Terahertz Nondestructive Stratigraphic Analysis of Complex Layered Structures: Reconstruction Techniques

Abstract

Terahertz (THz) time-of-flight tomography (TOFT), a nondestructive-evaluation technique for the stratigraphic characterization of structures with layers on the micron-to-millimeter scales, has proven to be challenging to apply to samples containing both micron-scale and millimeterscale layers. In THz TOFT, echoes reflected from distant interfaces and defects are often obscured as they may be immersed in a noisy background as such features in the reflected signal may be weak due to attenuation and dispersion, leading to the loss of valuable information. Moreover, overlapping echoes from any optically thin layers, such as thin coatings on thick specimens, are likely to be mistaken for a single interface in reconstructing the stratigraphy. Thus, layered structures containing both thick and thin layers have proven problematic for THz TOFT characterization. In this paper, a sparse-deconvolution (SD) technique, based on an interior-point method, and including a propagation model accounting for dispersion is demonstrated. The method is shown to be successful in extracting the impulse response of samples that combine the challenges of both thick and thin layers. The robustness and effectiveness of this method are verified numerically and experimentally. While the SD approach does not perform quite as well as cross-correlation (CC) techniques in terms of maximum thickness, it can provide a clearer and more accurate reconstruction of moderately thick samples incorporating thin layers.

Nondestructive Tertiary Mill‐Scale Thickness Measurement on Commercial Hot‐Rolled Steel Strip: Terahertz Time‐of‐Flight Tomography

“…AR aims at extrapolating the entire transfer function H( f ) (the Fourier transform of h(t) with f the frequency) where SNR is poor, based on frequency components within a frequency band where SNR is sufficiently high so that the data is reliable. [45][46][47] Superior to conventional deconvolution approaches, such as frequency-wavelet domain deconvolution (FWDD), [48] the bandwidth of the impulse response function h(t) is not narrowed to enhance SNR of the transfer function H( f ); contrary to sparse deconvolution, [49,50] AR does not require a large number of computational cost to achieve superconvergence and thus seems more suitable for rapid diagnosis of the quality of fabricated steel products.…”

Coherent Off-Axis Terahertz Tomography with a Multi-Channel Array and f-theta Optics

“…Terahertz imaging is a versatile technique in the field of non-destructive testing and imaging [ 1 , 2 , 3 ]. Possible application scenarios include material characterization [ 4 , 5 ], layer thickness determination [ 6 ], as well as moisture and liquid detection [ 7 ], spanning various fields of industry, such as automotive, aviation, polymers, petrochemicals, pharmaceutical industry, and many more [ 1 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. Most imaging setups employ raster-like scanning from one side, either in transmission or reflection geometry, to create volumetric sample representations.…”

Material Characterization and Thickness Measurement of Iron Particle Reinforced Polyurethane Multi-layer Coating for Aircraft Stealth Applications Using THz-Time Domain Spectroscopy

“…Hence, an alternate technique, namely sparse deconvolution utilizing the sparsity of the impulse response function, has been employed. Previous literature [20] reveals the application of sparse deconvolution technique along with iterative shrinkage algorithm to estimate the thickness of mill-scale ~5 µm. In this work, the sparse deconvolution technique has been employed to quantitatively characterize the layer thicknesses of each layer in a multi-layered RAP sample.…”