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Doctoral Thesis
DOI
10.11606/T.18.2007.tde-09082007-142229
Document
Author
Full name
Oscar Javier Begambre Carrillo
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2007
Supervisor
Committee
Laier, José Elias (President)
Beck, André Teófilo
Dias, Carlos Alberto Nunes
Libardi, Walter
Santos, José Maria Campos dos
Title in Portuguese
Algoritmo híbrido para avaliação da integridade estrutural: uma abordagem heurística
Keywords in Portuguese
Identificação de dano
Oscilador não linear
Particle Swarm Optimization
Problemas inversos
Simulated annealing
Vigas fissuradas
Abstract in Portuguese
Neste estudo, o novo algoritmo hibrido autoconfigurado PSOS (Particle Swarm Optimization - Simplex) para avaliação da integridade estrutural a partir de respostas dinâmicas é apresentado. A formulação da função objetivo para o problema de minimização definido emprega funções de resposta em freqüência e/ou dados modais do sistema. Uma nova estratégia para o controle dos parâmetros do algoritmo Particle Swarm Optimization (PSO), baseada no uso do método de Nelder - Mead é desenvolvida; conseqüentemente, a convergência do PSO fica independente dos parâmetros heurísticos e sua estabilidade e precisão são melhoradas. O método híbrido proposto teve melhor desempenho, nas diversas funções teste analisadas, quando comparado com os algoritmos simulated annealing, algoritmos genéticos e o PSO. São apresentados diversos problemas de detecção de dano, levando em conta os efeitos do ruído e da falta de dados experimentais. Em todos os casos, a posição e extensão do dano foram determinadas com sucesso. Finalmente, usando o PSOS, os parâmetros de um oscilador não linear (oscilador de Duffing) foram identificados.
Title in English
Hybrid algorithm for damage detection: a heuristic approach
Keywords in English
Cracked beam
Damage identification
Inverse problems
Non-linear oscillator
Particle Swarm Optimization
Simulated annealing
Abstract in English
In this study, a new auto configured Particle Swarm Optimization - Simplex algorithm for damage detection has been proposed. The formulation of the objective function for the minimization problem is based on the frequency response functions (FRFs) and the modal parameters 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 accuracy are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA), the Genetic Algorithm (GA) and the basic PSO. Several damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied. In these cases, the damage location and extent were determined successfully. Finally, using the PSOS, a non-linear oscillator (Duffing oscillator) was identified with good results.
 
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BegT.pdf (1.02 Mbytes)
Publishing Date
2007-09-19
 
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