Combination of wavelet transform and extreme learning machine for detecting damages in composite plates-Reference-Cited by-同舟云学术

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Combination of wavelet transform and extreme learning machine for detecting damages in composite plates

Published:2023-11 Issue: Volume:57 Page:105242
ISSN:2352-0124
Container-title:Structures
language:en
Short-container-title:Structures

Author:

Jiang Yongying,Shao Liang,Xiang Jiawei^ORCID

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Publisher

Elsevier BV

Subject

Safety, Risk, Reliability and Quality,Building and Construction,Architecture,Civil and Structural Engineering

Reference56 articles.

1. Multiple damage detection in laminated composite beams using automated model update;Kahya;Structures,2021

2. Damage detection in beam structures using Bayesian deep learning and balancing composite motion optimization;Nguyen;Structures,2022

3. Seismic behavior of damaged RC columns repaired with FRCM composites;Toska;Eng Struct,2022

4. Flexural behavior of fire-damaged concrete beams repaired with strain-hardening cementitious composite;Li;Eng Struct,2022

5. Fatigue performance of stud shear connectors in steel-concrete composite beam with initial damage;Lu;Eng Struct,2023

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An effective vibration-based feature extraction method for single and multiple damage localization in thin-walled plates using one-dimensional wavelet transform: A numerical and experimental study;Thin-Walled Structures;2024-11

2. Time-varying damage detection in beam structures using variational mode decomposition and continuous wavelet transform;Construction and Building Materials;2024-01

3. Multi-Damage Quantitative Detection in Composite Wind Turbine Blade Combining Curvature Modal Shape Based on the Surface Interpolation Method with Extreme Learning Machine;2023

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