A Deep Learning Approach for Autonomous Compression Damage Identification in Fiber-Reinforced Concrete Using Piezoelectric Lead Zirconate Titanate Transducers

A Deep Learning Approach for Autonomous Compression Damage Identification in Fiber-Reinforced Concrete Using Piezoelectric Lead Zirconate Titanate Transducers

Effective damage identification is paramount to evaluating safety conditions and preventing catastrophic failures of concrete structures. Although various methods have been introduced in the literature, developing robust and reliable structural health monitoring (SHM) procedures remains an open rese...

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Bibliographic Details
Main Authors: George M. Sapidis, Ioannis Kansizoglou, Maria C. Naoum, Nikos A. Papadopoulos, Constantin E. Chalioris
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Sensors
Subjects:
structural health monitoring (SHM)
concrete damage identification
convolutional neural network (CNN)
1-D CNN
damage classification
deep learning
Online Access:https://www.mdpi.com/1424-8220/24/2/386

Internet

https://www.mdpi.com/1424-8220/24/2/386

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