The University of Southampton
University of Southampton Institutional Repository

Bayesian damage localisation at higher frequencies with Gaussian process error

Lecomte, Christophe, Forster, J.J., Mace, B.R. and Ferguson, N.S. (2012) Bayesian damage localisation at higher frequencies with Gaussian process error In, Simmermacher, T., Cogan, S., Horta, L.G. and Barthorpe, R. (eds.) Topics in Model Validation and Uncertainty Quantification, Volume 4. Springer New York pp. 39-48. (Conference Proceedings of the Society for Experimental Mechanics Series, 29). (doi:10.1007/978-1-4614-2431-4_4).

Record type: Book Section


This paper concerns the estimation of the location (and properties) of damage in structures using Bayesian methods and Markov Chain Monte Carlo (MCMC). It is widely recognised that the consideration of uncertainty in structural dynamic systems may be essential, for example from an economic point of view ("Does it make sense to add expensive damping if it will only affect a small proportion of the vehicles we produce?") or for critical safety purposes ("What is the risk of failure of an airplane engine due to bladed disk mistuning?"). The use of Bayesian methods appears to be a viable approach to obtain inferences about the parameters of such uncertain systems. Here we report on numerical experiments on the use of MCMC to locate a frequency dependent damage in a one-dimensional structure. Transfer function measurements subject to a Gaussian process measurement error are available. The particular structure of the resulting system matrices is then seen to have a special form which results in a semi-analytic solution method being available and a much reduced computational cost. We discuss the characteristics and efficiency of the Bayesian model and MCMC computation and highlight features in the analysis of structural dynamic systems such as higher-frequency multimodality.

Full text not available from this repository.

More information

Published date: 2012
Organisations: Computational Engineering & Design Group


Local EPrints ID: 342589
ISBN: 9781461424307
PURE UUID: 3bed0ec2-abcb-4df2-b6ed-c343f659c825
ORCID for N.S. Ferguson: ORCID iD

Catalogue record

Date deposited: 11 Sep 2012 12:02
Last modified: 18 Jul 2017 05:28

Export record



Author: Christophe Lecomte
Author: J.J. Forster
Author: B.R. Mace
Author: N.S. Ferguson ORCID iD
Editor: T. Simmermacher
Editor: S. Cogan
Editor: L.G. Horta
Editor: R. Barthorpe

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.