Intelligent identification of damage defects in quartz fiber composites using terahertz technique based on convolutional neural network

doi:10.3969/j.issn.1000-1565.2022.06.015

Abstract

Abstract: In this paper, terahertz time-domain spectroscopy was used to detect the delamination defects in quartz fiber reinforced polymer(QFRP), and a one-dimensional convolutional neural network was built to realize the accurate identification of damage defects at different positions and depths, and the accuracy of the verification results was more than 90%. The defect detection image of the composite constructed according to the recognition results has high definition and contrast, which was consistent with the actual terahertz image. Terahertz technology combined with convolutional neural network can realize the intelligent recognition of non-polar materials.

Key words: terahertz time domain spectroscopy, quartz fiber composite, lamination defect, intelligent identification

CLC Number:

TP391.4
V19

LI Tao, XUE Gang, HUO Zixiang, WANG Baomin, LI Xiaoling, YANG Zhaonan. Intelligent identification of damage defects in quartz fiber composites using terahertz technique based on convolutional neural network[J]. Journal of Hebei University(Natural Science Edition), 2022, 42(6): 665-672.

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