Identifying damage to composite materials based on deep residual shrinkage network

Abstract Interlaminar delamination damage is a common and typical defect in the context of structural damage in carbon fiber-reinforced resin matrix composites. The technology to identify such damage is crucial for improving the safety and reliability of structures. In this paper, we fabricated carbon fiber-reinforced composite laminates with different degrees of delamination damage, conducted static load experiments on them and used femtosecond fiber Bragg grating sensors (fsFBG) to determine their structural state to investigate the effects of delamination damage on their performance. We constructed a model to identify damage based on the deep residual shrinkage network, and used experimental data to enable it to identify varying degrees of delamination damage to carbon fiber-reinforced composites with an accuracy of 97.98%.

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Publication Details

Journal
The Aeronautical Journal
Published
2024-12-13
DOI
https://doi.org/10.1017/aer.2024.83
Citations
1
Primary Topic
Advanced Fiber Optic Sensors
Type
article
Field-Weighted Citation Impact
0.21
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Identifying damage to composite materials based on deep residual shrinkage network

Youjie Zhang, Chang Xu, Jie Li, Chufeng Sun et al.
1 citations
The Aeronautical Journal
Advanced Fiber Optic Sensors
0.21
article

Identifying damage to composite materials based on deep residual shrinkage network

Youjie Zhang, Chang Xu, Jie Li, Chufeng Sun, Jia Lu
article en
1 citations

Abstract

Abstract Interlaminar delamination damage is a common and typical defect in the context of structural damage in carbon fiber-reinforced resin matrix composites. The technology to identify such damage is crucial for improving the safety and reliability of structures. In this paper, we fabricated carbon fiber-reinforced composite laminates with different degrees of delamination damage, conducted static load experiments on them and used femtosecond fiber Bragg grating sensors (fsFBG) to determine their structural state to investigate the effects of delamination damage on their performance. We constructed a model to identify damage based on the deep residual shrinkage network, and used experimental data to enable it to identify varying degrees of delamination damage to carbon fiber-reinforced composites with an accuracy of 97.98%.

The Aeronautical JournalVol. 129(1331)
PLA Rocket Force University of Engineering (CN)
Openalex Percentile: Top 45%
Advanced Fiber Optic Sensors
0.21
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