Automated identification of compressive stress and damage in concrete specimen using convolutional neural network learned electromechanical admittance

Title
Automated identification of compressive stress and damage in concrete specimen using convolutional neural network learned electromechanical admittance
Authors
Keywords
Electromechanical admittance (EMA), PZT transducer, Two-dimensional convolutional neural network, Compressive stress, Damage identification, Concrete structure
Journal
ENGINEERING STRUCTURES
Volume 259, Issue -, Pages 114176
Publisher
Elsevier BV
Online
2022-03-25
DOI
10.1016/j.engstruct.2022.114176

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