Evidence map›Paper›PMID 37376293›Full record

ArticlePolymers2023

Identification of NOL-Ring Composite Materials' Damage Mechanism Based on the STOA-VMD Algorithm.

Peng Jiang, Hui Li, Xiaowei Yan, Luying Zhang, Wei Li

Abstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Peng JiangCollege of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, China.
Hui LiCollege of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, China.
Xiaowei YanShandong Gaint E-Tech Co., Ltd., Jinan 250000, China.
Luying ZhangCollege of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, China.
Wei LiCollege of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, China.

Funding

Key R&D plan of Hainan Province ZDYF2023GXJS014Natural Science Foundation of Heilongjiang Province of China LH2022E029Postdoctoral Research Foundation project of Heilongjiang Province LBH-Q21083
6 · The paper itself

Abstract

This research utilized the sooty tern optimization algorithm-variational mode decomposition (STOA-VMD) optimization algorithm to extract the acoustic emission (AE) signal associated with damage in fiber-reinforced composite materials. The effectiveness of this optimization algorithm was validated through a tensile experiment on glass fiber/epoxy NOL-ring specimens. To solve the problems of a high degree of aliasing, high randomness, and a poor robustness of AE data of NOL-ring tensile damage, the signal reconstruction method of optimized variational mode decomposition (VMD) was first used to reconstruct the damage signal and the parameters of VMD were optimized by the sooty tern optimization algorithm. The optimal decomposition mode number K and penalty coefficient α were introduced to improve the accuracy of adaptive decomposition. Second, a typical single damage signal feature was selected to construct the damage signal feature sample set and a recognition algorithm was used to extract the feature of the AE signal of the glass fiber/epoxy NOL-ring breaking experiment to evaluate the effectiveness of the damage mechanism recognition. The results showed that the recognition rates of the algorithm in matrix cracking, fiber fracture, and delamination damage were 94.59%, 94.26%, and 96.45%, respectively. The damage process of the NOL-ring was characterized and the findings indicated that it was highly efficient in the feature extraction and recognition of polymer composite damage signals.

Indexed as

acoustic emissioncomposite materialsglass fiber/epoxy NOL-ringsmatrix crackingpattern recognitionvariational mode decomposition

Identifiers

PMID37376293
PMCPMC10304721

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