Yuan, Zhaoxu ORCID: 0000-0002-0400-3423, Liang, Peng, Silva, Tiago, Yu, Kaiping and Mottershead, JE ORCID: 0000-0003-1279-2562
(2019)
Parameter selection for model updating with global sensitivity analysis.
Mechanical Systems and Signal Processing, 115.
pp. 483-496.
Text
ZY_Parameter_selection_25May2018.pdf - Author Accepted Manuscript Download (2MB) |
Abstract
The problem of selecting parameters for stochastic model updating is one that has been studied for decades, yet no method exists that guarantees the ‘correct’ choice. In this paper, a method is formulated based on global sensitivity analysis using a new evaluation function and a composite sensitivity index that discriminates explicitly between sets of parameters with correctly-modelled and erroneous statistics. The method is applied successfully to simulated data for a pin-jointed truss structure model in two studies, for the cases of independent and correlated parameters respectively. Finally, experimental validation of the method is carried out on a frame structure with uncertainty in the position of two masses. The statistics of mass positions are confirmed by the proposed method to be correctly modelled using a Kriging surrogate.
Item Type: | Article |
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Uncontrolled Keywords: | model updating, parameter selection, uncertainty, global sensitivity |
Depositing User: | Symplectic Admin |
Date Deposited: | 08 Jun 2018 09:54 |
Last Modified: | 19 Jan 2023 01:32 |
DOI: | 10.1-16/j.ymssp.2018.05.048 |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3022330 |