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Stochastic model updating - covariance matrix adjustment from uncertain experimental modal data

Govers, Yves and Link, Michael (2009) Stochastic model updating - covariance matrix adjustment from uncertain experimental modal data. Mechanical Systems and Signal Processing (MSSP). Elsevier. DOI: 10.1016/j-ymssp.2009.10.006 ISSN 0888-3270

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Official URL: http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6WN1-4XJP3XR-1&_user=100058&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_acct=C000007338&_version=1&_urlVersion=0&_userid=100058&md5=81e5dc52b0bedd899232072cf6b5ae78


With deterministic methods finite element model parameters are updated by using a single set of experimental data. As a consequence the corrected analytical model only reflects this single test case. However, test data are inherently exposed to uncertainty due to measurement errors, different modal extraction techniques etc. Even a more relevant factor for variability originates from production tolerances and consequently the question arises, how to describe model parameters from the stochastic point of view? Therefore it would be desirable to use statistical properties of multiple sets of experimental and to consider the update parameters as random variables. This paper presents an inverse approach how to identify a stochastic finite element model from uncertain test data. In detail, this work demonstrates a method to adjust design parameter means and their related covariance matrix from multiple sets of experimental modal data. Results are shown from a numerical example.

Item URL in elib:https://elib.dlr.de/60534/
Document Type:Article
Title:Stochastic model updating - covariance matrix adjustment from uncertain experimental modal data
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Govers, YvesInstitute of AeroelasticityUNSPECIFIED
Link, MichaelUniversity of Kassel, Institute for Statics and DynamicsUNSPECIFIED
Journal or Publication Title:Mechanical Systems and Signal Processing (MSSP)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1016/j-ymssp.2009.10.006
Series Name:ScienceDirect
Keywords:stochastic model updating, uncertainty, inverse problems
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Aircraft Research (old)
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Flexible Aircraft (old)
Location: Göttingen
Institutes and Institutions:Institute of Aeroelasticity
Deposited By: Erdmann, Daniela
Deposited On:10 Dec 2009 11:45
Last Modified:06 Sep 2019 15:28

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