Interval model updating with irreducible uncertainty using the Kriging predictor

Journal article 1193 views

Hamed Haddad Khodaparast, John E Mottershead, Kenneth J Badcock, Hamed Haddad Khodaparast

Mechanical Systems and Signal Processing, Volume: 25, Issue: 4, Pages: 1204 - 1226

Swansea University Author: Hamed Haddad Khodaparast

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DOI (Published version): 10.1016/j.ymssp.2010.10.009

Published in:	Mechanical Systems and Signal Processing
ISSN:	0888-3270
Published:	2011
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa15775
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Item Description:	Stochastic model updating methods have emerged recently which take into account aleatoric (irreducible) uncertainties. However, the majority of the methods use probabilistic models. Funded by the European Union's 6th Framework Project, this paper proposed the use of possibilistic models (e.g. interval model) and developed an interval model updating technique. The results are validated experimentally. The method requires less measurement data for system identification, which led to significant saving in cost without sacrificing accuracy. This research has led to collaboration with DLR (German Aerospace Centre, http://www.dlr.de ).
College:	Faculty of Science and Engineering
Issue:	4
Start Page:	1204
End Page:	1226