Advanced Damage Monitoring in Beam Structures Using Grey Wolf Optimizer and Additional Masses
Dynamic characteristics are of significant interest to researchers in the field of damage detection. Among these, natural frequencies stand out due to their high accuracy and resistance to noise. However, relying solely on natural frequencies is often insufficient for determining the depth and locat...
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MDPI AG
2025-01-01
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| author | Abdallah Salama Alaa El-Sisi Atef Eraky Shimaa Emad |
| author_facet | Abdallah Salama Alaa El-Sisi Atef Eraky Shimaa Emad |
| author_sort | Abdallah Salama |
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| description | Dynamic characteristics are of significant interest to researchers in the field of damage detection. Among these, natural frequencies stand out due to their high accuracy and resistance to noise. However, relying solely on natural frequencies is often insufficient for determining the depth and location of damage. To address this limitation, additional masses can be strategically placed at different locations on structural elements, altering the natural frequencies. Each mass placement creates a distinct dynamic scenario with a unique frequency profile, enabling a more comprehensive analysis. In this study, additional masses were introduced at specific elements of the beam structure within the numerical model which were then strategically placed at various locations along the beam. The resulting shifts in natural frequencies served as inputs to the Grey Wolf Optimizer (GWO), which identified elements with stiffness reductions indicative of damage. A custom MATLAB code was developed to perform finite element analysis on the numerical model. The results were validated against previously published experimental data, demonstrating the method’s reliability with a 5% difference. A parametric study involving both simple and continuous span beams was performed. The procedure effectively detected damage severities of 10%, 25%, and 50%, with corresponding errors of 4.3%, 0.44%, and 0.02%, respectively. |
| format | Article |
| id | doaj-art-99e722e1795045e0b4baf72d165fb5bf |
| institution | Kabale University |
| issn | 2075-5309 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-99e722e1795045e0b4baf72d165fb5bf2025-01-24T13:26:27ZengMDPI AGBuildings2075-53092025-01-0115227910.3390/buildings15020279Advanced Damage Monitoring in Beam Structures Using Grey Wolf Optimizer and Additional MassesAbdallah Salama0Alaa El-Sisi1Atef Eraky2Shimaa Emad3Department of Structural Engineering, Faculty of Engineering, Zagazig University, Zagazig 44519, EgyptDepartment of Civil Engineering, Southern Illinois University Edwardsville, Edwardsville, IL 62026, USADepartment of Structural Engineering, Faculty of Engineering, Zagazig University, Zagazig 44519, EgyptDepartment of Structural Engineering, Faculty of Engineering, Zagazig University, Zagazig 44519, EgyptDynamic characteristics are of significant interest to researchers in the field of damage detection. Among these, natural frequencies stand out due to their high accuracy and resistance to noise. However, relying solely on natural frequencies is often insufficient for determining the depth and location of damage. To address this limitation, additional masses can be strategically placed at different locations on structural elements, altering the natural frequencies. Each mass placement creates a distinct dynamic scenario with a unique frequency profile, enabling a more comprehensive analysis. In this study, additional masses were introduced at specific elements of the beam structure within the numerical model which were then strategically placed at various locations along the beam. The resulting shifts in natural frequencies served as inputs to the Grey Wolf Optimizer (GWO), which identified elements with stiffness reductions indicative of damage. A custom MATLAB code was developed to perform finite element analysis on the numerical model. The results were validated against previously published experimental data, demonstrating the method’s reliability with a 5% difference. A parametric study involving both simple and continuous span beams was performed. The procedure effectively detected damage severities of 10%, 25%, and 50%, with corresponding errors of 4.3%, 0.44%, and 0.02%, respectively.https://www.mdpi.com/2075-5309/15/2/279damage detectionnumerical modelinggrey wolfadditional massesstructure dynamicsbeams |
| spellingShingle | Abdallah Salama Alaa El-Sisi Atef Eraky Shimaa Emad Advanced Damage Monitoring in Beam Structures Using Grey Wolf Optimizer and Additional Masses Buildings damage detection numerical modeling grey wolf additional masses structure dynamics beams |
| title | Advanced Damage Monitoring in Beam Structures Using Grey Wolf Optimizer and Additional Masses |
| title_full | Advanced Damage Monitoring in Beam Structures Using Grey Wolf Optimizer and Additional Masses |
| title_fullStr | Advanced Damage Monitoring in Beam Structures Using Grey Wolf Optimizer and Additional Masses |
| title_full_unstemmed | Advanced Damage Monitoring in Beam Structures Using Grey Wolf Optimizer and Additional Masses |
| title_short | Advanced Damage Monitoring in Beam Structures Using Grey Wolf Optimizer and Additional Masses |
| title_sort | advanced damage monitoring in beam structures using grey wolf optimizer and additional masses |
| topic | damage detection numerical modeling grey wolf additional masses structure dynamics beams |
| url | https://www.mdpi.com/2075-5309/15/2/279 |
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