Detecting damage location and severity in a double layer grid using modal strain energy method and data fusion
Changes in modal strain energy of elements before and after damage is a robust damage detection index. However, in structures like double layer grids which have large number of elements, this method has some problems. First, In large structures this method needs more mode shapes to detect damage thr...
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | FA |
| Publié: |
Iranian Society of Structrual Engineering (ISSE)
2020
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/70b1438754fb4daf8e32c89e5db0f16b |
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| Résumé: | Changes in modal strain energy of elements before and after damage is a robust damage detection index. However, in structures like double layer grids which have large number of elements, this method has some problems. First, In large structures this method needs more mode shapes to detect damage through modal strain energy method which in practice is difficult to determine. Second, this method introduce some healthy elements as damaged element. To overcome these problems, in this paper a two stage damage detection technique based on modal strain energy method is presented for detecting damage in double layer grids. First, the Modal Strain Energy Based Index (MSEBI) for each mode shape is determined. Then a data fusion technique based on Bayesian theory is used to combine MSEBI values obtained from each mode shape to find damaged elements. Then Charged System Search (CSS) optimization method which is a powerful optimization method is employed to optimize an objective function based on natural frequency to determine damage severity of damaged elements. To demonstrate the performance of the proposed method, a large double layer grid with 1536 elements and different single and multiple damage cases is considered. Numerical results show that the proposed method can successfully find damaged elements and their severities using only few first numbers of mode shapes and frequencies. |
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