Performance-based prognosis scheme for industrial gas turbines

TSOUTSANIS, Elias, MESKIN, Nader, BENAMMAR, Mohieddine and KHORASANI, K. (2015). Performance-based prognosis scheme for industrial gas turbines. In: RAMUHALLI, Pradeep and LOWE, Ryan, (eds.) Prognostics and Health Management (PHM), 2015 IEEE Conference on. Institute of Electrical and Electronics Engineers Inc..

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Official URL: http://ieeexplore.ieee.org/document/7245018/
Link to published version:: 10.1109/ICPHM.2015.7245018

Abstract

In this paper, we present a novel method for performance-based prognostics of industrial gas turbines. The concept of performance adaptation is implemented through a dynamic engine model that is developed in Matlab/Simulink environment to diagnose the health of the gas turbine. The proposed method is tested under variable operating conditions at both steady state and transient operational modes for estimating and predicting the compressor degradation. Different types of mathematical representations are used to fit the diagnosis results and consequently prognose the performance behavior of the engine. The results demonstrate the promising prospect of our proposed method for predicting accurately and efficiently the performance of gas turbine compressors as they degrade over time. © 2015 IEEE.

Item Type: Book Section
Additional Information: Paper originally presented at the IEEE Conference on Prognostics and Health Management, PHM 2015, 22 - 25 June 2015. Austin Texas. Conference Code:118047, cited by 2. INSPEC Accession Number: 15436982 IEEE PHM Conference
Uncontrolled Keywords: Compressibility of gases; Degradation; Engines; Gas compressors; Gases; Health; Mathematical models; Systems engineering; Turbines, Adaptation models; Industrial gas turbines; Mathematical representations; MATLAB/Simulink environment; Object oriented model; Prognostics and health managements; Steady state and transients; Variable operating condition, Gas turbines
Departments: Faculty of Science, Technology and Arts > Engineering and Mathematics
Identification Number: 10.1109/ICPHM.2015.7245018
Depositing User: Elias Tsoutsanis
Date Deposited: 17 Jan 2018 14:40
Last Modified: 17 Jan 2018 14:40
URI: http://shura.shu.ac.uk/id/eprint/16179

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