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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Vydané v:	Polymers Ročník 16; číslo 11; s. 1561
Hlavní autori:	Liu, Yi, Yu, Qing, Liu, Kaixin, Zhu, Ningtao, Yao, Yuan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 31.05.2024 MDPI
Predmet:	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
On-line prístup:	Získať plný text
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