EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 19 / No 2 (2018) Mechanics & Industry, 19 2 (2018) 209 References
Open Access
Issue
Mechanics & Industry
Volume 19, Number 2, 2018
Article Number 209
Number of page(s) 9
DOI https://doi.org/10.1051/meca/2017056
Published online 03 September 2018
  1. X. Wu, J. Shen, Y. Li, K. Lee, Steam power plant configuration, design, and control, Wiley Interdiscip. Rev. 4 (2015) 537–563 [Google Scholar]
  2. B.A. Alekseev, Main equipment in power systems. Determining the status (diagnostics) of large turbine units, NTs ENAS, Moscow, 2001 [Google Scholar]
  3. S. Thomas, R. Dawe, Review of ways to transport natural gas energy from countries which do not need the gas for domestic use, Energy 28 (2003) 1461–1477 [CrossRef] [Google Scholar]
  4. V.V. Shevchenko, A. Minko, Modernisation of turbo-generators of domestic structures, taking into account the requirements of maintaining their competitiveness, J. NTU "KhPI 38 (2014) 146–155 [Google Scholar]
  5. Y.-C. Huang, C.-M. Huang, Optimization based support vector classifier for vibration fault diagnosis of steam turbine-generator sets, Procedia Eng. (2012) 1816–1821 [CrossRef] [Google Scholar]
  6. S. Biswas, T. Breuel, Learning morphological transformations with recurrent neural networks. Procedia Comput. Sci. 53 (2015) 335–344 [CrossRef] [Google Scholar]
  7. A.M. Pantaleo, S. Camporeale, B. Fortunato, Small scale biomass CHP: techno-economic performance of steam vs. gas turbines with bottoming ORC, Energy Procedia 82 (2015) 825–832 [CrossRef] [Google Scholar]
  8. V.V. Shevchenko, A. Minko, S.A. Lukyanchikova, Proposals to modernize the turbogenerators designs fulfilled a technical resource, J. Sci. Technol. 3 (2015) 8–13 [Google Scholar]
  9. A.I. Kumenko, The improvement modification of rotor unbalance verification technique in monitoring systems and automatic diagnostics. Procedia Eng. 113 (2015) 324–331 [CrossRef] [Google Scholar]
  10. P. Cross, X. Ma, Nonlinear system identification for model-based condition monitoring of wind turbines, Renew. Energy 71 (2014) 166–175 [CrossRef] [Google Scholar]
  11. I. Antoniadou, G. Manson, W.J. Staszewski, T. Barszcz, A time-frequency analysis approach for condition monitoring of a wind turbine gearbox under varying load conditions, Mech. Syst. Signal Process. 64 (2015) 188–216 [CrossRef] [Google Scholar]
  12. W.Y. Liu, B.P. Tang, J.G. Han, X.N. Lu, N.N. Hu, Z.Z. He, The structure healthy condition monitoring and fault diagnosis methods in wind turbines: a review, Renew. Sustain. Energy Rev. 44 (2015) 466–472 [CrossRef] [Google Scholar]
  13. C. Carcasci, B. Pacifici, L. Winchler, L. Cosi, R. Ferraro, Thermoeconomic analysis of a one-pressure level heat recovery steam generator considering real steam turbine cost, Energy Procedia 82 (2015) 591–598 [CrossRef] [Google Scholar]
  14. G Sisi, P. Liu, L. Zheng, Data reconciliation for the overall thermal system of a steam turbine power plant, Appl. Energy (2016) 165 [Google Scholar]
  15. O. Shindor, A. Svirina, Hydraulic units' vibration diagnostics subsystem improvement and its impact on the level of technogenic risks, Energy Procedia 72 (2015) 345–352 [CrossRef] [Google Scholar]
  16. A.M. Pantaleo, P.D. Ciliberti, S.N. Camporeale, Thermo-economic Assessment of Small Scale Biomass CHP: Steam Turbines vs ORC in Different Energy Demand Segments, Energy Procedia 75 (2015) 1609–1617 [CrossRef] [Google Scholar]
  17. V. Shevchenko, I. Lisan, Evaluation of the technical parameters of turbine generators to determine the work to restore them or to establish the need to replace. Systems of arms and military equipment 2 (2015) 145–150 [Google Scholar]
  18. E.V. Urev, J.N. Ahypytova, Problems of Creating technical diagnosis of turbine units, J Thermal Eng 11 (2001) 25–30 [Google Scholar]
  19. V. Uraikul, C.W. Chan, P. Tontiwachwuthikul, Artificial intelligence for monitoring and supervisory control of process systems, Int. J. Eng. Appl. Sci. 20 (2007) 115–131 [Google Scholar]
  20. T. Gavrilova, V. Horoshavskiy, Knowledge base of intellectual systems, St. Petersburg, Piter, 2001 (in Russian) [Google Scholar]
  21. K. Chen, L. Chen, M. Chen, C. Lee, Using SVM based method for equipment fault detection in a thermal power plant, Comput. Ind. 62 (2011) 42–50. [CrossRef] [Google Scholar]
  22. B. Suleimenov, L. Sugurova, N. Turynbetov, A. Suleimenov, Concept of developing an intelligent system for control and operational diagnostics of technological equipment condition, Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 1 (2014) 27–34 [CrossRef] [Google Scholar]
  23. H. Malik, S. Mishra, Application of probabilistic neural network in fault diagnosis of wind turbine using FAST, TurbSim and Simulink, Procedia Comput. Sci. 58 (2015) 186–193 [CrossRef] [Google Scholar]
  24. Y. Li, B. Yang, Z. Wang, X Fault pattern classification of turbine-generator set based on artificial neural network. International Conference 15, 157–159, 2010 [Google Scholar]
  25. K. Lee, J.V. Sickel, J. Hoffman, Controller design for a large-scale ultrasupercritical once-through boiler power plant, IEEE Trans. Energy Convers. 25 (2010) 1063–1070 [CrossRef] [Google Scholar]
  26. A. Lees, Vibration Problems in Machines: Diagnosis and Resolution, CRC Press, 2016 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.