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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Polymers Jg. 16; H. 11; S. 1561
Hauptverfasser:	Liu, Yi, Yu, Qing, Liu, Kaixin, Zhu, Ningtao, Yao, Yuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 31.05.2024 MDPI
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!