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

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-07-20 DOI:10.20965/jaciii.2023.p0726
Tian-yao Zhang, Boyang Li, Zhipeng Ye, Jianfeng Yan, Xiaoyan Zhao, Zhaohui Zhang
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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.
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基于太赫兹频谱的塑料制品厚度预测
提出了一种基于连续波太赫兹(THz)频域光谱(THz- fds)预测塑料厚度的新方法。最初,目标材料的太赫兹折射率是由太赫兹fds的相干特性提供的相位信息确定的。对于厚度预测,首先选择信噪比高、水汽吸收小的最优频段。从相位延迟信息中提取太赫兹波穿过厚度未知样品的光路。然后使用在第一步中获得的校准折射率来确定样品的物理厚度。聚四氟乙烯,一种经典的塑料材料,被用来说明所提出的过程。太赫兹fds预测厚度与卡尺测量厚度之间的总体相对差异仅为0.45%,具有显著的一致性。所提出的方法有望大大扩展太赫兹光谱的能力。
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
89
期刊介绍: JACIII focuses on advanced computational intelligence and intelligent informatics. The topics include, but are not limited to; Fuzzy logic, Fuzzy control, Neural Networks, GA and Evolutionary Computation, Hybrid Systems, Adaptation and Learning Systems, Distributed Intelligent Systems, Network systems, Multi-media, Human interface, Biologically inspired evolutionary systems, Artificial life, Chaos, Complex systems, Fractals, Robotics, Medical applications, Pattern recognition, Virtual reality, Wavelet analysis, Scientific applications, Industrial applications, and Artistic applications.
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