Gas turbine engine condition monitoring using Gaussian mixture and hidden Markov models

Jacobs, W.R., Edwards, H., Li, P. et al. (2 more authors) (2018) Gas turbine engine condition monitoring using Gaussian mixture and hidden Markov models. International Journal of Prognostics and Health Management, 9. 26. ISSN 2153-2648

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 W. R. Jacobs et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License (https://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: Fault detection; condition monitoring; gas turbine engine; Gaussian Mixture Model; Hidden Markov Model
Dates:
  • Published (online): 16 August 2018
  • Published: 16 August 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Funding Information:
FunderGrant number
INNOVATE UK (TSB)TS/P00184X/1 70117-263238
Depositing User: Symplectic Sheffield
Date Deposited: 11 Sep 2018 10:11
Last Modified: 11 Sep 2018 10:12
Published Version: https://www.phmsociety.org/node/2455
Status: Published
Publisher: The Prognostics and Health Management Society
Refereed: Yes

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