Evidence map›Paper›PMID 39910209›Full record

ArticleScientific reports2025

Structural edge damage detection based on wavelet transform and immune genetic algorithm.

Jianwei Zhao, Zhuo Zhou, Deqing Guan, Liang Gong

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jianwei ZhaoDepartment of Civil Engineering, Changsha University of Science and Technology, Changsha, Hunan, China.
Zhuo ZhouDepartment of Civil Engineering, Changsha University of Science and Technology, Changsha, Hunan, China.
Deqing GuanHunan University of Information Technology, Changsha, Hunan, China. Guan491596452@163.com.
Liang GongDepartment of Civil Engineering, Changsha University of Science and Technology, Changsha, Hunan, China.

Funding

Hunan Graduate Scientific Research Innovation Project of China No. CX20200815Hunan Graduate Scientific Research Innovation Project of China No. CX20210737National Natural Science Foundation of China No.5138079
6 · The paper itself

Abstract

The wavelet transform (WT) has gained significant attention for its ability to identify damage details within strain modes. However, edge damage in structures often remains obscured and unrecognizable when WT is applied, primarily due to edge effects. Intelligent algorithms used to assess structural damage severity often face challenges such as premature convergence and a tendency to settle on local optima. To address these challenges, damage location is analyzed using WT with a fitting extension of the original vibration signal, effectively mitigating edge effects. Additionally, an immune-genetic algorithm, integrating genetic and immune algorithms, is employed to overcome limitations of traditional intelligent algorithms in damage severity identification. The two-stage method's effectiveness was validated through finite element simulations of fixed beam and frame structures, as well as vibration tests of fixed and cantilever beams, for locating and assessing edge damage. This method showed clear advantages, including precise damage characterization, noise robustness, and high sensitivity to edge damage.

Indexed as

Edge effectFitting extensionImmune-geneticIntelligent algorithmsWavelet transform

Identifiers

PMID39910209
PMCPMC11799308

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.