Enhanced Defect Detection in Carbon Fiber Reinforced Polymer Composites via Generative Kernel Principal Component Thermography

Enhanced Defect Detection in Carbon Fiber Reinforced Polymer Composites via Generative Kernel Principal Component Thermography

Increasing machine learning methods are being applied to infrared non-destructive assessment for internal defects assessment of composite materials. However, most of them extract only linear features, which is not in accord with the nonlinear characteristics of infrared data. Moreover, limited infra...

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Bibliographic Details
Main Authors: Kaixin Liu, Zhengyang Ma, Yi Liu, Jianguo Yang, Yuan Yao
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Polymers
Subjects:
infrared non-destructive assessment
polymer composite
deep learning
generative adversarial network
thermographic data analysis
kernel principal component analysis
Online Access:https://www.mdpi.com/2073-4360/13/5/825

Internet

https://www.mdpi.com/2073-4360/13/5/825

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