Structural Damage Assessment via Model Updating Using Augmented Grey Wolf Optimization Algorithm
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
View: 337
This Paper With 10 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_IJE-33-7_002
تاریخ نمایه سازی: 4 شهریور 1399
Abstract:
Some civil engineering-based infrastructures are planned for the structural health monitoring (SHM) system based on their importance. Identifiction and detecting damage automatically at the right time are one of the major objectives this system faces. One of the methods to meet this objective is model updating whit use of optimization algorithms in structures.This paper is aimed to evaluate the location and severity of the damage combining two being-updated parameters of the flexibility matrix and the static strain energy of the structure using augmented grey wolf optimization (AGWO) and only with extracting the data of damaged structure, by applying 5 percent noise. The error between simulated and estimated results in average of ten runs and each damage scenario was less than 3 percent which proves the proper performance of this method in detection of the all damages of the 37-member three-dimensional frame and the 33-member two-dimensional truss. Moreover, they indicate that AGWO can provide a reliable tool to accurately identify the damage in compare with the particle swarm optimizer (PSO) and grey wolf optimizer (GWO).
Keywords:
augmented grey wolf optimization algorithm , Damage detection , flexibility matrix , Modal data , static strain energy
Authors
S. Ghasemi
Civil Engineering Department, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
G. Ghodrati Amiri
Centre of Excellence for Fundamental Studies in Structural Engineering, School of Civil Engineering, Iran University of Science & Technology, Tehran, Iran
M. Mohamadi Dehcheshmeh
Civil Engineering Department, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :