LAPSE:2024.1079
Published Article

LAPSE:2024.1079
Enhancing Damage Localization in GFRP Composite Plates: A Novel Approach Using Feedback Optimization and Multi-Label Classification
June 10, 2024
Abstract
Damage localization in GFRP (glass-fiber-reinforced polymer) composite plates is a crucial research area in marine engineering. This study introduces a feedback-based damage index (DI) combined with multi-label classification to enhance the accuracy of damage localization and address scenarios involving multiple damages. The research begins with the creation of a modal database for yachts’ GFRP composite plates using finite element modeling (FEM). A method for deriving a feedback-weighted matrix, based on the accuracy of the DI, is then developed. Sensitivity analysis reveals that the feedback DI is 50% more sensitive than the traditional DI, reducing false positives and missed detections. The associated feedback-weighted matrix depends solely on the structural shape, ensuring its transferability. To address the challenge for localizing multiple damages, a multi-label classification approach is proposed. The synergy between the feedback optimization and multi-label classification enables the rapid and precise localization of multiple damages in GFRP composite plates. Modal testing on damaged GFRP plates confirms the enhanced accuracy for combining the feedback DI with multi-label classification for pinpointing damage locations. Compared with traditional methods, this feedback DI method improves sensitivity, while multi-label classification effectively handles multiple damage scenarios, enhancing the overall efficiency of the damage diagnosis. The effectiveness of the proposed methods is validated through experimentation, offering robust theoretical support for composite plate damage diagnostics.
Damage localization in GFRP (glass-fiber-reinforced polymer) composite plates is a crucial research area in marine engineering. This study introduces a feedback-based damage index (DI) combined with multi-label classification to enhance the accuracy of damage localization and address scenarios involving multiple damages. The research begins with the creation of a modal database for yachts’ GFRP composite plates using finite element modeling (FEM). A method for deriving a feedback-weighted matrix, based on the accuracy of the DI, is then developed. Sensitivity analysis reveals that the feedback DI is 50% more sensitive than the traditional DI, reducing false positives and missed detections. The associated feedback-weighted matrix depends solely on the structural shape, ensuring its transferability. To address the challenge for localizing multiple damages, a multi-label classification approach is proposed. The synergy between the feedback optimization and multi-label classification enables the rapid and precise localization of multiple damages in GFRP composite plates. Modal testing on damaged GFRP plates confirms the enhanced accuracy for combining the feedback DI with multi-label classification for pinpointing damage locations. Compared with traditional methods, this feedback DI method improves sensitivity, while multi-label classification effectively handles multiple damage scenarios, enhancing the overall efficiency of the damage diagnosis. The effectiveness of the proposed methods is validated through experimentation, offering robust theoretical support for composite plate damage diagnostics.
Record ID
Keywords
damage localization, feedback optimization, GFRP, multi-label classification
Subject
Suggested Citation
Cao J, Liao J, Yan J, Yu H. Enhancing Damage Localization in GFRP Composite Plates: A Novel Approach Using Feedback Optimization and Multi-Label Classification. (2024). LAPSE:2024.1079
Author Affiliations
Cao J: School of Marine Engineering, Jimei University, Xiamen 361021, China [ORCID]
Liao J: School of Marine Engineering, Jimei University, Xiamen 361021, China
Yan J: School of Marine Engineering, Jimei University, Xiamen 361021, China
Yu H: School of Marine Engineering, Jimei University, Xiamen 361021, China
Liao J: School of Marine Engineering, Jimei University, Xiamen 361021, China
Yan J: School of Marine Engineering, Jimei University, Xiamen 361021, China
Yu H: School of Marine Engineering, Jimei University, Xiamen 361021, China
Journal Name
Processes
Volume
12
Issue
2
First Page
414
Year
2024
Publication Date
2024-02-18
ISSN
2227-9717
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Original Submission
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PII: pr12020414, Publication Type: Journal Article
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LAPSE:2024.1079
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https://doi.org/10.3390/pr12020414
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[v1] (Original Submission)
Jun 10, 2024
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Jun 10, 2024
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