Deep Feature Extraction Based on AE Signals for the Characterization of Loaded Carbon Fiber Epoxy and Glass Fiber Epoxy Composites

Deep Feature Extraction Based on AE Signals for the Characterization of Loaded Carbon Fiber Epoxy and Glass Fiber Epoxy Composites

Characterization of acoustic emission (AE) signals in loaded materials can reveal structural damage and consequently provide early warnings about product failures. Therefore, extraction of the most informative features from AE signals is an important part of the characterization process. This study...

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Bibliographic Details
Main Authors: Primož Potočnik, Martin Misson, Roman Šturm, Edvard Govekar, Tomaž Kek
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Applied Sciences
Subjects:
polymer composites
acoustic emission
feature extraction
convolutional autoencoder
deep features
Online Access:https://www.mdpi.com/2076-3417/12/4/1867

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