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

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.