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Dynamic displacements‐based model updating with motion capture system
Author(s) -
Oh Byung Kwan,
Hwang Jin Woo,
Choi Se Woon,
Kim Yousok,
Cho Tongjun,
Park Hyo Seon
Publication year - 2017
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.1904
Subject(s) - sorting , weighting , modal , mode (computer interface) , genetic algorithm , algorithm , function (biology) , set (abstract data type) , computer science , vibration , engineering , machine learning , medicine , chemistry , radiology , programming language , operating system , physics , quantum mechanics , evolutionary biology , biology , polymer chemistry
Summary In this paper, a dynamic displacements‐based model updating method using a motion capture system (MCS) is proposed. The dynamic characteristics from MCS are used to find the parameters that minimize the difference between updated model and direct measurement. Using a multi‐objective optimization algorithm of non‐dominated sorting genetic algorithm‐II, the number of objective functions for model updating is set to the same number of modes under consideration, and all the objective function are simultaneously minimized. To consider the contribution of each mode on model updating and to avoid biased results, a rule for weighting of solutions associated to each mode based on modal participation factors is suggested and tested. Using a free vibration experimental test of a three‐story shear model, the performance of model updating method is verified by the comparison of the dynamics characteristics between the updated model and direct measurement by MCS. In addition, time histories of displacements from the updated model are compared with the direct measurement. Copyright © 2016 John Wiley & Sons, Ltd.