Physical constraints-based terahertz thickness measurement method of thermal barrier coating

Due to the uneven microstructure of the thermal barrier coatings (TBCs) and dispersion effect, there is a discrepancy between the measured terahertz (THz) signals and the theory, which leads to the optimization process of the model inversion method is prone to local extremes. This results in a lack of reliability of THz thickness measurements based on model inversion. A THz inversion method based on physical constraints is proposed to measure the thickness of TBCs. In this paper, we illustrate the characteristics of the THz signal and propose a fitness function suitable for inversion of TBCs thickness. A feature comparison and adaptive mutation combined with teaching-learning-based optimization algorithm (FCAM-TLBO) is also proposed for inverting the theoretical model to extract ceramic layer thickness. The experiments show that the average relative error is less than 0.3 % for thickness measurements of TBC samples, which has better reliability than the conventional inversion methods.