Single-Sensor Acoustic Emission Source Localization in Plate-Like Structures Using Deep Learning

Single-Sensor Acoustic Emission Source Localization in Plate-Like Structures Using Deep Learning

This paper introduces two deep learning approaches to localize acoustic emissions (AE) sources within metallic plates with geometric features, such as rivet-connected stiffeners. In particular, a stack of autoencoders and a convolutional neural network are used. The idea is to leverage the reflectio...

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Bibliographic Details
Main Authors: Arvin Ebrahimkhanlou, Salvatore Salamone
Format: Article
Language:English
Published: MDPI AG 2018-05-01
Series:Aerospace
Subjects:
acoustic emission
guided ultrasonic waves
deep learning
autoencoders
convolutional neural networks
machine learning
edge reflection
reverberation patterns
structural health monitoring
Online Access:http://www.mdpi.com/2226-4310/5/2/50

Internet

http://www.mdpi.com/2226-4310/5/2/50

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