Abstract-Terahertz Time-of-Flight Tomography Beyond the Axial Resolution Limit: Autoregressive Spectral Estimation Based on the Modified Covariance Method

Min Zhai, Alexandre Locquet, Cyrielle Roquelet,  D. S. Citrin

https://link.springer.com/article/10.1007/s10762-020-00722-1

We present a time-of-flight tomography method for exceeding the naïve axial (i.e., depth) resolution limit of terahertz (THz) deconvolution by autoregressive spectral extrapolation (AR) based on the modified covariance method (AR/MCM). In contrast to Wiener filtering combined with wavelet denoising, AR/MCM does not discard any frequency components in the low signal-to-noise (SNR) regions of the measured data, and unlike the AR approach based on the Burg method (AR/BM), no peak splitting (single peaks in the impulse response function appearing as double peaks) as well as frequency bias (spectral peaks shifted with respect to their correct positions) is observed after deconvolution. After verifying the advantages of AR/MCM over Wiener filtering in conjunction with wavelet denoising as well as over AR/BM, using synthetic data, AR/MCM is employed to reconstruct a single layer of mill scale on a steel coupon from experimental THz time-of-flight tomography data. The reconstruction shows good agreement with the film thickness obtained from destructive cross-sectional measurements. In addition, unlike AR/BM, optimizing the parameters to obtain stable reconstruction is straightforward relying of Akaike’s information criterion suggesting that AR/MCM can be an easier to implement for THz nondestructive characterization of stratigraphy under noisy conditions, particularly when estimates of the stratigraphy may not a priori be available.

Abstract-Nondestructive measurement of mill-scale thickness on steel by terahertz time-of-flight tomography

Min Zhai, Alexandre Locquet, Cyrielle Roquelet, Patrice Alexandre, Laurence Daheron, D.S.Citrin,



https://www.sciencedirect.com/science/article/abs/pii/S0257897220304345

We measure in a nondestructive and noncontact fashion the thicknesses of three scale films with thicknesses 28.5 ± 1.4 μm, 13.4± 0.9 μm, and 5.1 ± 0.3 μm on steel substrates employing terahertz time-of-flight tomography combined with advanced signal-processing techniques. Wüstite is the dominant phase in the scale films, though magnetite and hematite are also present. Because wüstite is electrically insulating, the incident terahertz electromagnetic pulses largely penetrate into the scale film; however, the pulses are entirely reflected by the underlying electrically conductive steel substrate. Because the film layers are thin, in some cases optically thin, the distinct pulses reflected at the air/scale and scale/steel interfaces overlap in time and thus are not visually evident in the reflected terahertz signal, necessitating the use of deconvolution techniques to recover the sample structure. We compare the merits of three deconvolution techniques, one unsuccessful (frequency-wavelet domain deconvolution) and two successful (sparse deconvolution and autoregressive extrapolation), to characterize the thicknesses of these scale films.

Abstract-Visualization of subsurface damage in woven carbon fiber-reinforced composites using polarization-sensitive terahertz imaging

Junliang Dong, Pascal Pomarède, Lynda Chehami, Alexandre Locquet, Fodil Meraghni, Nico F.Declercq, D.S.Citrin,

https://www.sciencedirect.com/science/article/pii/S0963869518301610

Polarization-sensitive terahertz imaging is applied to characterize subsurface damage in woven carbon fiber-reinforced composite laminates in this study. Terahertz subsurface spectral imaging based on terahertz deconvolution is tailored and applied to detect, in a nondestructive fashion, the subsurface damage within the first ply of the laminate caused by a four-point bending test. Subsurface damage types, including matrix cracking, fiber distortion/fracture, as well as intra-ply delamination, are successfully characterized. Our results show that, although the conductivity of carbon fibers rapidly attenuates terahertz propagation with depth, the imaging capability of terahertz radiation on woven carbon fiber-reinforced composites can nonetheless be significantly enhanced by taking advantage of the terahertz polarization and terahertz deconvolution. The method demonstrated in this study is capable of extracting and visualizing a number of fine details of the subsurface damage in woven carbon fiber-reinforced composites, and the results achieved are confirmed by comparative studies with X-ray tomography.

