Parameter selection for model updating based on the global sensitivity method

Yuan, Zhaoxu, Yu, Kaiping and Mottershead, John E ORCID: 0000-0003-1279-2562 (2018) Parameter selection for model updating based on the global sensitivity method. .

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Abstract

A new model-updating parameter selection method based on global sensitivity analysis is presented in this work. A specifically designed evaluation function is used for the probability that the sample fits the distribution of test data. In contrast to other parameter selection methods the test-data information is introduced to the parameter selection procedure. Global sensitivity analysis is performed and a set of composite indices for parameter selection is calculated. The parameters are selected based on the values of these composite indices. The method is validated using simulation data from a pin-jointed truss structure model. The cases of independent and correlated parameters are studied and the presented method is shown to be effective for both.

Item Type:	Conference or Workshop Item (Unspecified)
Depositing User:	Symplectic Admin
Date Deposited:	05 Feb 2019 16:03
Last Modified:	19 Jan 2023 01:05
DOI:	10.1088/1742-6596/1106/1/012004
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3032291