Damage Detection through Genetic and Swarm-Based Optimization Algorithms

Koh, Bong-Hwan; Choi, Jong-Hun; Jeong, Minjoong

doi:10.1061/41096(366)215

Cited by 1 publication

(1 citation statement)

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“…Various methods can be applied to generate basic population such as Monte Carlo [18], Latin Hypercube Sampling [19], and Space-Filling Model [20]. These methods include each their own applications for different engineering issues.…”

Section: Moga and Mmogamentioning

confidence: 99%

Detecting structural damage in Timoshenko beams based on optimization via simulation (OVS)

Farokhzad¹,

Mohebi²,

Amiri³

et al. 2016

J. vibroeng.

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Abstract. Considering easy determination of natural frequency in structures leads researchers to focus on detecting the damage through the dynamic parameters using combination of various artificial intelligence algorithms. The main contribution of this research is to detect damage in structures (including its depth and location) for the deep beams with Timoshenko behavior using optimization via simulation (OVS). This method is established based on the first three natural frequencies of the deep or semi-deep beams. The finite element method (FEM) is conducted to obtain essential inputs parameters for OVS. The exact location and depth of the structural damage are determined, using combination of multi-objective optimization algorithms, multi-objective genetic algorithm (MOGA), and modified multi-objective genetic algorithm (MMOGA). This research also remarkably concerns about detecting the location of the defect in the beams with several cracks. In order to verify the results obtained from numerical analysis, several experimental specimens are presented. The dynamics parameters of the beams are experimentally identified using modal hammer. The responses obtained from the numerical method, proposed in this research, are also compared with the results obtained from previous studies. Practically, a beam with real dimensions is examined for different boundary conditions. In addition, the results obtained from MOGA and MMOGA are compared with the other researchers' achievements. Finally, it was observed that the proposed method, (OVS), can be satisfyingly determined the exact location and depth of damage with the high accuracy.Keywords: first three natural frequency, multi-objective genetic algorithm (MOGA), modified multi-objective genetic algorithm (MMOGA), optimization via simulation (OVS), and Timoshenko beam.

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Section: Moga and Mmogamentioning

confidence: 99%