DocumentCode :
3367173
Title :
Study on damage identification for bridge structure based on improved genetic algorithm
Author :
Huang, Minshui ; Li, Jie ; Lu, Xinhai ; Hu, Guoxiqang ; Yu, Jing
fYear :
2010
fDate :
26-28 June 2010
Firstpage :
990
Lastpage :
994
Abstract :
A damage identification method based on improved genetic algorithm (IGA) is presented that accurately identifies both the location and severity of damage in a simulated 3-span continuous beam bridge. Damage identification based on finite element model updating is often used and damage is identified by minimizing the error between measured and analytical results. But whether model updating can be carried out successfully mainly depend on accuracy of model, quality of vibration testing, definition of optimization problem and calculation performance of optimization algorithm. In the paper, the construction technique of objective function based on modal parameters is introduced firstly, an improved genetic algorithm (IGA) is presented secondly. In the end, through the simulation of a continuous beam bridge damage identification is studied comparatively. From the results it can be seen that the damage identification method developed using IGA provides greater accuracy in identifying the location and severity of damage.
Keywords :
beams (structures); bridges (structures); finite element analysis; genetic algorithms; structural engineering; bridge structure; damage identification; finite element model; genetic algorithm; optimization problem; simulated 3-span continuous beam bridge; vibration testing; Analytical models; Bridges; Civil engineering; Finite element methods; Genetic algorithms; Monitoring; Optimization methods; Structural beams; Testing; Vibrations; bridge structure; damage identification; improved genetic algorithm (IGA);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
Type :
conf
DOI :
10.1109/MACE.2010.5536663
Filename :
5536663
Link To Document :
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