The Inverse Method of Damage Detection using Swarm Life Cycle Algorithm (SLCA) via Modal Parameters in Beam Like Structures

ADMT Journal

دوره 14، شماره 2، شهریور 2021، صفحه 1-14   

نوع مقاله: Original Article

شناسه دیجیتال (DOI): 10.30495/admt.2021.1921979.1248

نویسندگان

Alireza Arghavan¹؛ Ali Ghoddosian^{* 2}؛ Ehsan Jamshidi³

¹Department of Mechanical Engineering, Semnan University, Semnan, Iran.

²Department of Mechanical Engineering, Semnan University, Semnan, Iran

³Energy and Sustainable Development Research Center, Semnan Branch, Islamic Azad University, Semnan, Iran.

چکیده

The Non-destructive vibration based structural damage detection techniques have been developed in the recent decades. They are usually converted into a mathematical optimization problem that should be solved using optimization algorithms. In this paper, a new hybrid algorithm, using a particle swarm - genetic optimization, is proposed that is called Swarm Life Cycle Algorithm (SLCA). Additionally, Modified Total Modal Assurance Criterion (MTMAC) that is modal based and involved natural frequencies and mode shapes, is used as an objective function. A cantilever beam is modelled and simulated using finite element method as a numerical case study with several different damage scenarios. To compare the effectiveness of the proposed algorithm with GA and PSO, they are applied to detect the locations and severities of damages of numerical cases separately. To assess the robustness of them, the effects of environmental noise, coordinate and mode incompleteness on the accuracy of damage detection have investigated. For experimental validation of the proposed method, empirical studies of single and double crack aluminium cantilever beams were conducted. The numerical and experimental results show that the proposed algorithm has great potential in crack identification. It is observed that SLCA is able to detect the location and extent of damage irrespective of the noise level and perform well in the presence of mode and coordinate incompleteness.

کلیدواژه‌ها

Damage Detection؛ Genetic Algorithm؛ Hybrid Algorithm؛ Modal Properties؛ Particle Swarm Optimization

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