TY - JOUR ID - 21222 TI - Damage detection in a double-beam system using proper orthogonal decomposition and teaching-learning based algorithm JO - Scientia Iranica JA - SCI LA - en SN - 1026-3098 AU - Mirzabeigy, A. AU - Madoliat, R. AD - School of Mechanical Engineering, Iran University of Science and Technology, Narmak, Tehran, 16846, Iran. AD - School of Mechanical Engineering, Iran University of Science and Technology, Narmak, Tehran, 16846, Iran., Narmak, Tehran, 16846, Iran Y1 - 2020 PY - 2020 VL - 27 IS - 2 SP - 757 EP - 771 KW - Double-beam system KW - Proper orthogonal decomposition KW - crack KW - Damage KW - Teaching-Learning based optimization DO - 10.24200/sci.2019.50520.1738 N2 - This study deals with inverse approach for damage detection in a double-beam system. A double-beam system made of two parallel beams connected through an elastic layer. Degradation in stiffness of beams element, crack occurrence and partly destruction of inner layer has been considered as different types of damage. The time domain acceleration response of the system measured and proper orthogonal decomposition has been applied to the collected data in order to derive the proper orthogonal values (POV) and proper orthogonal modes (POM) of the system. Effect of single damage in different locations on the POV has been analyzed and an objective function has been defined using the dominant POV and POM of each beam separately. In order to increase robustness of the method against noise, the objective function enriched by adding statistical property of time domain response. The teaching-learning based optimization algorithm has been employed to solve optimization problem. Efficiency of the proposed method for detecting single and multiple damages in the system demonstrated with and without noise. Simulation results show good accuracy of the proposed method for detection single and multiple damages of different types in the system. UR - https://scientiairanica.sharif.edu/article_21222.html L1 - https://scientiairanica.sharif.edu/article_21222_e3de823e3f632afd7e8a94d7cb46607e.pdf ER -