Abstract-Terahertz Quantitative Nondestructive Evaluation of Failure Modes in Polymer-Coated Steel

Junliang Dong,   Alexandre Locquet,   D. S. Citrin,

http://ieeexplore.ieee.org/document/7572023/


Terahertz reflective imaging is applied to characterize the failure modes in a polymer coating on a steel plate. The coating was initially scratched, then after accelerated aging, several types of failure have occurred. In order to resolve the thin coating (~50 μm), terahertz frequency-wavelet domain deconvolution is implemented. With the deconvolved signals, the temporally overlapping echoes of the incident, roughly single-cycle terahertz pulse are clearly resolved, and three important failure modes, viz. corrosion, delamination, and blistering, are characterized quantitatively. Terahertz images in three dimensions clearly exhibit the coating thickness distribution across the entire damaged coating, highlighting the terahertz features associated with different failure modes, thus demonstrating that terahertz imaging can be considered as an effective modality for characterizing damage mechanisms in polymer coatings on metals.

Abstract-Terahertz Superresolution Stratigraphic Characterization of Multilayered Structures Using Sparse Deconvolution

Junliang Dong,  Xiaolong Wu,  Alexandre Locquet, David S. Citrin,

http://ieeexplore.ieee.org/document/7874211/

Terahertz sparse deconvolution based on an iterative shrinkage algorithm is presented in this study to characterize multilayered structures. With an upsampling approach, sparse deconvolution with superresolution is developed to overcome the time resolution limited by the sampling period in the measurement and increase the precision of the estimation of echo arrival times. A simple but effective time-domain model for describing the temporal pulse spreading due to the frequency-dependent loss is also designed and introduced into the algorithm, which greatly improves the performance of sparse deconvolution in processing time-varying pulses during the propagation of terahertz waves in materials. Numerical simulations and experimental measurements verify the algorithms and show that sparse deconvolution can be considered as an effective tool for terahertz nondestructive characterization of multilayered structures.

Abstract-Depth resolution enhancement of terahertz deconvolution by autoregressive spectral extrapolation

Junliang Dong, Alexandre Locquet, and D. S. Citrin

https://www.osapublishing.org/ol/abstract.cfm?uri=ol-42-9-1828&origin=search

This Letter presents a method for enhancing the depth resolution of terahertz deconvolution based on autoregressive (AR) spectral extrapolation. The terahertz frequency components with a high signal-to-noise ratio (SNR) are modeled with an AR process, and the missing frequency components in the regions with low SNRs are extrapolated based on the AR model. In this way, the entire terahertz frequency spectrum of the impulse response function, corresponding to the material structure, is recovered. This method, which is verified numerically and experimentally, is able to provide a “quasi-ideal” impulse response function and, therefore, greatly enhances the depth resolution for characterizing optically thin layers in the terahertz regime.

© 2017 Optical Society of America

Abstract-Terahertz frequency-wavelet domain deconvolution for stratigraphic and subsurface investigation of art painting

Junliang Dong, J. Bianca Jackson, Marcello Melis, David Giovanacci, Gillian C. Walker, Alexandre Locquet, John W. Bowen, and D. S. Citrin

https://www.osapublishing.org/oe/abstract.cfm?uri=oe-24-23-26972

Terahertz frequency-wavelet deconvolution is utilized specifically for the stratigraphic and subsurface investigation of art paintings with terahertz reflective imaging. In order to resolve the optically thin paint layers, a deconvolution technique is enhanced by the combination of frequency-domain filtering and stationary wavelet shrinkage, and applied to investigate a mid-20th century Italian oil painting on paperboard, After Fishing, by Ausonio Tanda. Based on the deconvolved terahertz data, the stratigraphy of the painting including the paint layers is reconstructed and subsurface features are clearly revealed, demonstrating that terahertz frequency-wavelet deconvolution can be an effective tool to characterize stratified systems with optically thin layers.

© 2016 Optical Society of America

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