2021
DOI: 10.1155/2021/8863107
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Performance of Fitness Functions Based on Natural Frequencies in Defect Detection Using the Standard PSO‐FEM Approach

Abstract: Structural defect detection based on finite element model (FEM) updating is an optimization problem by minimizing the discrepancy of responses between model and measurement. Researchers have introduced many methods to perform the FEM updating for defect detection of the structures. A popular approach is to adopt the particle swarm optimization (PSO) algorithm. In this process, the fitness function is a critical factor in the success of the PSO-FEM approach. Our objective is to compare the performances of four … Show more

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Cited by 8 publications
(6 citation statements)
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“…In the BAS algorithm, the smaller the fitness value, the better the system performance [32]. Hence, the inverse of the performance index function is used as the fitness function as shown in Eq.…”
Section: Design Of Fitness Functionmentioning
confidence: 99%
“…In the BAS algorithm, the smaller the fitness value, the better the system performance [32]. Hence, the inverse of the performance index function is used as the fitness function as shown in Eq.…”
Section: Design Of Fitness Functionmentioning
confidence: 99%
“…In this article, m = 9 is used uniformly. Besides, when compared with other forms of the fitness function composed of pure natural frequencies, the superiority of fitness function that is shown in Equation ( 7) has been demonstrated in [24].…”
Section: Fitness Functionmentioning
confidence: 99%
“…The defective element, simulating the crack, commonly has a reduced Young's modulus. In most of the studies, the number of finite elements in the model is taken between 4 and 30, and the reduction of the elastic modulus of an element is in the range of 20% to 50%, see, for example, [7][8][9][10][11]. This approach requires centering the crack on an element and, therefore, the precision of assessing damage is determined by the distribution of the elements along the beam [10].…”
Section: Introductionmentioning
confidence: 99%