Keywords
shaft
multiple-mass model
parameter identification
genetic algorithm
conjugate gradient method
How to Cite
Abstract
The mathematical models of different dimensions with a finite number of degrees of freedom of a powerful turbine-generator shaft, which is used to calculate the torsional vibrations of the shaft train, were compared. The computational studies of transients during switching of the turbine-generator to parallel operation with the electrical system with no-load conditions using different mathematical models of the shaft train and comparison of torsional moments were performed. The method of parameter identification for the multi-mass model of the shaft line of the turbine set using an iterative conjugate gradient method and a heuristic genetic algorithm was developed. The performed computational studies have shown efficiency of the developed technique. References 12, figures 6.
References
Biederman V.L. Theory of Mechanical Oscillations: Textbook for Universities. М: Vyssh.shkola, 1980. 408 p.
Bovsunovsky A.P., Kuevda Yu.V. Accounting of the swings of the shaft line of the turbine unit in the assessment of fatigue damage to its elements in the process of successful non-synchronous inclusion. Pratsi Instytutu Elektrodynamiky NANU. 2015. Issue 42. Pp. 56–59.
Detinko F.M., Zagorodnaya G.A., Fastovsky V.M. Strength and oscillations of electric machines. L.: Ehnergiya, 1969. 440 p.
Kyrylenko O.V., Segeda M.S., Butkevych O.F., Mazur T.A. Mathematical modeling in electric power industry: Textbook. Lviv: Publishing house of the National Academy of Sciences. University Lvivska Polytechnika, 2010. 608 p.
Lashko V.A., Leibovich M.V. Matrix methods in the calculations of torsional oscillations of power plants with ICE. Khabarovsk: Izd-vo KhSTU, 2003. 211 p.
Lukin V.N., Romanov M.F., Tolkachev E.A. System analysis of electrical circuits and machines. L.: Izd-vo Leningr.un-ta, 1985. 136 p.
Moiseev N.N., Ivanilov Yu.P., Stolyarova E.M. Methods of optimization. M.: Main editorial office of phys.-math. Literatury, 1978. 352 p.
Rutkovskaya D., Pilnskii M., Rutkovskii L. Neural networks, genetic algorithms and fuzzy systems. M.: Hot line Telecom, 2006. 452 p.
Chaban A.V. Algorithm rozrahunku mehanichnykh krutilnykh kolivnykh processes on the application of the system parova turbina - rotor synchronous turbogenerator. Visnyk Nats. University Lvivska polytechnika. 2006. No 556. Pp. 86–90.
Bovsunovskii A.P. Torsional vibration in steam turbine shafting in turbogenerator abnormal modes of operation. Strength of Materials. 2012. 44 (2). Pp. 177–186.
Hosea M.E., Shampine L.F. Analysis and implementation of TR-BDF2. Applied Numerical Mathematics. 1996. 20. Pp. 21–37.
Isermann R., Munchhof M. Identification of Dynamic systems. Berlin-Heidelberg: Springer, 2011. 705 p.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright (c) 2017 Yu.V. Kuievda, S.M. Baluta