Distributed digital twins for health monitoring: resource constrained aero-engine fleet management

Hartwell, A., Montana, F. orcid.org/0000-0003-0938-6838, Jacobs, W. orcid.org/0000-0001-8163-0685 et al. (3 more authors) (2024) Distributed digital twins for health monitoring: resource constrained aero-engine fleet management. The Aeronautical Journal, 128 (1325). pp. 1556-1575. ISSN 0001-9240

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Item Type: Article
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© The Author(s), 2024. PublishedbyCambridgeUniversityPressonbehalfofRoyalAeronauticalSociety. ThisisanOpenAccessarticle, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use and/or adaptation of the article.

Keywords: digital twin; health monitoring; machine learning; fault diagnosis
Dates:
  • Published: July 2024
  • Published (online): 15 April 2024
  • Accepted: 17 February 2024
  • Submitted: 27 October 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
Funding Information:
Funder
Grant number
ROLLS-ROYCE POWER ENGINEERING PLC
1500-00420117
Depositing User: Symplectic Sheffield
Date Deposited: 31 Jan 2025 11:32
Last Modified: 31 Jan 2025 11:32
Status: Published
Publisher: Cambridge University Press (CUP)
Refereed: Yes
Identification Number: 10.1017/aer.2024.23
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