Guided Wave-based Probabilistic Imaging Using Wavefront Asymmetry for Corrosion Assessment in Metallic Plates

Abstract Corrosion is a critical factor in the degradation of metallic structures, especially in sectors such as maritime, aerospace, and civil infrastructure. Traditional corrosion assessment techniques, while widely used, are limited by their point-based measurements, labor intensity, and susceptibility to human error. This study proposes an advanced non-destructive evaluation (NDE) method combining guided wave propagation with probabilistic imaging to assess global corrosion damage and surface roughness in metallic plates. The approach utilizes Lamb waves, which are sensitive to thickness variations and capable of propagating over large areas with minimal sensor deployment. Key indicators such as wavefront asymmetry, residual signal energy, and correlation-based metrics (RAPID) were analyzed both numerically and experimentally. Corroded plates were modeled using Gaussian random fields and validated through controlled electrochemical degradation experiments. Results demonstrate that guided wave-based indices can effectively detect and monitor corrosion progression, with sensitivity to both the degree of material loss and surface irregularity. Additionally, a reference-free method based on wavefront asymmetry showed potential for practical, in-situ applications. The findings confirm the viability of guided waves as a powerful tool for structural health monitoring, offering enhanced spatial coverage, automation potential, and early-stage damage detection capabilities.