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A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

delete2009-09-01
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PRE
AI
Ó
Óscar Begambre *
J
José Elías Laier
DOI:10.1016/j.advengsoft.2009.01.004delete
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摘要

摘要

En 中文
This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSOb). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved
Keyword:
Particle Swarm Optimization
Damage identification
Inverse problems
Truss structure
Cracked beam
Non-linear oscillator

期刊

Advances in Engineering Software 封面图
Advances in Engineering Software
IF:
5.7
论文数:
3.4K
被引数:
1.2W

机构

U
universidade de sao paulo
学者数:
10.6W
论文数: 6.7W
被引数: 93
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