Multiobjective structural damage identification in uncertain environments

Evolutionary algorithms are suitable to solve damage identification problems in a multiobjective context. However, the performance of these methods can deteriorate quickly with increasing noise intensities originating numerous uncertainties. In this paper, a statistic structural damage detection met...

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Bibliographic Details
Main Authors: Ruiz A., Perera R., Sevillano E.
Format: Article
Language:English
Published: EDP Sciences 2012-07-01
Series:MATEC Web of Conferences
Online Access:http://dx.doi.org/10.1051/matecconf/20120101006
Description
Summary:Evolutionary algorithms are suitable to solve damage identification problems in a multiobjective context. However, the performance of these methods can deteriorate quickly with increasing noise intensities originating numerous uncertainties. In this paper, a statistic structural damage detection method formulated in a multiobjective context is proposed. The statistic analysis is implemented to take into account the uncertainties existing in the structural model and measured structural modal parameters. The presented method is verified by a number of simulated damage scenarios. The effects of noise and damage levels on damage detection are investigated.
ISSN:2261-236X