Structural edge damage detection based on wavelet transform and immune genetic algorithm
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 s...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-87712-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823862481398792192 |
|---|---|
| author | Jianwei Zhao Zhuo Zhou Deqing Guan Liang Gong |
| author_facet | Jianwei Zhao Zhuo Zhou Deqing Guan Liang Gong |
| author_sort | Jianwei Zhao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-62765b88ac574f71ad7d8ead18b3e502 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-62765b88ac574f71ad7d8ead18b3e5022025-02-09T12:31:58ZengNature PortfolioScientific Reports2045-23222025-02-0115111810.1038/s41598-025-87712-2Structural edge damage detection based on wavelet transform and immune genetic algorithmJianwei Zhao0Zhuo Zhou1Deqing Guan2Liang Gong3Department of Civil Engineering, Changsha University of Science and TechnologyDepartment of Civil Engineering, Changsha University of Science and TechnologyHunan University of Information TechnologyDepartment of Civil Engineering, Changsha University of Science and TechnologyAbstract 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.https://doi.org/10.1038/s41598-025-87712-2Edge effectFitting extensionWavelet transformIntelligent algorithmsImmune-genetic |
| spellingShingle | Jianwei Zhao Zhuo Zhou Deqing Guan Liang Gong Structural edge damage detection based on wavelet transform and immune genetic algorithm Scientific Reports Edge effect Fitting extension Wavelet transform Intelligent algorithms Immune-genetic |
| title | Structural edge damage detection based on wavelet transform and immune genetic algorithm |
| title_full | Structural edge damage detection based on wavelet transform and immune genetic algorithm |
| title_fullStr | Structural edge damage detection based on wavelet transform and immune genetic algorithm |
| title_full_unstemmed | Structural edge damage detection based on wavelet transform and immune genetic algorithm |
| title_short | Structural edge damage detection based on wavelet transform and immune genetic algorithm |
| title_sort | structural edge damage detection based on wavelet transform and immune genetic algorithm |
| topic | Edge effect Fitting extension Wavelet transform Intelligent algorithms Immune-genetic |
| url | https://doi.org/10.1038/s41598-025-87712-2 |
| work_keys_str_mv | AT jianweizhao structuraledgedamagedetectionbasedonwavelettransformandimmunegeneticalgorithm AT zhuozhou structuraledgedamagedetectionbasedonwavelettransformandimmunegeneticalgorithm AT deqingguan structuraledgedamagedetectionbasedonwavelettransformandimmunegeneticalgorithm AT lianggong structuraledgedamagedetectionbasedonwavelettransformandimmunegeneticalgorithm |