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Structural Engineering and Mechanics
  Volume 70, Number 3, May10 2019, pages 339-350
DOI: http://dx.doi.org/10.12989/sem.2019.70.3.339
 


Evolutionary-base finite element model updating and damage detection using modal testing results
Mehdi Vahidi, Shahram Vahdani, Mohammad Rahimian, Nima Jamshidi and Alireza Taghavee Kanee

 
Abstract
    This research focuses on finite element model updating and damage assessment of structures at element level based on global nondestructive test results. For this purpose, an optimization system is generated to minimize the structural dynamic parameters discrepancies between numerical and experimental models. Objective functions are selected based on the square of Euclidean norm error of vibration frequencies and modal assurance criterion of mode shapes. In order to update the finite element model and detect local damages within the structural members, modern optimization techniques is implemented according to the evolutionary algorithms to meet the global optimized solution. Using a simulated numerical example, application of genetic algorithm (GA), particle swarm (PSO) and artificial bee colony (ABC) algorithms are investigated in FE model updating and damage detection problems to consider their accuracy and convergence characteristics. Then, a hybrid multi stage optimization method is presented merging advantages of PSO and ABC methods in finding damage location and extent. The efficiency of the methods have been examined using two simulated numerical examples, a laboratory dynamic test and a high-rise building field ambient vibration test results. The implemented evolutionary updating methods show successful results in accuracy and speed considering the incomplete and noisy experimental measured data.
 
Key Words
    Finite Element Model updating; GA; PSO; ABC; hybrid optimization; damage detection, modal analysis
 
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