Nondestructive Testing of Hollowing Deterioration of the Yungang Grottoes Based on THz-TDS

Abstract

Terahertz (THz) spectroscopy is an important method in noninvasive detection and diagnosis for historic relics. A new nondestructive testing (NDT) method based on terahertz time-domain spectroscopy (THz-TDS) technology was developed to measure the hollowing deterioration of the Yungang Grottoes in this paper. Hollowing deterioration samples were strictly prepared, and a series of experiments were conducted to ensure the representativeness of the experimental results. A hollowing thickness model was established by the relationship between the thickness of the hollowing deterioration sample and the time difference of the front flaked stone surface and the stone wall surface of the hollowing deterioration samples. The results show that the R-squared value of the model equation reached 0.99795, which implies that this model is reliable. Therefore, the actual hollowing thickness of the Yungang Grottoes can be obtained by substituting the time difference in the proposed thickness hollowing model, where the time difference is obtained from measured THz spectra. The detection method of stone relic hollowing deterioration is easy to apply, which can not only realize qualitative NDT but also quantitative hollowing deterioration thickness determination. This method has crucial practical significance for the repair and strengthening of stone relics similar to the Yungang Grottoes.

Highly sensitive Terahertz non-destructive testing technology for stone relics deterioration prediction using SVM-based machine learning models

“…It can be found that the SVM-HDPM using the linear kernel function can have the lowest MSE with the value as low as 3.303 E-4, which indicates that it can have the most superior prediction accuracy among the three models. Moreover, it is better than the traditional curve fitting method with MSE of 0.998 reported by Feng [37].…”

Highly Sensitive Terahertz Non-destructive Testing Technology for Stone Relics Deterioration Prediction Using SVM-Based Machine Learning Models

“…It can be found that the SVM-HDPM using the linear kernel function can have the lowest MSE with the value as low as 3.303 E-4, which indicates that it can have the most superior prediction accuracy among the three models. Moreover, it is better than the traditional curve fitting method with MSE of 0.998 reported by Feng [37]. Therefore, the SVM-HDPM with the linear kernel function can have the most accurate in the predicting the thickness of the hollowing thickness.…”

Terahertz Technologies and Its Applications

“…Analyses of the structures are carried out using THz time-domain spectroscopy. In Reference [13], it is shown how THz spectroscopy can be used for nondestructive testing of the hollowing deterioration of stone relics (Yungang Grottoes in this case). Further applications for non-destructive testing using THz radiation are presented in Reference [14], where an optimal scanning technique for honeycomb sandwich composite panels is proposed.…”