Model-driven terahertz image reconstruction method for debonding defects in thermal barrier coatings.

A terahertz imaging system is considered to be an effective method to study the thermal barrier coating defects in gas turbine engines. However, due to the influence of the system hardware and terahertz wavelength, the imaging system has slow acquisition efficiency, low image resolution, and serious edge blur, which cannot meet the demand for defect detection. To overcome the above defects, a model-driven terahertz image reconstruction method is proposed, which uses simulation data to build datasets, reduces the dependence on experimental data, and has a good reconstruction effect on experimental images. A fusion loss function based on the edge intensity was designed to optimize the edge effect of reconstructed images. Compared with the bicubic, SRCNN, and VDSR methods, the proposed method can achieve better results in terms of visual and evaluation indices for the reduced terahertz images. It is proved that this method can effectively restore the defect contour in the terahertz image, sharpen the edge of the image, and improve the image quality. It has a good application value in the industry.

Frequency Optimization for Enhancement of Surface Defect Classification Using the Eddy Current Technique.

Eddy current testing is quite a popular non-contact and cost-effective method for nondestructive evaluation of product quality and structural integrity. Excitation frequency is one of the key performance factors for defect characterization. In the literature, there are many interesting papers dealing with wide spectral content and optimal frequency in terms of detection sensitivity. However, research activity on frequency optimization with respect to characterization performances is lacking. In this paper, an investigation into optimum excitation frequency has been conducted to enhance surface defect classification performance. The influences of excitation frequency for a group of defects were revealed in terms of detection sensitivity, contrast between defect features, and classification accuracy using kernel principal component analysis (KPCA) and a support vector machine (SVM). It is observed that probe signals are the most sensitive on the whole for a group of defects when excitation frequency is set near the frequency at which maximum probe signals are retrieved for the largest defect. After the use of KPCA, the margins between the defect features are optimum from the perspective of the SVM, which adopts optimal hyperplanes for structure risk minimization. As a result, the best classification accuracy is obtained. The main contribution is that the influences of excitation frequency on defect characterization are interpreted, and experiment-based procedures are proposed to determine the optimal excitation frequency for a group of defects rather than a single defect with respect to optimal characterization performances.

[Identification and classification of textiles based on terahertz time domain spectroscopy].

A method to discriminate textiles was proposed based on terahertz time-domain spectroscopy (THz-TDS) and clustering analysis, and some typical cotton textiles were investigated to prove its feasibility. Their time domain waveforms were measured using THz-TDS system and then their absorption spectra were obtained. Principal component analysis (PCA) was applied to extract features of the data, and then Mahalanobis distance discriminant method was employed to classify these materials. The results show that this method can classify these five textiles accurately. It indicates that the method to classify textiles is feasible which combines PCA and Mahalanobis distance discriminant method based on their THz absorption spectra. The proposed method has a potential for identifying textiles of similar composition.

[Terahertz time-domain spectroscopy of L-ascorbic acid].

The present paper reports the theoretical and experimental vibrational frequencies of L-ascorbic acid in the frequency range from 0.2 to 2.4 THz respectively. The vibrational frequencies of L-ascorbic acid in the THz range were simulated by Becke-3-Lee-Yang-Parr (B3LYP) algorithm of density functional theory. Simultaneously, the absorption and refractive index spectra of L-ascorbic acid were obtained using terahertz time-domain spectroscopy (THz-TDS). Based on the results from density functional calculations, the observed vibrational peaks were assigned with the aid of Gaussian View 3.07. Finally, the tera-hertz absorption spectra of tablets of vitamin C were compared with those of L-ascorbic acid. It was found that L-ascorbic acid had some distinct fingerprint spectra in the THz region and the theoretical results were in good agreement with the experimental results. The observed vibrational peaks were induced jointly by the intramolecular and intermolecular vibrations. The absorption peaks of L-ascorbic acid could be observed in the absorption spectra of the tablets of vitamin C. Our research is helpful to understanding the role of L-ascorbic acid in biological reactions. Still, the research results show the potential of the application of THz-TDS in the quantification of L-ascorbic acid.

[Terahertz spectroscopic investigation of imidacloprid].

Terahertz radiation generated by ultra short laser pulses has a broad band width in the far-infrared range. Terahertz wave interacting with materials is a new research field. In this paper, we performed measurement of absorption coefficient and refractive index of imidacloprid in the frequency range 0.2-2.0 THz at room temperature by THz-TDS. The results indicate that imidacloprid has absorption fingerprints in this frequency range, and the absorption coefficient increases with the frequency. The average refractive index of imidacloprid is 1.65, and the refractive index of imidacloprid increases slightly with frequency. A semi-empirical theory was applied to obtain the structure and vibrational frequencies of the imidacloprid molecules in THz region. The calculated results agree well with the experimental data. The absorption features are caused by the collective vibrational and torsional modes, and different absorption peaks correspond to different vibrational modes. The comparison between experimental and theoretical study shows that far-infrared absorption features are highly sensitive to the structure and spatial arrangement of the molecules. THz-TDS is a potential tool to understand the collective vibrational modes and conformational structures of biomolecules.