Shock Properties Characterization of Dielectric Materials Using Millimeter-Wave Interferometry and Convolutional Neural Networks

Shock Properties Characterization of Dielectric Materials Using Millimeter-Wave Interferometry and Convolutional Neural Networks

In this paper, a neural network approach is applied for solving an electromagnetic inverse problem involving solid dielectric materials subjected to shock impacts and interrogated by a millimeter-wave interferometer. Under mechanical impact, a shock wave is generated in the material and modifies the...

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Bibliographic Details
Main Authors: Jérémi Mapas, Alexandre Lefrançois, Hervé Aubert, Sacha Comte, Yohan Barbarin, Maylis Lavayssière, Benoit Rougier, Alexandre Dore
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Sensors
Subjects:
convolutional neural network
shock properties
mm-wave interferometry
metrology
shock velocity
particle velocity
Online Access:https://www.mdpi.com/1424-8220/23/10/4835

Internet

https://www.mdpi.com/1424-8220/23/10/4835

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