A Neural Network Framework for Validating Information–Theoretics Parameters in the Applications of Acoustic Emission Technique for Mechanical Characterization of Materials

A Neural Network Framework for Validating Information–Theoretics Parameters in the Applications of Acoustic Emission Technique for Mechanical Characterization of Materials

A multiparameter approach is preferred while utilizing Acoustic Emission (AE) technique for mechanical characterization of composite materials. It is essential to utilize a statistical parameter, which is independent of the sensor characteristics, for this purpose. Thus, a new information–theoretics...

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Bibliographic Details
Main Authors: Claudia Barile, Giovanni Pappalettera, Vimalathithan Paramsamy Kannan, Caterina Casavola
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Materials
Subjects:
acoustic emission
CFRP
Lempel–Ziv complexity
k-means
data clustering
deep learning
Online Access:https://www.mdpi.com/1996-1944/16/1/300

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https://www.mdpi.com/1996-1944/16/1/300

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