Terahertz nondestructive quantitative characterization for layer thickness based on sparse representation method

Abstract

Terahertz (THz) time-domain detection has emerged as a promising tool for nondestructive testing due to its superior detection accuracy and sensitivity for both interfaces and internal defects inside non-metallic materials. In THz nondestructive evaluation, accurate characterizations of time-of-flight (TOF) extracted from the echo signal are critical to locate the layer interfaces and damages inside the structure. However, for prevalent complex THz echo signals such as overlapping echoes, low signal-to-noise (SNR) echoes and severe dispersion echoes, conventional methods by merely determining the TOF such as the direct method and the deconvolution method might be compromised. Here we have proposed the sparse representation (SR) method to quantitatively characterize the layer thickness by reconstructing the impulse response from complex THz echo signals. To balance the accuracy and the computational efficiency, we have proposed a combinational search method for selecting the optimal regularization parameter and constructed a convolution dictionary based on the structural prior of THz reference echo during the sparse decomposition process. Both numerical and experimental analysis are performed to validate the robustness of SR method on the THz echo localization compared with those conventional methods. It can be expected that SR will provide a novel approach to the application of precise localization and quantification of defects in THz based nondestructive techniques.