Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77339
Title: Structural damage detection using finite element model updating with evolutionary algorithms : a survey
Authors: Alkayem, NF
Cao, M
Zhang, Y
Bayat, M
Su, Z 
Keywords: Dynamic characteristics
Evolutionary algorithms
Finite element model updating
Optimization
Residuals
Structural damage detection
Issue Date: 2018
Publisher: Springer
Source: Neural computing and applications, 2018, v. 30, no. 2, p. 389-411 How to cite?
Journal: Neural computing and applications 
Abstract: Structural damage identification based on finite element (FE) model updating has been a research direction of increasing interest over the last decade in the mechanical, civil, aerospace, etc., engineering fields. Various studies have addressed direct, sensitivity-based, probabilistic, statistical, and iterative methods for updating FE models for structural damage identification. In contrast, evolutionary algorithms (EAs) are a type of modern method for FE model updating. Structural damage identification using FE model updating by evolutionary algorithms is an active research focus in progress but lacking a comprehensive survey. In this situation, this study aims to present a review of critical aspects of structural damage identification using evolutionary algorithm-based FE model updating. First, a theoretical background including the structural damage detection problem and the various types of FE model updating approaches is illustrated. Second, the various residuals between dynamic characteristics from FE model and the corresponding physical model, used for constructing the objective function for tracking damage, are summarized. Third, concerns regarding the selection of parameters for FE model updating are investigated. Fourth, the use of evolutionary algorithms to update FE models for damage detection is examined. Fifth, a case study comparing the applications of two single-objective EAs and one multi-objective EA for FE model updating-based damage detection is presented. Finally, possible research directions for utilizing evolutionary algorithm-based FE model updating to solve damage detection problems are recommended. This study should help researchers find crucial points for further exploring theories, methods, and technologies of evolutionary algorithm-based FE model updating for structural damage detection.
URI: http://hdl.handle.net/10397/77339
ISSN: 0941-0643
DOI: 10.1007/s00521-017-3284-1
Rights: © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
The following article: Alkayem, N. F., Cao, M., Zhang, Y., Bayat, M., & Su, Z. (2018). Structural damage detection using finite element model updating with evolutionary algorithms: a survey. Neural Computing and Applications, 30: 389, is available at https//doi.org/10.1007/s00521-017-3284-1
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