Inverse identification of geometric and acoustic parameters of inhomogeneous coatings through URCAS-based least-squares coupled cross-correlation algorithm

Abstract

Aiming to determine the geometric and acoustic parameters of inhomogeneous multi-layer coatings, an ultrasonic pressure reflection coefficient amplitude spectrum (URCAS) is derived using a material-oriented regularization scheme, when wave propagates perpendicularly to the coating surface. Based on the derived theoretical URCAS, a new objective function combining least-squares and cross-correlation algorithm is developed to simultaneously identify the thickness, sound velocity, density, attenuation coefficient amplitude, and attenuation coefficient power-law of the multi-layer coating. Genetic algorithm with the constraint of total multi-layer coating thickness being known is presented to optimize the nonlinear objective function for obtaining global optimal solution. Ultrasonic experiments were implemented on a dual-layer coating specimen with coating1/coating2/substrate structure using a flat immersion transducer with a central frequency of 15 MHz. The inversed thicknesses, sound velocities, and densities of the dual-layer coating were in good agreement with those measured through other methods, with less than 8.1% errors. The inversed attenuation coefficients of the coating 1 and coating 2 were α(f) = 1.02e-2 × f1.93 and α(f) = 4.62e-3 × f1.97, respectively. The upper bounds of the relative errors +r of inverted parameters were all less than 0.061. The proposed ultrasonic inversion method could be used to quantitatively characterize the surface integrity of inhomogeneous multi-layer coatings.