicators were used to assess pit morphology and acoustic surface specularity. The proposed framework was evaluated using laboratory measurements and through preliminary long-term monitoring of two pre-pitted specimens deployed in the HarshLab offshore environment. In these deployments, the methodology enabled simultaneous tracking of localized pit-wall evolution and overall backwall thickness changes from the same pulse-echo measurements, illustrating the potential of the approach for monitoring localized corrosion activity alongside generalized specimen wall loss.