A generalizable deep learning framework for localizing and characterizing acoustic emission sources in riveted metallic panels-Reference-Cited by-同舟云学术

A generalizable deep learning framework for localizing and characterizing acoustic emission sources in riveted metallic panels

Published:2019-09 Issue: Volume:130 Page:248-272
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Ebrahimkhanlou Arvin^ORCID,Dubuc Brennan,Salamone Salvatore

Funder

Office of Naval Research

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference36 articles.

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4. A new methodology for automating acoustic emission detection of metallic fatigue fractures in highly demanding aerospace environments: an overview;Holford;Prog. Aerosp. Sci.,2017

5. Simultaneous localization and classification of acoustic emission sources in plates using a guided wave-based sparse reconstruction;Dubuc,2017

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