A Bayesian non-parametric clustering approach for semi-supervised Structural Health Monitoring

Rogers, T.J., Worden, K., Fuentes, R. et al. (3 more authors) (2018) A Bayesian non-parametric clustering approach for semi-supervised Structural Health Monitoring. Mechanical Systems and Signal Processing, 119. pp. 100-119. ISSN 0888-3270

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Structural health monitoring; Damage detection; Bayesian methods; Clustering; Semi-supervised learning
Dates:
  • Published (online): 24 September 2018
  • Accepted: 5 September 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Funding Information:
FunderGrant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/J016942/1
Depositing User: Symplectic Sheffield
Date Deposited: 08 Oct 2018 14:02
Last Modified: 08 Oct 2018 14:02
Published Version: https://doi.org/10.1016/j.ymssp.2018.09.013
Status: Published
Publisher: Elsevier
Refereed: Yes
Identification Number: https://doi.org/10.1016/j.ymssp.2018.09.013

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