Deep Learning Approaches for Robust Time of Arrival Estimation in Acoustic Emission Monitoring

Deep Learning Approaches for Robust Time of Arrival Estimation in Acoustic Emission Monitoring

In this work, different types of artificial neural networks are investigated for the estimation of the time of arrival (ToA) in acoustic emission (AE) signals. In particular, convolutional neural network (CNN) models and a novel capsule neural network are proposed in place of standard statistical st...

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Bibliographic Details
Main Authors: Federica Zonzini, Denis Bogomolov, Tanush Dhamija, Nicola Testoni, Luca De Marchi, Alessandro Marzani
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Sensors
Subjects:
acoustic emissions
capsule neural network
convolutional neural network
source localization
time of arrival
Online Access:https://www.mdpi.com/1424-8220/22/3/1091

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