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Faults detection in gas turbine rotor using vibration analysis under varying conditions

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Monitoring of rotating machines is a very important task in most industrial sectors, which requires a chosen number of performance indicators during the exploitation of such kind of equipments. Indeed, for understanding the undesirable phenomena complexity of the industrial systems under operation, a reliable and an accurate mathematical modeling is required to ensure the diagnosis and the control of these phenomena. This work proposes development of a fault monitoring system of a gas turbine type GE MS 3002 based on vibration analysis technique using spectral analysis tools. The obtained results prove the effectiveness of the presented monitoring tool approach which is applied on the gas turbine, for avoiding the operation under vibration mode and for generating optimal performance during the exploitation of the gas turbine.
Rocznik
Strony
393--406
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa, Algeria
autor
  • Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa, Algeria
autor
  • Applied Automation and Industrial Diagnostics Laboratory, Faculty of Science and Technology, University of Djelfa, Algeria
Bibliografia
  • 1. Ali U., Font Palma C., Hughes K.J., Ingham D.B., Ma L., Pourkashanian M., 2015, Impact of the operating conditions and position of exhaust gas recirculation on the performance of a micro gas turbine, Computer Aided Chemical Engineering, 37, 2417-2422
  • 2. Ashour O., Khalidi A., Fadlun E., Giannini N., Pieri M., Ceccherini A., 2012, On-line monitoring of gas turbines to improve their availability, reliability, and performance using both process and vibration data, Proceeding of the 3rd Gas Processing Symposium, 334-343
  • 3. Djaidir B., Hafaifa A., Kouzou A., 2015, Monitoring gas turbines using speedtronic Mark VI Control Systems, Pipeline and Gas Journal, 242, 10, 48-86
  • 4. Djaidir B., Hafaifa A., Kouzou A., 2016, Vibration detection in gas turbine rotor using artifi- cial neural network, International Conference on Acoustics and Vibration ATAVI’16, March 21-23, 2016, Hammamet-Tunisia
  • 5. Djeddi A.Z., Hafaifa A., Kouzou A., Abudura S., 2016, Exploration of reliability algorithms using modified Weibull distribution: Application on gas turbine, International Journal of System Assurance Engineering and Management, DOI 10.1007/s13198-016-0480-9, First online: 12 May 2016, 1-10
  • 6. Djeddi A.Z., Hafaifa A., Salam A., 2015, Gas turbine reliability model based on tangent hyperbolic reliability function, Journal of Theoretical and Applied Mechanics, 53, 3, 723-730
  • 7. Eshati S., Abu A., Laskaridis P., Khan F., 2013, Influence of water-air ratio on the heat transfer and creep life of a high pressure gas turbine blade, Applied Thermal Engineering, 60, 1-2, 335-347
  • 8. Ford C.L., Carrotte J.F., Walker A.D., 2013, The application of porous media to simulate the upstream effects of gas turbine injector swirl vanes, Computers and Fluids, 77, 143-151
  • 9. Galindo J., Fajardo P., Navarro R., Garca-Cuevas L.M., 2013, Characterization of a radial turbocharger turbine in pulsating flow by means of CFD and its application to engine modeling, Applied Energy, 103, 116-127
  • 10. Guasch A., Quevedo J., Milne R., 2000, Fault diagnosis for gas turbines based on the control system, Engineering Applications of Artificial Intelligence, 13, 4, 477-484
  • 11. Guemana M., Hafaifa A., Rahmoune M.B., 2015, Reliability study of gas turbines for improving their availability by ensuring optimal exploitation, OIL GAS European Magazine, 2, 88-91
  • 12. Gunyaz A. ¨ , 2013, A modeling and control approach to advanced nuclear power plants with gas turbines, Energy Conversion and Management, 76, 899-909
  • 13. Hadroug N., Hafaifa A., Kouzou A., Chaibet A,, 2016, Faults detection in gas turbine using hybrid adaptive network based fuzzy inference systems to controlling there dynamic behavior, Diagnostyka – The Journal of Polish Society of Technical Diagnostics (PSTD), 17, 4, 3-17
  • 14. Jagaduri R.T., Radman G., 2007, Modeling and control of distributed generation systems including PEM fuel cell and gas turbine, Electric Power Systems Research, 77, 1, 83-92
  • 15. Jurado F., Carpio J., 2006, Improving distribution system stability by predictive control of gas turbines, Energy Conversion and Management, 47, 18/19, 2961-2973
  • 16. Kim K.H., Ko H.-J., Perez-Blanco H., 2011, Analytical modeling of wet compression of gas turbine systems, Applied Thermal Engineering, 31, 5, 834-840
  • 17. Krzyzynski T., Popp K., Sextro W., 2000, On some irregularities in dynamic response of cyclic periodic structures, Chaos, Solitons and Fractals, 11, 1597-1609
  • 18. Lee M.C., Chung J.H., Park W.S., Park S., Yonn Y., 2013, The combustion tuning methodology of an industrial gas turbine using a sensitivity analysis, Applied Thermal Engineering, 50, 1, 714-721
  • 19. Liu X., Lu C., Liang S., Godbole A., Chen Y., 2015, Influence of the vibration of large-scale wind turbine blade on the aerodynamic load, Energy Procedia, 75, 873-879
  • 20. Madhavan S., Rajeev J., Sujatha C., Sekha A.S., 2014, Vibration based damage detection of rotor blades in a gas turbine engine, Engineering Failure Analysis, 46, 26-39
  • 21. Nikpey H., Assadi M., Breuhaus P., Mørkved P.T., 2014, Experimental evaluation and ANN modeling of a recuperative micro gas turbine burning mixtures of natural gas and biogas, Applied Energy, 117, 30-41
  • 22. Rahmoune M.B., Hafaifa A., Guemana M., 2015, Neural network monitoring system used for the frequency vibration prediction in gas turbine, The 3rd International Conference on Control, Engineering and Information Technology CEIT’2015, 25-27 May 2015 Tlemcen, Algeria
  • 23. Sanaye S., Tahani M., 2010, Analysis of gas turbine operating parameters with inlet fogging and wet compression processes, Applied Thermal Engineering, 30, 2/3, 234-244
  • 24. Sextro W., Popp K., Krzyzynski T., 2001, Localization in nonlinear mistuned systems with cyclic symmetry, Nonlinear Dynamics, 25, 207-220
  • 25. Simani S., Patton R.J., 2008, Fault diagnosis of an industrial gas turbine prototype using a system identification approach, Control Engineering Practice, 16, 7, 769-786
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f90e596e-0002-430d-8d18-f03b199226fc
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