%0 Journal Article
%T Structural damage detection using time domain responses and teaching–learning-based optimization (TLBO) algorithm
%J Scientia Iranica
%I Sharif University of Technology
%Z 1026-3098
%A Fallahian, S.
%A Joghataie, Abdolreza
%A Kazemi, Mohammad Taghi
%D 2018
%\ 12/01/2018
%V 25
%N 6
%P 3088-3100
%! Structural damage detection using time domain responses and teaching–learning-based optimization (TLBO) algorithm
%K structural damage detection
%K Time domain response
%K Measurement noise
%K Teaching–Learning-Based Optimization (TLBO) algorithm
%K analytical model
%R 10.24200/sci.2017.4238
%X Nowadays, structural health monitoring has attracted much attention, due to the construction of important and complex structures and their safety. One branch of structural health monitoring is damage detection, estimating the location and extent of eventual damages in the structural systems. In this study, an efficient method is introduced to determine the location and extent of damage in the frame, beam and truss structures using time domain response and an optimization algorithm. First of all, the structural damage detection problem is formulated as a standard optimization problem. So that, the optimization objective function is defined by using the acceleration of damaged structures and analytical model acceleration. The acceleration is obtained using Newmark method. Damage is simulated by reducing the elasticity modulus of structural members. Then, damage problem converted to an optimization problem are solved by teaching–learning-based optimization (TLBO) algorithm therefore, the exact location and extent of damage in structure can be determined. In order to show the capabilities of the proposed approach for identifying structural damage, four illustrative test examples are considered with considering measurement noise effect. The results clearly show that the proposed method is as a powerful method to detect multiple damage in structures.
%U http://scientiairanica.sharif.edu/article_4238_60951380e54c88f7bd7a9c862e95fc53.pdf