@article { author = {Kaveh, A. and Hosseini, S.M. and Barzinpour, F.}, title = {Damage Identification And Quantification Of Structures By Vibration-Based Model Updating Method Using Teaching-Learning-Based Optimization}, journal = {Sharif Journal of Civil Engineering}, volume = {37.2}, number = {1.1}, pages = {71-84}, year = {2021}, publisher = {Sharif University of Technology}, issn = {2676-4768}, eissn = {2676-4776}, doi = {10.24200/j30.2020.55365.2732}, abstract = {Engineering structures are prone to damage over their service life as a result of natural disaster so that damage spreading may lead to many casualties. In order to prevent these catastrophic events, early damage detection must be carried out. By considering these issues, numerous structural damage detection methods have been proposed by many researchers in the last few decades. Among all sorts of methods developed for damage detection in structures, vibration-based methods due to their simplicity and applicability are highly favored by many researchers. The basic conceptual of the vibration-based methods is that modal parameters (natural frequencies and their associated mode shapes) are functions of the physical properties of the structure (mass, damping, and stiffness). Therefore, changes in the physical properties will cause changes in the modal properties. A class of vibration-based methods is identified and damages are quantified using the model updating approach. In these methods, an objective function defined in terms of the discrepancies between the analytical model and real structural system is minimized as an optimization problem. In this paper, a novel model updating method is presented based on a structure’s main modal parameters (natural frequencies and their corresponding modal shapes). For this purpose, a hybrid vibration-based objective function is proposed to minimize the differences between the structure’s properties and the analytical model. A penalty function is integrated into the objective function to reduce the effects of noise in damage detection and uncertainties in the assessment procedure. The Teaching-Learning-Based Optimization (TLBO) algorithm is applied to solve this problem as an optimization problem. This algorithm is inspired by the traditional learning process of students in school. The two main stages of this algorithm are the effect of the teacher’s knowledge on student learning by the convergence strategy and students learning from each other by the divergence strategy. To evaluate the applicability of the proposed objective function in detecting the location and intensity of the damage, three numerical cases are considered. These cases include an 8-story shear frame, a continuous beam, and a spatial truss. Different challenges such as the effect of noise on measured data and the effect of the penalty-function on results of damage detection were considered. Furthermore, a comparative study is investigated between the proposed objective function and three other objective functions developed based the main model parameters. The results demonstrated that the proposed method is a reliable and stable technique in damage prognosis in structures.}, keywords = {Damage detection,model updating method,modal parameters,objective function,Teaching–learning-based optimization}, title_fa = {شناسایی و تعیین مقدار آسیب سازه ها با روش به روزرسانی مدل ارتعاش-محور و بکارگیری الگوریتم بهینه سازی مبتنی بر آموزش و یاد گیری}, abstract_fa = {در مطالعه‌ی حاضر، یک روش جدید به‌روزرسانی مدل بر مبنای پارامترهای مودال اصلی سازه (بسامدهای طبیعی و شکل‌های مودی متناظر) ارائه شده است. بدین منظور، یک تابع ترکیبی ارتعاش ـ محور با هدف کمینه‌سازی اختلاف بین مشخصات سازه‌ی اندازه‌گیری شده و مدل تحلیلی تعریف شده است. به‌منظور کاهش آثار نوفه، یک تابع جریمه بر تابع هدف اعمال شده است. برای حل مسئله‌ی شناسایی آسیب از الگوریتم بهینه‌یاب مبتنی بر آموزش و یادگیری استفاده شده است. جهت ارزیابی تابع هدف، سه مثال عددی بررسی شده است. چالش‌هایی نظیر اثر نوفه و تابع جریمه در نتایج شناسایی آسیب مطالعه شده است. همچنین مطالعه‌یی برای مقایسه‌ی تابع هدف پیشنهادی با سه تابع هدف دیگر مبتنی بر اطلاعات مودال انجام شده است. نتایج نشان می‌دهند که روش پیشنهادی با اعمال تابع جریمه و به کار بردن الگوریتم بهینه‌سازی مبتنی بر آموزش و یادگیری می‌تواند یک روش قابل اطمینان و پایدار در شناسایی آسیب سازه‌ها محسوب شود.}, keywords_fa = {شناسایی آسیب,روش به‌روزرسانی مدل,پارامترهای مودال,تابع هدف,الگوریتم بهینه‌سازی مبتنی بر آموزش و یادگیری}, url = {https://sjce.journals.sharif.edu/article_21960.html}, eprint = {https://sjce.journals.sharif.edu/article_21960_470b4ea9a5fb286c63780a39d7a352ce.pdf} }