A Terahertz Fast Imaging Method for Debonding Defects of Thermal Barrier Coatings Based on Dual-Channel Convolutional Neural Network

IF 0.5 4区材料科学 Q4 MATERIALS SCIENCE, CHARACTERIZATION & TESTING

Materials Evaluation Pub Date : 2023-05-01 DOI:10.32548/2023.me-04302

Binghua Cao, Dalin Yang, Mengbao Fan

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引用次数: 1

Abstract

To tackle the inefficiency of terahertz (THz)-based C-scan defect detection for thermal barrier coatings (TBCs), a dual-channel convolutional neural network–based THz fast imaging method is proposed. In this paper, the finite-difference time-domain (FDTD) method is used to prepare the training set. In the numerical simulation, the actual C-scan step is simulated by grid division of different sizes. The large step THz image is preliminarily reconstructed by bicubic interpolation, and then the deep and shallow features in the image are extracted by the dual-channel convolution neural network and the image under small step is reconstructed by different weight refusion, so as to improve the detection efficiency by reducing the number of C-scan points. Gaussian white noise with different distributions is employed when simulating the real test image. The experimental results show that compared with bicubic, ICBI, SRCNN, and ResNet, the dual-channel convolutional neural network improves PSNR (peak signal-to-noise ratio) by 2.85, 2.81, 2.25, and 1.54, and improves by 0.019, 0.014, 0.014, and 0.009 on SSIM (structural similarity).

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基于双通道卷积神经网络的热障涂层脱胶缺陷太赫兹快速成像方法

为了解决基于太赫兹（THz）的热障涂层C扫描缺陷检测的低效性，提出了一种基于双通道卷积神经网络的太赫兹快速成像方法。本文采用时域有限差分法（FDTD）编制训练集。在数值模拟中，通过不同尺寸的网格划分来模拟实际的C扫描步骤。通过双三次插值对大步长THz图像进行初步重建，然后通过双通道卷积神经网络提取图像中的深部和浅部特征，并通过不同的权重推理对小步长下的图像进行重建，从而通过减少C扫描点的数量来提高检测效率。在模拟真实测试图像时，采用了不同分布的高斯白噪声。实验结果表明，与bicubic、ICBI、SRCNN和ResNet相比，双通道卷积神经网络将PSNR（峰值信噪比）提高了2.85、2.81、2.25和1.54，并将SSIM（结构相似性）提高了0.019、0.014、0.014和0.009。

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来源期刊

Materials Evaluation 工程技术-材料科学：表征与测试

CiteScore

0.90

自引率

16.70%

发文量

审稿时长

6-12 weeks

期刊介绍： Materials Evaluation publishes articles, news and features intended to increase the NDT practitioner’s knowledge of the science and technology involved in the field, bringing informative articles to the NDT public while highlighting the ongoing efforts of ASNT to fulfill its mission. M.E. is a peer-reviewed journal, relying on technicians and researchers to help grow and educate its members by providing relevant, cutting-edge and exclusive content containing technical details and discussions. The only periodical of its kind, M.E. is circulated to members and nonmember paid subscribers. The magazine is truly international in scope, with readers in over 90 nations. The journal’s history and archive reaches back to the earliest formative days of the Society.