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11 (1) 2021

The Particle Swarm Optimization (PSO) algorithm in Structural Health Monitoring (SHM) application


Author - Affiliation:
Le Thanh Cuong - Ho Chi Minh City Open university , Vietnam
To Thanh Sang - Ho Chi Minh City Open University , Vietnam
Corresponding author: Le Thanh Cuong - cuong.lt@ou.edu.vn
Submitted: 24-02-2021
Accepted: 05-03-2021
Published: 15-02-2022

Abstract
In the paper, a method of determining the structural damage using the Particle Swarm Optimization (PSO) algorithm is presented. PSO is a famous algorithm to search optimization. Damaged structural system members are detected by the PSO through the frequency change before and after the damage.

Keywords
damage detection, PSO algorithm, Structural Health Monitoring (SHM)

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Cite this paper as:

Le, T. C., & To, T. S. (2021). The Particle Swarm Optimization (PSO) algorithm in Structural Health Monitoring (SHM) application. Ho Chi Minh City Open University Journal of Science – Engineering and Technology, 11(1), 64-68. doi:10.46223/HCMCOUJS.tech.en.11.1.1446.2021


References

Capozucca, R. (2009). Static and dynamic response of damaged RC beams strengthened with NSM CFRP rods. Composite Structures, 91(3), 237-248. doi: 10.1016/j.compstruct.2009.05.003


Cha, Y. J., & Buyukozturk, O. (2015). Structural damage detection using modal strain energy and hybrid multiobjective optimization. Computer‐Aided Civil and Infrastructure Engineering, 30(5), 347-358. doi:10.1111/mice.12122


Colorni, A., Dorigo, M., & Maniezzo, V. (1992). An investigation of some properties of an “Ant algorithm”. In proceedings of the parallel problem solving from nature 2 (PPSN 92) (pp. 509-520). Brussels, Belgium: Elsevier Publishing.


Dorigo, M., Caro, G. D., & Gambardella, L. M. (1999). Ant algorithms for discrete optimization. Artificial Life, 5(2), 137-172. doi:10.1162/106454699568728


Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization: Technical report-tr06. Retrieved January 20, 2021, from https://www.researchgate.net/publication/255638348_An_Idea_Based_on_Honey_Bee_Swarm_for_Numerical_Optimization_Technical_Report_-_TR06


Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In Proceedings of ICNN’95 - International conference on neural networks (pp. 1942-1948). Perth, Australia: IEEE Publications.


Mirjalili, S. (2016). Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Computing and Applications, 27(4), 1053-1073. doi: 10.1007/s00521-015-1920-1


Yang, X.-S., & Deb, S. (2009). Cuckoo search via Lévy flights. In Proceedings 2009 World congress on nature & biologically inspired computing (NaBIC) (pp. 210-214). India: IEEE Publications.



DOI: https://doi.org/10.46223/HCMCOUJS.tech.en.11.1.1446.2021
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