Volume 18, Issue 3 (2018)                   MME 2018, 18(3): 237-246 | Back to browse issues page

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alina M M, sepehr mousavi S V, amanabadi J. Damage detection process comparison using various optimization algorithms in 3D plane elements based on dynamics properties of structure. MME. 2018; 18 (3) :237-246
URL: http://journals.modares.ac.ir/article-15-8003-en.html
1- Professor, Department of civil engineering, Amirkabir University of Technology
2- amirkabir university of technology
Abstract:   (539 Views)
Damage occurrence in structural and mechanical systems during utilization is an inevitable phenomenon. Death and financial losses could be prevented by health monitoring systems and damage detection processes in structures. In the mentioned framework, damage detection based on dynamics properties, is one of the most important and efficient methods, without concentration on special zones in structure. In this study frequency response functions were analyzed by principle component analysis, then, in order to complete process, dimension reduction and damage indices extraction were conducted. At the end, plate damage detection was introduced as an optimization problem considering extracted damage indices, and solution of the problem were given by PSO and Genetic algorithms. Output results consist of estimation about location and intensity of applied damage. Several scenarios including single, simultaneously dual and triple stiffness losses were figured out to investigate and evaluate the efficiency of the mentioned algorithms. Finally, outcome result around performance and utility of method had been discussed. It's obviously demonstrated that Particle Swarm Optimization algorithm has more accurate result, especially in estimation of damage location than Genetic algorithm optimization solution, during health monitoring processes. The mentioned conclusion has been gotten more explicit with getting scenario complicated.
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Article Type: Research Article | Subject: Vibration
Received: 2017/11/12 | Accepted: 2018/02/10 | Published: 2019/03/1

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