Physics-guided deep neural network for structural damage identification-Reference-Cited by-同舟云学术

Physics-guided deep neural network for structural damage identification

Published:2022-09 Issue: Volume:260 Page:112073
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Huang Zhou,Yin Xinfeng,Liu Yang

Publisher

Elsevier BV

Subject

Ocean Engineering,Environmental Engineering

Reference61 articles.

1. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks;Abdeljaber;J. Sound Vib.,2017

2. 1-D CNNs for structural damage detection: verification on a structural health monitoring benchmark data;Abdeljaber;Neurocomputing,2018

3. Signal processing techniques for vibration-based health monitoring of smart structures;Amezquita-Sanchez;Arch. Comput. Methods Eng.,2016

4. Recent progress and future trends on damage identification methods for bridge structures;An;Struct. Control Health Monit.,2019

5. Structural damage detection in real time: implementation of 1D convolutional neural networks for SHM applications;Avci;35th IMAC Conf. Expos. Struct. Dyn.,2017

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