Noninvasive acoustic time-of-flight measurements in heated, hermetically-sealed high explosives using a convolutional neural network

We present a data-driven technique for measuring the time-of-flight through material sealed within a container. Time-of-flight measurement provides a noninvasive means of quantifying the sound speed profile within a material by transmitting an acoustic burst and then measuring the time required for...

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Detalles Bibliográficos

Principais autores:	John Greenhall, David Zerkle, Eric Sean Davis, Robert Broilo, Cristian Pantea
Formato:	Artigo
Idioma:	Inglês
Publicado:	Elsevier 2022-09-01
Series:	Machine Learning with Applications
Assuntos:	Acoustic time-of-flight Wave interference Convolutional Neural Networks Nondestructive evaluation Acoustic measurement in high explosives
Acceso en liña:	http://www.sciencedirect.com/science/article/pii/S2666827022000731
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