Stable 3D Deep Convolutional Autoencoder Method for Ultrasonic Testing of Defects in Polymer Composites

Ultrasonic testing is widely used for defect detection in polymer composites owing to advantages such as fast processing speed, simple operation, high reliability, and real-time monitoring. However, defect information in ultrasound images is not easily detectable because of the influence of ultrasou...

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Bibliographic Details
Published in:	Polymers Vol. 16; no. 11; p. 1561
Main Authors:	Liu, Yi, Yu, Qing, Liu, Kaixin, Zhu, Ningtao, Yao, Yuan
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 31.05.2024 MDPI
Subjects:	Analysis Carbon fiber reinforced plastics Deep learning Defects Dimensional stability Fiber reinforced polymers Fourier transforms Machine learning Methods Neural networks Nondestructive testing Performance evaluation Polymer matrix composites Polymeric composites Three dimensional composites Time series Ultrasonic testing Wavelet transforms Taiwan carbon-fiber-reinforced polymer receptive field 3D convolution deep autoencoder ultrasonic testing
ISSN:	2073-4360, 2073-4360
Online Access:	Get full text
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