Nonlinear dynamic coefficients prediction of journal bearings using partial derivative method

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

For decades, linear dynamic coefficients of bearings are widely used to evaluate the stability and dynamic response of oil-film bearing-rotor systems. However, there often exist many strong nonlinear excitation sources in rotor systems. Therefore, the linear oil-film forces cannot reflect the nonlinearity characteristics of rotor systems. Some researchers present numerical methods for prediction of bearing nonlinear dynamic coefficients in order to represent nonlinear oil-film forces of bearing, while their methods are closely dependent on the size and shape of journal orbits. This article gives a computational method which is independent on the journal orbit to predict bearing dynamic coefficients using partial derivative method. The reliability of the numerical method is verified by comparing the linear dynamic coefficients of two-axial-groove bearing with the published results. The variation of dynamic coefficients with eccentricity ratios and length-to-diameter ratios of a simple oil-lubricated 360° journal bearing model is discussed. The numerical results indicate that bearing dynamic coefficients are dramatically increasing with the growth of eccentricity ratios and length-to-diameter ratios, especially when eccentricity ratio is larger than 0.8. The numerical model presented in this article will greatly simplify the solution of oil-film forces in nonlinear dynamic analysis of rotor systems.

Original languageEnglish
Pages (from-to)328-339
Number of pages12
JournalProceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology
Volume226
Issue number4
DOIs
StatePublished - Apr 2012

Keywords

  • Fluid-film lubrication
  • Nonlinear dynamic coefficients
  • Oil-film force
  • Partial derivative method

Fingerprint

Dive into the research topics of 'Nonlinear dynamic coefficients prediction of journal bearings using partial derivative method'. Together they form a unique fingerprint.

Cite this