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Review
. 2018;30(2):389-411.
doi: 10.1007/s00521-017-3284-1. Epub 2017 Nov 22.

Structural damage detection using finite element model updating with evolutionary algorithms: a survey

Nizar Faisal Alkayem  1 , Maosen Cao  1 , Yufeng Zhang  2   3 , Mahmoud Bayat  4 , Zhongqing Su  5
Affiliations
Review

Structural damage detection using finite element model updating with evolutionary algorithms: a survey

Nizar Faisal Alkayem et al. Neural Comput Appl. 2018.

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.

Keywords: Dynamic characteristics; Evolutionary algorithms; Finite element model updating; Optimization; Residuals; Structural damage detection.

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Conflict of interest statement

Compliance with ethical standardsThe authors declare that there is no conflict of interests regarding the publication of this paper.

Figures

Fig. 1
Fig. 1
FE model updating approaches
Fig. 2
Fig. 2
The organization of structural damage detection using FE model updating with EAs
Fig. 3
Fig. 3
FE model updating using single-objective EAs for damage identification
Fig. 4
Fig. 4
Convex Pareto front (a) and non-convex Pareto front (b)
Fig. 5
Fig. 5
FE model updating using multi-objective EAs for structural damage identification
Fig. 6
Fig. 6
The ASC–ASCE SHM benchmark 4-story building model. a The original model [154], b the developed model
Fig. 7
Fig. 7
The damage scenario
Fig. 8
Fig. 8
Damage detection using GA
Fig. 9
Fig. 9
Damage detection using GA under noisy conditions
Fig. 10
Fig. 10
Damage detection using PSO
Fig. 11
Fig. 11
Damage detection using PSO under noisy conditions
Fig. 12
Fig. 12
Damage detection using MOPSO
Fig. 13
Fig. 13
Damage detection using MOPSO under noisy conditions
See this image and copyright information in PMC

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