A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
18/10/2012
18/10/2012
2009
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Resumo |
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 (PSO(b)). 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 CNPq - Brazil (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico) |
Identificador |
ADVANCES IN ENGINEERING SOFTWARE, v.40, n.9, p.883-891, 2009 0965-9978 http://producao.usp.br/handle/BDPI/17873 10.1016/j.advengsoft.2009.01.004 |
Idioma(s) |
eng |
Publicador |
ELSEVIER SCI LTD |
Relação |
Advances in Engineering Software |
Direitos |
restrictedAccess Copyright ELSEVIER SCI LTD |
Palavras-Chave | #Particle Swarm Optimization #Damage identification #Inverse problems #Truss structure #Cracked beam #Non-linear oscillator #GLOBAL OPTIMIZATION #FAULT-DETECTION #PREDICTION #MODELS #Computer Science, Interdisciplinary Applications #Computer Science, Software Engineering |
Tipo |
article original article publishedVersion |