AN HYBRID STOCHASTIC-DETERMINISTIC OPTIMIZATION ALGORITHM FOR STRUCTURAL DAMAGE IDENTIFICATION

• Autor(a) principal: Nhamage, Idilson António
• Data de Publicação: 2017
• Outros Autores: Lopez, Rafael Holdorf, Miguel, Leandro Fleck Fadel, Miguel, Letícia Fleck Fadel, Torii, André Jacomel
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Interdisciplinar de Pesquisa em Engenharia
• Texto Completo: https://periodicos.unb.br/index.php/ripe/article/view/21658
• topic: Structural health monitoring. Hybrid stochastic/deterministic (P-NMA) optimization method. Nelder-Mead algorithm. Representation formula of Pincus.

This paper presents a hybrid stochastic/deterministic optimization algorithm to solve the target optimization problem of vibration-based damage detection. The use of a numerical solution of the representation formula to locate the region of the global solution, i.e., to provide a starting point for the local optimizer, which is chosen to be the Nelder-Mead algorithm (NMA), is proposed. A series of numerical examples with different damage scenarios and noise levels was performed under impact and ambient vibrations. To test the accuracy and efficiency of the optimization algorithm, its results were compared to previous procedures available in the literature, which employed different solutions such as the genetic algorithm (GA) and the harmony search algorithm (HS). The performance of the proposed optimization scheme was more accurate and required a lower computational cost than the GA and HS algorithms, emphasizing the capacity of the proposed methodology for its use in damage diagnosis and assessment.