An Artificial Intelligence-Based Scheme for Structural Health Monitoring in CFRE Laminated Composite Plates under Spectrum Fatigue Loading
Open Access
- 1 January 2025
- journal article
- Published by Tech Science Press in Structural Durability & Health Monitoring
- Vol. 19 (5) , 1145-1165
Abstract
In the fabrication and monitoring of parts in composite structures, which are being used more and more in a variety of engineering applications, the prediction and fatigue failure detection in composite materials is a difficu... | Find, read and cite all the research you need on Tech Science PressKeywords
This publication has 36 references indexed in Scilit:
- Seismic response prediction of structures based on Runge-Kutta recurrent neural network with prior knowledgeEngineering Structures, 2023
- Fatigue life prediction of glass fiber reinforced epoxy composites using artificial neural networksComposites Communications, 2021
- Deep long short-term memory networks for nonlinear structural seismic response predictionComputers & Structures, 2019
- SDNET2018: An annotated image dataset for non-contact concrete crack detection using deep convolutional neural networksData in Brief, 2018
- Pixel-level crack delineation in images with convolutional feature fusionStructural Control and Health Monitoring, 2018
- Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concreteConstruction and Building Materials, 2018
- Fault detection based on Kernel Principal Component AnalysisEngineering Structures, 2010
- Artificial neural networks in spectrum fatigue life prediction of composite materialsInternational Journal of Fatigue, 2007
- An artificial neural network for the fatigue study of bonded FRP–wood interfacesComposite Structures, 2006
- Modeling the mechanical behavior of fiber-reinforced polymeric composite materials using artificial neural networks—A reviewComposite Structures, 2006