Physics-informed machine learning for structural health monitoring

Cross, E.J., Gibson, S.J., Jones, M.R. et al. (3 more authors) (2022) Physics-informed machine learning for structural health monitoring. In: Cury, A., Ribeiro, D., Ubertini, F. and Todd, M.D., (eds.) Structural Health Monitoring Based on Data Science Techniques. Structural Integrity (21). Springer Cham , pp. 347-367. ISBN 9783030817152

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2022 The Author(s). This is an author-produced version of a chapter subsequently published in Structural Health Monitoring Based on Data Science Techniques. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Physics-informed machine learning; Grey-box modelling; Gaussian process regression
Dates:
  • Published (online): 24 October 2021
  • Published: 2022
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 Sciences Research CouncilEP/S001565/1
Depositing User: Symplectic Sheffield
Date Deposited: 23 Jun 2022 06:06
Last Modified: 24 Oct 2022 00:14
Status: Published
Publisher: Springer Cham
Series Name: Structural Integrity
Refereed: Yes
Identification Number: https://doi.org/10.1007/978-3-030-81716-9_17

Export

Statistics