Volume 14, Issue 3 (6-2024)                   IJOCE 2024, 14(3): 337-354 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Mahdavi V, Kaveh A. STRUCTURAL DAMAGE IDENTIFICATION BASED ON CHANGES IN NATURAL FREQUENCIES USING THREE MULTI-OBJECTIVE METAHEURISTIC ALGORITHMS. IJOCE 2024; 14 (3) :337-354
URL: http://ijoce.iust.ac.ir/article-1-598-en.html
1- Department of Civil and Geomechanics Engineering, Arak University of Technology, Arak, Iran
2- School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran-16, Iran
Abstract:   (1804 Views)
In order to evaluate the damage state, value, and position of structural members more accurately, a multi-objective optimization (MO) method is utilized that is based on changes in natural frequency. The multi-objective optimization dynamic-based damage detection method is first introduced. Two objective functions for optimization are then introduced in terms of changing the natural frequencies and mode shapes. The multi-objective optimization problem (MOP) is formulated by using the two objective functions. Three considered MO algorithms consist of Colliding Bodies Optimization (MOCBO), Particle Swarm Optimization (MOPSO), and non-dominated sorting genetic algorithm (NSGA-II) to achieve the best structural damage detection. The proposed methods are then applied to three planar steel frame structures. Compared to the traditional optimization methods utilizing the single-objective optimization (SO) algorithms, the presented methods provide superior results.
Full-Text [PDF 452 kb]   (269 Downloads)    
Type of Study: Research | Subject: Applications
Received: 2024/04/2 | Accepted: 2024/05/29 | Published: 2024/09/9

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb