Friction power loss in ball bearings: Correlation with bearing skidding and cage motion stability

This study introduces a prediction method for bearing friction power loss, focusing on the interplay of bearing skidding and cage motion stability on the tribological properties of ball bearings. The internal friction source is first identified in eight forms according to the interaction analysis among bearing components. Then, the ring flexibility generated by the assembly state of rotor-bearing system as well as the cage flexibility caused by the centrifugal effect are considered, and the effects of outer ring spatial displacement and contact force on outer ring deformations are also analyzed. Further, the traction effect of ball-raceway and the hydrodynamic lubrication of cage-guiding ring are discussed to establish the improved bearing dynamic model. The validity and reliability for present method are confirmed through a comparative analysis with experimental data. Finally, the relationships between dynamic behavior and friction power loss are investigated. Results denote the critical role of the friction loss of the bearing components subjected to lubricant viscosity resistance and the sliding friction loss of the cage-guiding ring in determining the total tribological properties. The dynamic behavior can also be optimized by adjusting the bearing preload and cage structure so as to effectively weaken the bearing friction power loss.

Authors

Publication Details

Journal
Friction
Published
2024-12-06
DOI
https://doi.org/10.26599/frict.2025.9440980
Citations
2
Primary Topic
Gear and Bearing Dynamics Analysis
Type
article
Field-Weighted Citation Impact
0.43
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Friction power loss in ball bearings: Correlation with bearing skidding and cage motion stability

Mingkai Wang, Ke Yan, Jun Hong, Kim Tiow Ooi et al.
2 citations
Friction
Gear and Bearing Dynamics Analysis
0.43
article

Friction power loss in ball bearings: Correlation with bearing skidding and cage motion stability

Mingkai Wang, Ke Yan, Jun Hong, Kim Tiow Ooi, Linbo Zhu, Haizhen Li
article en
2 citations

Abstract

This study introduces a prediction method for bearing friction power loss, focusing on the interplay of bearing skidding and cage motion stability on the tribological properties of ball bearings. The internal friction source is first identified in eight forms according to the interaction analysis among bearing components. Then, the ring flexibility generated by the assembly state of rotor-bearing system as well as the cage flexibility caused by the centrifugal effect are considered, and the effects of outer ring spatial displacement and contact force on outer ring deformations are also analyzed. Further, the traction effect of ball-raceway and the hydrodynamic lubrication of cage-guiding ring are discussed to establish the improved bearing dynamic model. The validity and reliability for present method are confirmed through a comparative analysis with experimental data. Finally, the relationships between dynamic behavior and friction power loss are investigated. Results denote the critical role of the friction loss of the bearing components subjected to lubricant viscosity resistance and the sliding friction loss of the cage-guiding ring in determining the total tribological properties. The dynamic behavior can also be optimized by adjusting the bearing preload and cage structure so as to effectively weaken the bearing friction power loss.

FrictionVol. 13(7)
Affordable and clean energy
Openalex Percentile: Top 40%
Gear and Bearing Dynamics Analysis
0.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.