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Multiple damage detection in composite beams using particle swarm optimization and genetic algorithm

(2017) MECHANIKA. 23(4). p.514-521
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Abstract
This paper presents a methodology for damage detection and localization in composite beams using vibration data, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The data was acquired by developing a program that performs dynamic analysis of unidirectional graphite -epoxy composite beams based on the Finite Element Method (FEM). The objective function makes use of natural frequencies and Modal Assurance Criterion. The proposed methodology is validated using numerically simulated data and experimental data. A comparative study between the performances of PSO and GA in detecting multiple and single damage scenarios is carried out. Then, the effect of noise is investigated by taking different noise levels in the modal data It appears that the noise has a negligible effect on the performance of the presented approaches.
Keywords
Damage detection, composite beams, modal analysis, Finite Element Analysis, Particle Swarm Optimization, Genetic Algorithm, MODE SHAPE, SENSITIVITY

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Please use this url to cite or link to this publication:

MLA
Khatir, Samir, et al. “Multiple Damage Detection in Composite Beams Using Particle Swarm Optimization and Genetic Algorithm.” MECHANIKA, vol. 23, no. 4, 2017, pp. 514–21.
APA
Khatir, S., Belaidi, I., Khatir, T., Hamrani, A., Zhou, Y.-L., & Abdel Wahab, M. (2017). Multiple damage detection in composite beams using particle swarm optimization and genetic algorithm. MECHANIKA, 23(4), 514–521.
Chicago author-date
Khatir, Samir, Idir Belaidi, Tawfiq Khatir, Abderrachid Hamrani, Yun-Lai Zhou, and Magd Abdel Wahab. 2017. “Multiple Damage Detection in Composite Beams Using Particle Swarm Optimization and Genetic Algorithm.” MECHANIKA 23 (4): 514–21.
Chicago author-date (all authors)
Khatir, Samir, Idir Belaidi, Tawfiq Khatir, Abderrachid Hamrani, Yun-Lai Zhou, and Magd Abdel Wahab. 2017. “Multiple Damage Detection in Composite Beams Using Particle Swarm Optimization and Genetic Algorithm.” MECHANIKA 23 (4): 514–521.
Vancouver
1.
Khatir S, Belaidi I, Khatir T, Hamrani A, Zhou Y-L, Abdel Wahab M. Multiple damage detection in composite beams using particle swarm optimization and genetic algorithm. MECHANIKA. 2017;23(4):514–21.
IEEE
[1]
S. Khatir, I. Belaidi, T. Khatir, A. Hamrani, Y.-L. Zhou, and M. Abdel Wahab, “Multiple damage detection in composite beams using particle swarm optimization and genetic algorithm,” MECHANIKA, vol. 23, no. 4, pp. 514–521, 2017.
@article{8530977,
  abstract     = {{This paper presents a methodology for damage detection and localization in composite beams using vibration data, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The data was acquired by developing a program that performs dynamic analysis of unidirectional graphite -epoxy composite beams based on the Finite Element Method (FEM). The objective function makes use of natural frequencies and Modal Assurance Criterion. The proposed methodology is validated using numerically simulated data and experimental data. A comparative study between the performances of PSO and GA in detecting multiple and single damage scenarios is carried out. Then, the effect of noise is investigated by taking different noise levels in the modal data It appears that the noise has a negligible effect on the performance of the presented approaches.}},
  author       = {{Khatir, Samir and Belaidi, Idir and Khatir, Tawfiq and Hamrani, Abderrachid and Zhou, Yun-Lai and Abdel Wahab, Magd}},
  issn         = {{1392-1207}},
  journal      = {{MECHANIKA}},
  keywords     = {{Damage detection,composite beams,modal analysis,Finite Element Analysis,Particle Swarm Optimization,Genetic Algorithm,MODE SHAPE,SENSITIVITY}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{514--521}},
  title        = {{Multiple damage detection in composite beams using particle swarm optimization and genetic algorithm}},
  url          = {{http://dx.doi.org/10.5755/j01.mech.23.4.15254}},
  volume       = {{23}},
  year         = {{2017}},
}

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