Performance-based prognosis scheme for industrial gas turbines

Elias Tsoutsanis; Nader Meskin; Mohieddine Benammar; K. Khorasani

doi:10.1109/ICPHM.2015.7245018

Performance-based prognosis scheme for industrial gas turbines

Elias Tsoutsanis, Nader Meskin, Mohieddine Benammar, K. Khorasani

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

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.

Original language	English
Title of host publication	2015 IEEE Conference on Prognostics and Health Management
Subtitle of host publication	Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHAf Technology and Application, PHM 2015
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)	9781479918935
DOIs	https://doi.org/10.1109/ICPHM.2015.7245018
Publication status	Published - 8 Sept 2015
Event	IEEE Conference on Prognostics and Health Management, PHM 2015 - Austin, United States Duration: 22 Jun 2015 → 25 Jun 2015

Conference

Conference	IEEE Conference on Prognostics and Health Management, PHM 2015
Country/Territory	United States
City	Austin
Period	22/06/15 → 25/06/15

Keywords

Adaptation models
Degradation
Engines
Mathematical model
Object oriented modeling
Prognostics and health management
Turbines

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Software
Engineering (miscellaneous)

Access to Document

10.1109/ICPHM.2015.7245018Licence: None: All rights reserved

https://ieeexplore.ieee.org/document/7245018Licence: None: All rights reserved

Cite this

Tsoutsanis, E., Meskin, N., Benammar, M., & Khorasani, K. (2015). Performance-based prognosis scheme for industrial gas turbines. In 2015 IEEE Conference on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHAf Technology and Application, PHM 2015 Article 7245018 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICPHM.2015.7245018

Tsoutsanis, Elias ; Meskin, Nader ; Benammar, Mohieddine et al. / Performance-based prognosis scheme for industrial gas turbines. 2015 IEEE Conference on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHAf Technology and Application, PHM 2015. Institute of Electrical and Electronics Engineers (IEEE), 2015.

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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.",

keywords = "Adaptation models, Degradation, Engines, Mathematical model, Object oriented modeling, Prognostics and health management, Turbines",

author = "Elias Tsoutsanis and Nader Meskin and Mohieddine Benammar and K. Khorasani",

year = "2015",

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doi = "10.1109/ICPHM.2015.7245018",

language = "English",

booktitle = "2015 IEEE Conference on Prognostics and Health Management",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

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Tsoutsanis, E, Meskin, N, Benammar, M & Khorasani, K 2015, Performance-based prognosis scheme for industrial gas turbines. in 2015 IEEE Conference on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHAf Technology and Application, PHM 2015., 7245018, Institute of Electrical and Electronics Engineers (IEEE), IEEE Conference on Prognostics and Health Management, PHM 2015, Austin, United States, 22/06/15. https://doi.org/10.1109/ICPHM.2015.7245018

Performance-based prognosis scheme for industrial gas turbines. / Tsoutsanis, Elias; Meskin, Nader; Benammar, Mohieddine et al.
2015 IEEE Conference on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHAf Technology and Application, PHM 2015. Institute of Electrical and Electronics Engineers (IEEE), 2015. 7245018.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Meskin, Nader

AU - Benammar, Mohieddine

AU - Khorasani, K.

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N2 - 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.

AB - 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.

KW - Adaptation models

KW - Degradation

KW - Engines

KW - Mathematical model

KW - Object oriented modeling

KW - Prognostics and health management

KW - Turbines

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M3 - Conference contribution

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BT - 2015 IEEE Conference on Prognostics and Health Management

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - IEEE Conference on Prognostics and Health Management, PHM 2015

Y2 - 22 June 2015 through 25 June 2015

ER -

Tsoutsanis E, Meskin N, Benammar M, Khorasani K. Performance-based prognosis scheme for industrial gas turbines. In 2015 IEEE Conference on Prognostics and Health Management: Enhancing Safety, Efficiency, Availability, and Effectiveness of Systems Through PHAf Technology and Application, PHM 2015. Institute of Electrical and Electronics Engineers (IEEE). 2015. 7245018 doi: 10.1109/ICPHM.2015.7245018

Performance-based prognosis scheme for industrial gas turbines

Abstract

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Keywords

ASJC Scopus subject areas

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