Neural Network-based non-destructive quantification of thin coating by terahertz pulsed imaging in the frequency domain

Terahertz pulsed imaging (TPI) is a powerful tool for non-destructive quantification of pharmaceutical tablet coatings. In this paper, we present a Neural Network (NN) based method for extracting the coating thickness from the FFT-amplitude of the measured terahertz waveform. We demonstrate that the...

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Bibliographic Details
Main Authors: Zhong, S, Shen, Y, Evans, M J, May, R K, Zeitler, J A, Dey, D
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Coatings
Pharmaceuticals
Reflection
Time domain analysis
Tomography
Online Access:Request full text
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Summary:Terahertz pulsed imaging (TPI) is a powerful tool for non-destructive quantification of pharmaceutical tablet coatings. In this paper, we present a Neural Network (NN) based method for extracting the coating thickness from the FFT-amplitude of the measured terahertz waveform. We demonstrate that the NN-based frequency domain method outperforms the standard "peak-finding" time-domain method, in terms of quantifying thinner coating thickness, although a learning set of data is necessary.
ISSN:2162-2027
DOI:10.1109/ICIMW.2010.5612560