Dynamic modeling for rigid rotor bearing systems with a localized defect considering additional deformations at the sharp edges

Jing Liu, Yimin Shao

Research output: Contribution to journalArticlepeer-review

223 Scopus citations

Abstract

Rotor bearing systems (RBSs) play a very valuable role for wind turbine gearboxes, aero−engines, high speed spindles, and other rotational machinery. An in−depth understanding of vibrations of the RBSs is very useful for condition monitoring and diagnosis applications of these machines. A new twelve−degree−of−freedom dynamic model for rigid RBSs with a localized defect (LOD) is proposed. This model can formulate the housing support stiffness, interfacial frictional moments including load dependent and load independent components, time−varying displacement excitation caused by a LOD, additional deformations at the sharp edges of the LOD, and lubricating oil film. The time−varying displacement model is determined by a half−sine function. A new method for calculating the additional deformations at the sharp edges of the LOD is analytical derived based on an elastic quarter−space method presented in the literature. The proposed dynamic model is utilized to analyze the influences of the housing support stiffness and LOD sizes on the vibration characteristics of the rigid RBS, which cannot be predicted by the previous dynamic models in the literature. The results show that the presented method can give a new dynamic modeling method for vibration formulation for a rigid RBS with and without the LOD on the races.

Original languageEnglish
Pages (from-to)84-102
Number of pages19
JournalJournal of Sound and Vibration
Volume398
DOIs
StatePublished - 23 Jun 2017
Externally publishedYes

Keywords

  • Dynamic modeling
  • Localized defect (LOD)
  • LOD edge deformation
  • Rotor bearing system (RBS)
  • Support stiffness

Fingerprint

Dive into the research topics of 'Dynamic modeling for rigid rotor bearing systems with a localized defect considering additional deformations at the sharp edges'. Together they form a unique fingerprint.

Cite this