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Kriging Metamodeling in Rotordynamics: Application for Predicting Critical Speeds and Vibrations of a Flexible Rotor

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  • J.-J. Sinou
  • L. Nechak
  • S. Besset

Abstract

Rotating machinery produces vibrations depending upon the design of the rotor systems as well as any faults or uncertainties in the machine that can increase the vibrations of such systems. This study illustrates the effectiveness of using surrogate modeling based on kriging in order to predict the vibrational behavior (i.e., the critical speeds and the vibration amplitudes) of a complex flexible rotor in the presence of uncertainties. The basic idea of kriging is to predict unknown values of a function by using a small size set of known data. The kriging estimation is based on a weighted average of the known values of the function in the neighborhood of the point for which the value of the function has to be calculated. The crucial dependence of a kriging predictor versus the correlation functions and different orders will be illustrated. This paper also shows that reducing the number of samples required to have predictive models can be achieved by performing an initial understanding of the mechanical system of interest and by considering certain characteristics directly deriving from the physics of the problem studied.

Suggested Citation

  • J.-J. Sinou & L. Nechak & S. Besset, 2018. "Kriging Metamodeling in Rotordynamics: Application for Predicting Critical Speeds and Vibrations of a Flexible Rotor," Complexity, Hindawi, vol. 2018, pages 1-26, March.
    • Handle: RePEc:hin:complx:1264619
    DOI: 10.1155/2018/1264619
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    References listed on IDEAS

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    1. Kleijnen, Jack P.C., 2009. "Kriging metamodeling in simulation: A review," European Journal of Operational Research, Elsevier, vol. 192(3), pages 707-716, February.
    2. Kleijnen, Jack P.C., 2017. "Regression and Kriging metamodels with their experimental designs in simulation: A review," European Journal of Operational Research, Elsevier, vol. 256(1), pages 1-16.
    3. Jack P.C. Kleijnen, 2015. "Design and Analysis of Simulation Experiments," International Series in Operations Research and Management Science, Springer, edition 2, number 978-3-319-18087-8, July-Dece.
    4. Kleijnen, J.P.C., 2015. "Regression and Kriging Metamodels with Their Experimental Designs in Simulation : Review," Other publications TiSEM c592e895-1656-43c3-8c7e-f, Tilburg University, School of Economics and Management.
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    Cited by:

    1. Chao Fu & Guojin Feng & Jiaojiao Ma & Kuan Lu & Yongfeng Yang & Fengshou Gu, 2020. "Predicting the Dynamic Response of Dual-Rotor System Subject to Interval Parametric Uncertainties Based on the Non-Intrusive Metamodel," Mathematics, MDPI, vol. 8(5), pages 1-15, May.
    2. Chao Fu & Dong Zhen & Yongfeng Yang & Fengshou Gu & Andrew Ball, 2019. "Effects of Bounded Uncertainties on the Dynamic Characteristics of an Overhung Rotor System with Rubbing Fault," Energies, MDPI, vol. 12(22), pages 1-15, November.

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