Volume 2, Issue 3 (7-2012)
IJOCE 2012, 2(3): 321-339 |
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Kaveh A, Zolghadr A. AN IMPROVED CHARGED SYSTEM SEARCH FOR STRUCTURAL DAMAGE IDENTIFICATION IN BEAMS AND FRAMES USING CHANGES IN NATURAL FREQUENCIES. IJOCE 2012; 2 (3) :321-339
URL: http://ijoce.iust.ac.ir/article-1-94-en.html
URL: http://ijoce.iust.ac.ir/article-1-94-en.html
Abstract: (21378 Views)
It is well known that damaged structural members may alter the behavior of the structures considerably. Careful observation of these changes has often been viewed as a means to identify and assess the location and severity of damages in structures. Among the responses of a structure, natural frequencies are both relatively easy to obtain and independent from external excitation, and therefore, could be used as a measure of the structure's behavior before and after an extreme event which might have lead to damage in the structure. Inverse problem of detection and assessment of structural damage using the changes in natural frequencies is addressed in this paper. This can be considered as an optimization problem with the location and severity of the damages being its variables. The objective is to set these variables such that the natural frequencies of the finite element model correspond to the experimentally measured frequencies of the actual damaged structure. In practice, although the exact number of damaged elements is unknown, it is usually believed to be small compared to the total number of elements of the structure. In beams and frames particularly, the necessity to divide the structural members into smaller ones in order to detect the location of the cracks more accurately, deepens this difference. This can significantly improve the performance of the optimization algorithms in solving the inverse problem of damage detection. In this paper, the Charged System Search algorithm developed by Kaveh and Talatahari [1] is improved to comprise the above mentioned point. The performance of the improved algorithm is then compared to the standard one in order to emphasize the efficiency of the proposed algorithm in damage detection inverse problems.
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