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Data Analytics for Performance Monitoring of Gas Turbine Engine

Yuan Liu, Avisekh Banerjee, Thambirajah Ravichandran, Amar Kumar, Glenn Heppler
2018 Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM  
Performance analysis of a low power rating and partially loaded industrial gas turbine engine (GTE) was carried out by using a model-free data analytic approach.  ...  Then novel methods are introduced for analysis of short-term and long-term performance deterioration arising from compressor fouling and structural degradation respectively.  ...  Step 5: Study the long-term performance deterioration In this step, the identification of the long-term performance deterioration is studied with the proposed performance indices.  ... 
doi:10.36001/phmconf.2018.v10i1.470 fatcat:aoqdzkmo7zfx5k2puxzacqvazu

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

Mohammadreza Tahan, Elias Tsoutsanis, Masdi Muhammad, Z.A. Abdul Karim
2017 Applied Energy  
the short and long term.  ...  the short and long term.  ... 
doi:10.1016/j.apenergy.2017.04.048 fatcat:rssxy6r5jvagphee6ykjwnxt4i

Discrimination of Rapid and Gradual Deterioration for an Enhanced Gas Turbine Life-cycle Monitoring and Diagnostics

Amare Fentaye, Valentina Zaccaria, Konstantinos Kyprianidis
2021 International Journal of Prognostics and Health Management  
The improvement achieved by the combined approach over the gas path analysis technique alone would strengthen the relevance and long-term impact of our proposed method in the gas turbine industry.  ...  Engine health deterioration can manifest itself in terms of rapid and gradual performance deviations.  ...  ACKNOWLEDGEMENT The authors graciously acknowledge the Knowledge Foundation (KKS) for supporting this research financially under the DIAGNOSIS and PROGNOSIS projects.  ... 
doi:10.36001/ijphm.2021.v12i3.2962 doaj:9b0cb44a597d404d8fe2d1d62aa7691e fatcat:hb5zdg4hrvaa5idla56lhnjmge

A data-driven approach for predicting long-term degradation of a fleet of micro gas turbines

Tomas Olsson, Enislay Ramentol, Moksadur Rahman, Mark Oostveen, Konstantinos Kyprianidis
2021 Energy and AI  
In an effort to enable fleet-level health monitoring of micro gas turbines, this work presents a novel data-driven approach for predicting system degradation over time.  ...  Methods for predictive health monitoring are typically developed for largescale gas turbines and have often focused on single systems.  ...  The research of Dr Enislay Ramentol has been funded by the European Research Consortium for Informatics and Mathematics (ERCIM) Alain Bensoussan Fellowship Programme and the Fraunhofer Institute for Industrial  ... 
doi:10.1016/j.egyai.2021.100064 fatcat:57477reyqbdhxf5jk2ym4xwzdm

Engine Condition Monitoring and Diagnostics [chapter]

Anastassios G.
2013 Progress in Gas Turbine Performance  
Stamatis Address all correspondence to tastamat@uth.gr Mechanical Engineering Department, Polytechnic School, University of Thessaly, Volos, Greece  ...  Journal of Engineering for Gas Turbines and Power. -. [ ] Ogaji SOT, Sampath S, Singh R, Probert SD. Parameter selection for diagnosing a gasturbine's performance-deterioration.  ...  Data management in order to keep historical data records for long term monitoring, without storing too much unnecessary information.  ... 
doi:10.5772/54409 fatcat:ufms6h3olzcupjjhmzmoodex2m

Model-Based Dynamic Performance Simulation of a Microturbine Using Flight Test Data

Mario Leonardo Erario, Maria Grazia De Giorgi, Radoslaw Przysowa
2022 Aerospace (Basel)  
This study aims at developing a numerical model of a micro gas turbine intended for prediction and prognostics of engine performance.  ...  The selected flight data were then used as input for the transient engine model.  ...  Model-based and data-driven fusion methods are essential for the core technology of digital twin model.  ... 
doi:10.3390/aerospace9020060 fatcat:7hpnapgjlbbshbc5bu55ki4ngm

Condition Assessment of Industrial Gas Turbine Compressor Using a Drift Soft Sensor Based in Autoencoder

Martí de Castro-Cros, Stefano Rosso, Edgar Bahilo, Manel Velasco, Cecilio Angulo
2021 Sensors  
These results lead to a qualitative indicator of the compressor behavior in long-term performance.  ...  The main objective of this study is to monitor and evaluate the condition of the compressor in a particular industrial gas turbine by developing a soft sensor following an autoencoder architecture.  ...  elaboration of the study.  ... 
doi:10.3390/s21082708 pmid:33921447 pmcid:PMC8069283 fatcat:4fylnysyifclngqgzk75pfbudy

Development of a real time intelligent health monitoring platform for aero-engine

Maria Grazia De Giorgi, Stefano Campilongo, Antonio Ficarella, K. Kontis, S. Pantelakis
2018 MATEC Web of Conferences  
In this paper an integrated heath monitoring platform is proposed and developed for performance analysis and degradation diagnostics of gas turbine engines.  ...  The training of the model is focused on components deterioration due to a combination of fouling and erosion.  ...  The long-term objective of the research will be a data-driven maintenance, which can be carried out with an innovative methodological analysis of the big data cluster from aero-engine system.  ... 
doi:10.1051/matecconf/201823300007 fatcat:rckdbf2prvc5fasxd34przauf4

