Volume 14, Issue 1 (1-2024)                   IJOCE 2024, 14(1): 95-113 | Back to browse issues page


XML Print


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

Talebpour M, Razavizade Mashizi S, Goudarzi A. SENSITIVITY ANALYSIS FOR STRUCTURAL DAMAGE DETECTION THROUGH STRAIN ENERGY. IJOCE 2024; 14 (1) :95-113
URL: http://ijoce.iust.ac.ir/article-1-577-en.html
1- School of Engineering, Damghan University, Damghan, Iran
2- Department of Civil Engineering, Technical and Vocational University (TVU), Tehran, Iran
3- Department of Civil Engineering, Shahrood non-profit and non-government higher Education Institute, Shahrood, Iran
Abstract:   (5731 Views)
This paper proposes a method for structural damage detection through the sensitivity analysis of modal shapes in the calculation of modal strain energy (MSE). For this purpose, sensitivity equations were solved to determine the strain energy based on dynamic data (i.e., modal shapes). An objective function was then presented through the sensitivity-based MSE to detect structural damage. Due to the nonlinearity of sensitivity equations, the objective function of the proposed formulation can be minimized through the shuffled shepherd optimization algorithm (SSOA). The first few modes were employed for damage detection in solving the inverse problem. The proposed formulation was evaluated in a few numerical examples under different conditions. The numerical results indicated that the proposed formulation was efficient and effective in solving the inverse problem of damage detection. The proposed method not only minimized sensitivity to measurement errors but also effectively identified the location and severity of structural damage.
 
Full-Text [PDF 1235 kb]   (1669 Downloads)    
Type of Study: Research | Subject: Optimal analysis
Received: 2024/02/8 | Accepted: 2024/01/1 | Published: 2024/01/1

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