Model-based autonomous plate defects visualization method for quantitative wall-thinning estimation.

• Current plate thickness evaluation methods require knowledge of Lamb waves. • Our model-based plate defect visualization method estimates wall-thinning. • Wavenumber information determines optimal mode to detect wall-thinning in plates. • Autonomous 2D digital filtering method is proposed using 2D FFT data. The visualization of the wall thinning of plate-like structures using scanning laser Doppler vibrometry (SLDV) is a promising method in nondestructive evaluation using laser ultrasonics. In particular, the Lamb-wave-based SLDV method that uses continuous excitation exhibits excellent performance for the estimation of the wall thinning of plates. Currently, plate thickness is quantitatively evaluated based on wavenumber analysis using measured signals. However, it is difficult to estimate plate thickness automatically below the product of frequency and thickness of 6 MHz·mm without knowing the wavenumber sensitivity and minimum wavenumber distance from reference mode owing to the lack of the physical understanding of Lamb waves. In this study, a model-based autonomous plate defects visualization method is proposed for the quantitative imaging of the wall thinning of plates so that inspectors can use scanning laser Doppler vibrometry (SLDV) without any knowledge of Lamb waves and its signal processing. Interdigital-transducer-based SLDV is utilized to validate the proposed method, and a 6-mm-thick carbon steel plate with 1–8% wall thinning, and a 2-mm-thick aluminum plate with Y-shaped wall thinning are used. Experiments demonstrate that the capability of the proposed method for detecting wall thinning in plates is equivalent to that of manual plate defects visualization method. [ABSTRACT FROM AUTHOR]