Aircraft Engine Performance Monitoring and Diagnostics Based on Deep Convolutional Neural Networks

Amare Desalegn Fentaye, Valentina Zaccaria, Konstantinos Kyprianidis
2021 Machines  
This paper presents a gas turbine fault detection and isolation method using modular convolutional neural networks preceded by a physics-driven performance-trend-monitoring system.  ...  However, the application in the field of gas turbine diagnostics is still limited.  ...  Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/machines9120337 fatcat:qqfwklhnxbfk3e7hya6ztnnxve

Remaining Useful Life Prediction of an Aircraft Turbofan Engine Using Deep Layer Recurrent Neural Networks

Unnati Thakkar, Hicham Chaoui
2022 Actuators  
This research uses machine learning to provide a prediction framework for an aircraft's remaining useful life (RUL) based on the entire life cycle data and deterioration parameter data (ML).  ...  Engine components are susceptible to degradation over the life of their operation, which affects the reliability and performance of an engine.  ...  Long Short-Term Memory (LSTM) is one of the methods used to estimate the RUL of turbofan engines; it can figure out how long old data should be remembered, when it should be forgotten, and when new data  ... 
doi:10.3390/act11030067 doaj:95d9acda5442422aaa2ad8726f35034a fatcat:svcz636b3ngf7iwsrknz4ahbxy

Gas turbine gas path diagnostics: A review

Amare Desalegn Fentaye, Syed Ihtsham Ul-Haq Gilani, Aklilu Tesfamichael Baheta, S.A. Che Ghani, A. Alias, R. Mamat, Md. M. Rahman
2016 MATEC Web of Conferences  
Gas turbine diagnostics has been studied for the past six decades and several methods are introduced.  ...  This is possible if the gas turbine availability and reliability is improved using the appropriate maintenance action at the right time.  ...  The existing gas turbine gas path diagnosis approaches have two major categories, namely, model based and data driven.  ... 
doi:10.1051/matecconf/20167400005 fatcat:6nq4brwmynfbfaw76opus6prwq

Adaptive Degradation Prognostic Reasoning by Particle Filter with a Neural Network Degradation Model for Turbofan Jet Engine

Faisal Khan, Omer Eker, Atif Khan, Wasim Orfali
2018 Data  
The emphasis of this article is on an adaptive data-driven degradation model and how to improve the remaining useful life (RUL) prediction performance in condition monitoring of a Turbofan Jet Engine.  ...  This article presents an adaptive data-driven prognostics reasoning approach. An engineering case study of Turbofan Jet Engine has been used to demonstrate the prognostic reasoning approach.  ...  Conflicts of Interest: No conflicts of interest have been found for this research.  ... 
doi:10.3390/data3040049 fatcat:ifzkmyrk3zcklnor3xfv5jznq4

An Adaptive Model-Based Framework for Prognostics of Gas Path Faults in Aircraft Gas Turbine Engines

Ogechukwu Alozie, Yi-Guang Li, Xin Wu, Xingchao Shong, Wencheng Ren
2019 International Journal of Prognostics and Health Management  
This paper presents an adaptive framework for prognostics in civil aero gas turbine engines, which incorporates both performance and degradation models, to predict the remaining useful life of the engine  ...  Sparse information about the engine configuration is used to adapt a performance model, which serves as a baseline for implementing optimum sensor selection, operating data correction, fault isolation,  ...  Engine Modelling and Adaptation A gas path performance model can provide useful insight into the behavior of gas turbine components and its overall output in terms of efficiencies, thrust, fuel consumption  ... 
doi:10.36001/ijphm.2019.v10i2.2728 fatcat:fp7pb535ybcfjdms3zqylabsdu

A physics-based framework for online surface roughness assessment for high-pressure turbines

Jie Liu, Zelig Li, Houman Hanachi
2020 Chinese Journal of Aeronautics  
This paper proposes a physics-based online framework for Gas Turbine Engines (GTE), in order to assess the blade surface roughness in a highpressure turbine without engine shutdown.  ...  The framework consolidates Gas Path Analysis (GPA) based performance monitoring models and meanline turbomachinery analysis, using a novel GPAmeanline matching process.  ...  effective- 212 ness in capturing the short-term compressor fouling and long- 213 term turbine performance deterioration, respectively.  ... 
doi:10.1016/j.cja.2020.06.015 fatcat:tihp2oeztnaq5n7sxmf6cemjua

Predictive Maintenance Modelling for Through-Life Engineering Services

C. Okoh, R. Roy, J. Mehnen
2017 Procedia CIRP  
The proposed data-driven prognostics approach employs a statistical technique of (i) the parameter estimation methods of the time-tofailure data to predict the relevant statistical model parameters and  ...  The analysis of the modelling uses synthetic data validated by industry domain experts.  ...  The authors also acknowledge Rolls-Royce Plc for their support in this research.  ... 
doi:10.1016/j.procir.2016.09.033 fatcat:jw6n2h5ixveq3lz2xo2fw2bo3q
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