Volume- 10
Issue- 4
Year- 2023
DOI: 10.55524/ijirem.2023.10.4.12 | DOI URL: https://doi.org/10.55524/ijirem.2023.10.4.12 Crossref
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
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Diwa James Enyia
Enhancing the performance of gas turbine requires the bringing together and optimization of the disciplines and expertise required to acquire an operationally competitive gas turbine engine. This study comprises comparative research between simulated and actual reliability of the gas path of a turbine engine. An innovative idea was introduced to reduce the gap between diagnostics processes via simulation and actual maintenance condition of the engine. The possible sources of errors were investigated by generating real error distribution. This research study explores the comparative investigation conducted to evaluate the reliability of a turbine gas path through simulating varying scenarios and analyzing real-life performance data. The application of simulation tools is to enable the replication of operating conditions and accurately model the gas turbine components, providing insights into potential weaknesses and strength. Real-life performance data provides important information about actual system behavior, including the frequency and nature of failures. Comparative investigations allow for validation of simulation accuracy, refinement of models, and identification of discrepancies. The findings from these investigations contribute to the optimization of gas turbine reliability, leading to efficient, cost-effective power generation systems.
[1] Saravanamuttoo, H.I.H., Roger, C.F.C., Cohen, H., Straznicky, P.V., (2009). “Gas Turbine Theory”, chapter 10, 6th Edition, pages 492-520.
[2] Walsh, P.P., Fletcher, P., (2008). “Gas Turbine Performance”. Chapter 5, 2nd Editioin, pages 149-247.
[3] Razak, A. M. Y., (2007). “Industrial Gas Turbines Performance and Operability”. Chapter 11, 1st Edition, pages 293-428.
[4] Rao, B.K.N. (1996). Handbook of Condition Monitoring, Elsevier Advanced Technology, Oxford
[5] Meher-Homji, C.B.; Chaker, M.A. & Motivwala, H.M. (2001). Gas turbine performance deterioration, Proceedings of Thirtieth Turbomachinery Symposium, pp.139-175, Texas, USA, September 17-20, 2001,Texas A&M University, Houston
[6] Tsalavoutas, A.; Stamatis, A.; Mathioudakis, K. et al. (2000). Identifying Faults in the Variable Geometry System of a Gas Turbine Compressor, ASME Paper No. 2000-GT-0033
[7] Ogaji, S.O.T.; Li, Y. G.; Sampath, S. et al. (2003). Gas path fault diagnosis of a turbofan engine from transient data using artificial neural networks, Proceedings of IGTI/ASME Turbo Expo 2003, 10p., Atlanta, Georgia, USA
[8] Sampath, S. & Singh, R. (2006). An integrated fault diagnostics model using genetic algorithm and neural networks, Journal of Engineering for Gas Turbines and Power, Vol. 128, No. 1, pp. 49-56?
[9] Butler, S.W; Pattipati, K.R.; Volponi, A. et al. (2006). An assessment methodology for data- driven and model based techniques for engine health monitoring, Proceedings of IGTI/ASME Turbo Expo 2006, 9p., Barcelona, Spain
[10] Romessis, C. & Mathioudakis, K. (2006). Bayesian network approach for gas path fault diagnosis, Journal of Engineering for Gas Turbines and Power, Vol. 128, No. 1, pp. 64-72.
[11] Bagherpour, H., Ouahrani, D., % Rech, J., (2017). “Reliability Assessment of Gas Turbines using Simulation Models: A Review. Energy, 128, 442-459.
[12] Cao, H., Tang, Y., Lang, y., & Huang, H. (2018). “Comparative Investigation of the Reliability of Turbine Blades using Simulation Models and Real Data”. Journal of Mechanical Science and Technology, 32(6), 2871-2881.
[13] Vo, T.H.D., Tran, M.T., & Le, H. P. (2019). “Comparative Investigation of Gas Turbine Reliability and fuel Consumption: Simulation versus Measurement Data”. Energies, 12(13), 2564.
[14] Zhang, Y., Wang, G., Fang, Y., Deng, Q., Wang, C., & Tan, J. (2021). “Comparative Analysis of Simulated and Real Reliability of a Gas Turbine Combustion Chamber”. Journal of engineering for Gas Turbines and Power, 143(5), 051006.
[15] Loboda, I. & Y epifanov , S. (2010). A Mixed Data-Driven and Model Based Fault Classification for Gas Turbine Diagnosis, Proceedings of ASME Turbo Expo 2010: International Technical Congress, 8p., Scotland, UK, June 14-18, Glasgow, ASME Paper No. GT2010-3075
Department of Mechanical Engineering, Cross River University of Technology, PMB 1123, Calabar, Nigeria
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