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Prediction of Thickness for Plastic Products Based on Terahertz Frequency-Domain Spectroscopy.

Authors :
Zhang, Tianyao
Li, Boyang
Ye, Zhipeng
Yan, Jianfeng
Zhao, Xiaoyan
Zhang, Zhaohui
Source :
Journal of Advanced Computational Intelligence & Intelligent Informatics. Jul2023, Vol. 27 Issue 4, p726-731. 6p.
Publication Year :
2023

Abstract

A novel method for predicting the thicknesses of plastics based on continuous-wave terahertz (THz) frequency-domain spectroscopy (THz-FDS) is presented in this study. Initially, the target material's THz refractive index is determined from the phase information provided by the coherent nature of THz-FDS. For thickness prediction, the optimal frequency band with a high signal-to-noise ratio and minor water vapor absorption is chosen first. The optical path along which the THz wave passes through a sample with unknown thickness is extracted from the phase delay information. The physical thickness of the sample is then determined using the calibrated refractive index obtained in the first step. Teflon, a classical plastic material, is utilized to illustrate the proposed process. A remarkable consistency with an overall relative difference of only 0.45% is revealed between the THz-FDS predicted and caliper measured thicknesses. The proposed method is expected to significantly expand the capabilities of THz spectroscopy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13430130
Volume :
27
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Advanced Computational Intelligence & Intelligent Informatics
Publication Type :
Academic Journal
Accession number :
165041991
Full Text :
https://doi.org/10.20965/jaciii.2023.p0726