Boaghe, O.M., Billings, S.A., Li, L.M. et al. (2 more authors) (2000) Time and Frequency Domain Identification and Analysis of a Gas Turbine Engine. Research Report. ACSE Research Report 778 . Department of Automatic Control and Systems Engineering
Abstract
The NARMAX (Nonlinear Auto Regressive Moving Average model with eXogenous inputs) approach has been used to analyse the dynamics of a gas turbine engine. The fuel flow-shaft speed relationship is analysed by identifying both time and frequency domain models of the system. The frequency domain analysis is studied by mapping the discrete-time NARMAX models into the Generalised Frequency Response Functions (GFRF's) to reveal the nonlinear coupling between the various input spectral components and the energy transfer mechanisms in the system. A continuous-time nonlinear differential equation model is also estimated using the Generalised Frequency Response Functions.
Metadata
Item Type: | Monograph |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) > ACSE Research Reports |
Depositing User: | MRS ALISON THERESA BARNETT |
Date Deposited: | 17 Mar 2015 11:09 |
Last Modified: | 24 Oct 2016 20:04 |
Status: | Published |
Publisher: | Department of Automatic Control and Systems Engineering |
Series Name: | ACSE Research Report 778 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:84270 |