Structural Damage Identification via Modal Data Based on Genetic Algorithm

2010 ◽  
Author(s):  
Jie Li ◽  
Bihai Liao ◽  
Minshui Huang
Keyword(s):  
Genetic Algorithm ◽  
Structural Damage ◽  
Damage Identification ◽  
Modal Data ◽  
Structural Damage Identification

scholarly journals A Combined Modal Correlation Criterion for Structural Damage Identification with Noisy Modal Data

2018 ◽  
Vol 2018 ◽  
pp. 1-20 ◽  
Author(s):  
Manolis Georgioudakis ◽  
Vagelis Plevris
Keyword(s):  
Structural Damage ◽  
High Efficiency ◽  
Damage Identification ◽  
Model Updating ◽  
Search Algorithm ◽  
Element Model ◽  
Identification Problem ◽  
Damage Scenarios ◽  
Modal Data ◽  
Structural Damage Identification

Structural damage identification is a scientific field that has attracted a lot of interest in the scientific community during the recent years. There have been many studies intending to find a reliable method to identify damage in structural elements both in location and extent. Most damage identification methods are based on the changes of dynamic characteristics and static responses, but the incompleteness of the test data is a great obstacle for both. In this paper, a structural damage identification method based on the finite element model updating is proposed, in order to provide the location and the extent of structural damage using incomplete modal data of a damaged structure. The structural damage identification problem is treated as an unconstrained optimization problem which is solved using the differential evolution search algorithm. The objective function used in the optimization process is based on a combination of two modal correlation criteria, providing a measure of consistency and correlation between estimations of mode shape vectors. The performance and robustness of the proposed approach are evaluated with two numerical examples: a simply supported concrete beam and a concrete frame under several damage scenarios. The obtained results exhibit high efficiency of the proposed approach for accurately identifying the location and extent of structural damage.

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