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

Author:

Zhang Tianyao1ORCID,Li Boyang1,Ye Zhipeng1,Yan Jianfeng2,Zhao Xiaoyan1,Zhang Zhaohui1

Affiliation:

1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing 100083, China

2. China Ship Research and Development Academy, 2 Dewai Shuangquanbao Road, Chaoyang District, Beijing 100192, China

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.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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