Identification of time-varying parameters using variational Bayes-sequential ensemble Monte Carlo sampler

Lye, Adolphus and Gray, Ander and Patelli, Edoardo; Castanier, Bruno and Cepin, Marko and Bigaud, David and Berenguer, Christophe, eds. (2021) Identification of time-varying parameters using variational Bayes-sequential ensemble Monte Carlo sampler. In: Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021. Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021 . Research Publishing, Singapore, FRA, pp. 443-450. ISBN 9789811820168 (https://doi.org/10.3850/978-981-18-2016-8_081-cd)

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Abstract

This work presents an extended sequential Monte Carlo sampling algorithm embedded with a Variational Bayes step. The algorithm is applied to estimate the distribution of time-varying parameters in a Bayesian filtering procedure. This algorithm seeks to address the case whereby the state-evolution model does not have an inverse function. In the proposed approach, a Gaussian mixture model is adopted whose covariance matrix is determined via principle component analysis. As a form of verification, a numerical example involving the identification of inter-storey stiffness within a 2-DOF shear building model is presented whereby the stiffness parameters degrade according to a simple State-evolution model whose inverse function can be derived. The Variational Bayes-sequential ensemble Monte Carlo sampler is implemented alongside the Sequential Monte Carlo sampler and the results compared on the basis of the accuracy and precision of the estimates as well computational time. A non-linear time-series model whose state-evolution model does not yield an inverse function is also analysed to show the applicability of the proposed approach.

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• Item metadata

  Item type:	Book Section
  ID code:	84631
  Dates:	Date Event 19 September 2021 Published 1 August 2021 Accepted
  Notes:	Funding Information: The authors would like to express their gratitude to the Singapore Nuclear Research and Safety Initiatives (SNRSI), EPSRC iCase studentship award 15220067, and Euratom research grant under agreement No. 633053, for their continued support in making this research possible. Publisher Copyright: © ESREL 2021. Published by Research Publishing, Singapore.
  Subjects:	Technology > Engineering (General). Civil engineering (General) Science > Mathematics
  Department:	Faculty of Engineering > Civil and Environmental Engineering
  Depositing user:	Pure Administrator
  Date deposited:	09 Mar 2023 15:48
  Last modified:	26 Apr 2024 00:10
  Related URLs:	Scopus publication
  URI:	https://strathprints.strath.ac.uk/id/eprint/84631