Abstract-Characterization of thermal barrier coatings microstructural features using terahertz spectroscopy

Dongdong Ye, Weize Wang, Haiting Zhou, Huanjie Fang, Jibo Huang, Yuanjun Li, Hanhong Gong, Zhen Li,



https://www.sciencedirect.com/science/article/abs/pii/S0257897220305053

A novel approach was presented to characterize microstructural features of thermal barrier coatings (TBCs) using terahertz spectroscopy based on machine learning algorithms. In this study, the microstructures of yttria-stabilized zirconia (YSZ) atmospheric-plasma-sprayed (APS) thermal barrier coatings were regulated by choosing different kinds of spray powders, distances and power during processing. A terahertz time-domain spectroscopy system configurated transmission mode with an incidence angle of 0° was employed to estimate terahertz properties of porous YSZ ceramic coatings, including refractive index, extinction coefficient and relative time-domain broadening ratio. The variation tendency of terahertz properties of YSZ ceramic coatings with different microstructure features (porosity, pore to crack ratio, pore size) were investigated. Principal component analysis (PCA) method was adopted to reduce the dimensions of refractive index and extinction coefficient spectra data at the range of 0.6–1.4 THz and to ensure that different terahertz properties could be treated as inputs with similar weights during modeling. Three models (multiple linear regression (MLR), back-propagation (BP) neural network and support vector machine (SVM)) were set up to conduct regression analysis. As a result, according to the contribution rates of eigenvectors, the top one principal component of refractive index spectra data and the top two principal components of extinction coefficient spectra data were selected as the model inputs. The correlation coefficient comparisons showed that the characterization accuracy of PCA-SVM reached by over 95% and outperformed the other models. Finally, this study proposed that THz nondestructive technology combined with machine learning technique is efficient and feasible for microstructural features characterization and has profound implications for the structure integrity of TBCs evaluation in gas turbine blades.

Abstract-In-situ evaluation of porosity in thermal barrier coatings based on the broadening of terahertz time-domain pulses: simulation and experimental investigations

Dongdong Ye, Weize Wang, Haiting Zhou, Jibo Huang, Wenchao Wu, Hanhong Gong, and Zhen Li

Morphologies of the 8YSZ powders. (a) Particle sizes in the range of 15–55 µm; (b) Particle sizes in the range of 40–96 µm.

https://www.osapublishing.org/oe/abstract.cfm?uri=oe-27-20-28150

Porosity is one of the most important indicators for the characterization of the comprehensive performance of thermal barrier coatings (TBCs). Herein, we explored a fast, nondestructive porosity evaluation method based on the terahertz time-domain broadening effect. Different preparation process parameters were used to deposit the ceramic coatings, and the porosity ranged from 9.09% to 21.68%. Monte Carlo simulations were conducted to reveal the transitive relation between porosity and the terahertz time-domain broadening at different extinction coefficients and transmission distances. A transmission mode with an incidence angle of 0° was used to estimate the terahertz dielectric properties of ceramic coatings and the relative broadening ratio of terahertz pulses at different porosities. As a result, the Monte Carlo simulations showed that the time-domain broadening effect was enhanced when the extinction coefficient and transmission distances increased. As the porosity increased, the refractive index decreased and the extinction coefficient increased. The latter was more sensitive to minor porosity changes as demonstrated by linear fitting comparisons. Meanwhile, the relative broadening ratio increased when the porosity increased, and reserved the sensitivity of the extinction coefficient to porosity changes. The effect was more obvious on the relative broadening ratio which experienced multiple transmissions and reflections. Moreover, the relative broadening ratio could be obtained faster and in an easier manner compared to the dielectric parameters in both the transmission and reflection modes, based on single-step tests with the use of actual terahertz wave inspection. Finally, this study proposed a novel, convenient, online, nondestructive, and noncontact porosity evaluation method that could be potentially utilized to evaluate the integrity of TBCs in gas turbine blades.

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