Deep learning of electromechanical admittance data augmented by generative adversarial networks for flexural performance evaluation of RC beam structure-Reference-Cited by-同舟云学术

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Deep learning of electromechanical admittance data augmented by generative adversarial networks for flexural performance evaluation of RC beam structure

Published:2023-12 Issue: Volume:296 Page:116891
ISSN:0141-0296
Container-title:Engineering Structures
language:en
Short-container-title:Engineering Structures

Author:

Ai Demi,Zhang Rui

Publisher

Elsevier BV

Reference78 articles.

1. In situ estimation of applied biaxial loads with lamb waves;Shi;J Acoust Soc Am,2013

2. Development and application of a relative displacement sensor for structural health monitoring of composite bridges;Li;Struct Control Health Monit,2015

3. Instrumentation on structural health monitoring systems to real world structures;Teng;Smart Struct Syst,2015

4. Structural health monitoring of continuous prestressed concrete bridges using ambient thermal responses;Kulprapha;Eng Struct,2012

5. Advanced structural health monitoring of concrete structures with the aid of acoustic emission;Behnia;Constr Build Mater,2014

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