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Functional and diagnostic structure of the equipment of a wind power station

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This article describes functional and diagnostic structure of the equipment of a Wind Power Station. Considering particular operational conditions of a technical object, that is a set of Wind Power Station equipment, this is a significant issue. A structural model of Wind Power Station equipment is developed. Based on that, a functional – diagnostic model of Wind Power Station equipment is elaborated. That model is a basis for determining primary elements of the object structure, as well as for interpreting a set of diagnostic signals and their reference signals.
Rocznik
Strony
323--328
Opis fizyczny
Bibliogr. 28 poz., rys., tab.
Twórcy
  • Koszalin University of Technology, Faculty of Electronics and Computer Science, Śniadeckich St., 75-453 Koszalin, Poland
  • Vortex Energy Polska sp. z o.o., Department of Technical and Commercial Management, Rodła Square 8, 70-419 Szczecin, Poland
  • Koszalin University of Technology, Faculty of Mechanical Engineering, 15-17 Raclawicka St., 75-620, Koszalin, Poland
  • Koszalin University of Technology, Faculty of Electronics and Computer Science, Śniadeckich St., 75-453 Koszalin, Poland
  • Department of Mechanical Engineering, Faculty of Technology, Institute of Technology and Business in České Budějovice, Okružní 10, 370 01 České Budějovice, Czech Republic
Bibliografia
  • 1. Bernatowicz D., Duer S., Wrzesień P. (2018). Expert system supporting the diagnosis of the wind farm equipments, Communications in Computer and Information Science, Vol. 928, Springer, pp. 432-441.
  • 2. Buchannan B., Shortliffe E. (1985). Rule-Based expert systems. Addison-Wesley Publishing Company, p. 387.
  • 3. Duer S. (2011). Modelling of the operation process of repairable technical objects with the use information from an artificial neural network. Expert Systems With Applications. 38, pp. 5867-5878. http://dx.doi.org/10.1016/j.eswa.2010.11.036.
  • 4. Duer S. (2012). Artificial neural network in the control process of object’s states basis for organization of a servicing system of a technical objects. Neural Computing & Applications. Vol. 21, No. 1, pp. 153-160.
  • 5. Duer S. (2012). Examination of the reliability of a technical object after its regeneration in a maintenance system with an artificial neural network. Neural Computing & Applications. Vol. 21, 3, pp. 523-534.
  • 6. Duer S., Wrzesień P., Duer R. (2017). Creating of structure of facts for the knowledge base of an expert system for wind power plant’s equipment diagnosis. EEMS 2017, E3S Web of Conferences 19, 01029. DOI: 10.1051/e3sconf/20171901038.
  • 7. Hayer-Roth F., Waterman D., Lenat D. (1983). Building expert systems. Addison-Wesley Publishing Company.
  • 8. Kacalak W., Majewski M. (2012). New Intelligent Interactive Automated Systems for Design of Machine Elements and Assemblies. Lecture Notes in Computer Science 7666, Part IV. Springer, 115-122.
  • 9. Linz P. (2002). An Introduction to Formal Languages and Automata. University of California, Davis.
  • 10. Majewski M., Kacalak W. (2009). Intelligent e-learning system through artificial neural networks. Polish Journal of Environmental Studies. Vol. 18, 3B, Hard Publishing Company Olsztyn, pp. 237-242.
  • 11. Majewski M., Kacalak W. (2017). Smart Control of Lifting Devices Using Patterns and Antipatterns. Advances in Intelligent Systems and Computing, Vol. 573, Artificial Intelligence Trends in Intelligent Systems. Springer, 486-493. http://doi.org/10.1007/978-3-31957261-1_48.
  • 12. Majewski M., Kacalak W. (2017). Innovative Intelligent Interaction Systems of Loader Cranes and Their Human Operators. Advances in Intelligent Systems and Computing, Vol. 573, Artificial Intelligence Trends in Intelligent Systems. Springer, 474-485. http://doi.org/10.1007/978-3-319-57261-1_47.
  • 13. Majewski M., Kacalak W. (2016). Building Innovative Speech Interfaces using Patterns and Antipatterns of Commands for Controlling Loader Cranes. CSCI 2016, Las Vegas, USA. IEEE Computer Society, IEEE Xplore Digital Library. 525-530. http://dx.doi.org/10.1109/CSCI.2016.0105.
  • 14. Nakagawa T. (2005). Maintenance Theory of Reliability, Springer-Verlag London Limited.
  • 15. Nakagawa T., Ito K. (2000). Optimal inspection policies for a storage system with degradation at periodic tests, Math. Comput. Model. Vol. 31, pp. 191-195.
  • 16. Palkova Z., Okenka I. (2007). Programovanie. Slovak University of Agriculture in Nitra.
  • 17. Pogaku N., Prodanovic M., and Green T. C. (2007). Modeling, analysis and testing of autonomous operation of an inverter-based microgrid, IEEE Trans. Power Electron, Vol. 22, 2, pp. 613–625.
  • 18. Pokoradi L. (2015). Logical Tree of Mathematical Modeling. Theory and Applications of Mathematics & Computer Science 5 (1), pp. 20–28.
  • 19. Pokorádi L., Duer S. (2016). Investigation of maintenance process with Markov matrix. Proceedings of the 4th International Scientific Conference on Advances in Mechanical Engineering. 13-15 October 2016, Debrecen, Hungary, pp. 402-407.
  • 20. Shahanaghi K., Babaei H., Bakhsha A. (2009). A Chance Constrained Model for a Two Units Series Critical System Suffering From Continuous Deterioration, International Journal of Industrial Engineering & Production Research. Vol. 20, pp. 69-75.
  • 21. Pedrycz W. (1993). Fuzzy Control and fuzzy systems. John Walley And Sons, Inc.
  • 22. Rosiński A. (2010). Reliability analysis of the electronic protection systems with mixed – three branches reliability structure. Reliability, Risk and Safety. Theory and Applications. Vol. 3. Editors: R. Bris, C. Guedes Soares & S. Martorell. CRC Press/Balkema, London.
  • 23. Rosiński A. (2012). Reliability analysis of the electronic protection systems with mixed m–branches reliability structure. Advances in Safety, Reliability and Risk Management. Editors: Berenguer, Grall & Guedes Soares. Taylor & Francis Group, London.
  • 24. Sanjari MJ, Gharehpetian GB. (2014). Game theoretic approach to cooperative control of distributed energy resources in islanded microgrid considering voltage and frequency stability. Neural Comput Appl 25(2):343–351. doi: 10.1007/s00521-013-1497-5.
  • 25. Sanjari MJ, Gharehpetian GB. (2013). Small signal stability based fuzzy potential function proposal for secondary frequency and voltage control of islanded microgrid. Electr Power Compon Syst 41(5):485–499.
  • 26. Siergiejczyk M., Paś J., Rosiński A. (2015). Modeling of process of maintenance of transport systems telematics with regard to electromagnetic interferences. Communications in Computer and Information Science, 531: 99-107. DOI: 10.1007/978-3-319-24577-5_10.
  • 27. Siergiejczyk M., Krzykowska M., Rosiński A. (2015). Reliability assessment of integrated airport surface surveillance system. Advances in intelligent systems and computing, 365: 435-443. DOI: 10.1007/978-3-31919216-1_41.
  • 28. Waterman D. (1986). A guide to export systems. Addison-Wesley Publishing Company.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bdbdced1-d346-4ee2-973d-703327cdd41a
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