INTERVAL ROTOR-BEARING SYSTEMS STABILITY VIA MONTE CARLO SIMULATION

K.A.F. Moustafa and H. El-Awady

References

  1. [1] A.D. Dimarogonas, Interval analysis of vibrating systems,Journal of Sound and Vibration, 183(4), 1992, 739–749. doi:10.1006/jsvi.1995.0283
  2. [2] A.D. Dimarogonas & S.A. Paipetis, Analytical methods in rotordynamics (London: Elsevier Applied science Publishers, 1983).
  3. [3] R. Stanway & C.R. Burrows, Active vibration control of aflexible rotor on flexibly mounted journal bearings, Journal ofDynamic Systems, Measurement, and Control, 103(4), 1981,383–388.
  4. [4] K.A.F. Moustafa & K. Asfar, Identification of journal bearingmodal parameters, International Journal of Analytical andExperimental Modal Analysis, 5(4), 1990, 213–221.
  5. [5] J. Chen, Sufficient conditions on stability of interval matrices:connections and new results, IEEE Transactions on AutomaticControl, 37(4), 1992, 541–544. doi:10.1109/9.126595
  6. [6] D. Hertz, The extreme eigenvalues and stability of real sym-metric interval matrices, IEEE Transactions on AutomaticControl, 37(4), 1992, 532–535. doi:10.1109/9.126593
  7. [7] K.A.F. Moustafa, Stability of journal bearing-rotor systemswith interval bearing parameters, Journal of Vibration andControl, 5(6), 1999, 941–953. doi:10.1177/107754639900500606
  8. [8] K.A.F. Moustafa & M. El-Gebeily, Effect of manufacturingtolerances on rotor-bearing systems stability via interval anal-ysis, Proc. 7th International Conf. on Production Engineering,Design and Control (PEDAC’2001), Alexandria University,Egypt, 2001.
  9. [9] I. Manno, Introduction to the Monte Carlo method (Budapest,Hungary: Akad´emiai Kiad´o, 1999).
  10. [10] C.P. Robert & G. Casella, Monte Carlo statistical methods,Second Edition (New York: Springer Texts in Statistics,Springer Science & Business Media Inc., 2004).
  11. [11] E. Gazi, W.D. Seider, & L.H. Ungar, A non-parametric montecarlo technique for controller verification, Automatica, 33(5),1997, 901–906.207 doi:10.1016/S0005-1098(96)00227-0
  12. [12] G.A. Mikhailov, Parametric estimates by the Monte Carlomethod (Utrecht, Netherlands: VSP, 1999).
  13. [13] A.B. Owen, Monte Calro, quasi-Monte Carlo, and random-ized quasi-Monte Carlo, Monte-Carlo and quasi-Monte Carlomethods, Proc. of the Conf. held at the Claremont GraduateUniversity, Claremont, California, USA, June 22–26, 1998,86–97.
  14. [14] J.M. Vance, Rotordynamics of turbomachinery (New York:John Wiley & Sons, 1988).
  15. [15] R. Barron, Engineering condition monitoring (New York:Longman, 1996).
  16. [16] I.H. Hibey, Stochastic stability theory for systems contain-ing interval matrices, IEEE Transactions on Aerospace andElectronic Systems, 32(4), 1996, 1385–1391. doi:10.1109/7.543859
  17. [17] M. El-Gebeily & K.A.F. Moustafa, Necessary and sufficientconditions for the stability of linear parameter-dependent sys-tems, International Journal of Systems Science, 32(7), 2001,931–936. doi:10.1080/00207720010005141
  18. [18] B.S. Blanchard & W.J. Fabrycky, Systems engineering andanalysis (New Jersey: Prentice Hall, 1998).
  19. [19] J.E. Shigley & C.R. Mischke, Mechanical engineering design(New York: McGraw Hill, 1989).
  20. [20] A. Law & W.D. Kelton, Simulation modeling and analysis(New York: McGraw Hill, 1991).
  21. [21] M. Evans, N. Hastings, & B. Peacock, Beta distribution,Chapter 5 in Statistical Distributions, Third Edition (NewYork: Wiley, 2000).

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