Study on Comprehensive Performance of Four-Point Contact Ball Slewing Bearings Based on a Bearing Support Bolt-Integrated Model

To investigate four-point contact ball slewing bearings, a bearing support bolt-integrated model was created with HyperMesh and ANSYS software, and its accuracy was theoretically confirmed. This study examines how the rolling element number Z, contact angle α, bolt number N, bolt pre-tightening force coefficient P, and radial load-overturning moment angle θ affect the comprehensive performance of four-point contact ball slewing bearings and connecting bolts. The study found that increasing Z, α, N, P, and θ reduces overall bearing, ring, rolling element, and contact load deformations. The maximum deformation and stress of bolts rise with P but decrease with Z, α, N, and θ. The degree of influence of each parameter on the deformation of the inner and outer rings, the deformation of the rolling element, and the contact load of the rolling body from large to small is ranked as follows: α, N, Z, θ, and P; the degree of influence on bolt deformation and bolt stress distribution uniformity from large to small is ranked as follows: N, α, Z, θ, and P; the degree of influence on the overall deformation of the bearing from large to small is ranked as follows: N, θ, α, Z and P; the degree of impact on the maximum stress of the bolt from large to small is ranked as follows: P, N, Z, α, θ. To improve the overall performance of a four-point contact ball slewing bearing, increase α, N, Z, and θ.

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Institutions

Publication Details

Journal
Machines
Published
2024-11-15
DOI
https://doi.org/10.3390/machines12110814
Citations
3
Primary Topic
Gear and Bearing Dynamics Analysis
Type
article
Field-Weighted Citation Impact
0.64

Funders

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article

Study on Comprehensive Performance of Four-Point Contact Ball Slewing Bearings Based on a Bearing Support Bolt-Integrated Model

Xinghui Xie, Dongchen Qin, Jingbo Wen, Zhanshu He et al.
3 citations
Machines
Gear and Bearing Dynamics Analysis
0.64
article

Study on Comprehensive Performance of Four-Point Contact Ball Slewing Bearings Based on a Bearing Support Bolt-Integrated Model

Xinghui Xie, Dongchen Qin, Jingbo Wen, Zhanshu He, Jinggan Shao, Zhenpeng Shi, Xianghui Liu
article en
3 citations

Abstract

To investigate four-point contact ball slewing bearings, a bearing support bolt-integrated model was created with HyperMesh and ANSYS software, and its accuracy was theoretically confirmed. This study examines how the rolling element number Z, contact angle α, bolt number N, bolt pre-tightening force coefficient P, and radial load-overturning moment angle θ affect the comprehensive performance of four-point contact ball slewing bearings and connecting bolts. The study found that increasing Z, α, N, P, and θ reduces overall bearing, ring, rolling element, and contact load deformations. The maximum deformation and stress of bolts rise with P but decrease with Z, α, N, and θ. The degree of influence of each parameter on the deformation of the inner and outer rings, the deformation of the rolling element, and the contact load of the rolling body from large to small is ranked as follows: α, N, Z, θ, and P; the degree of influence on bolt deformation and bolt stress distribution uniformity from large to small is ranked as follows: N, α, Z, θ, and P; the degree of influence on the overall deformation of the bearing from large to small is ranked as follows: N, θ, α, Z and P; the degree of impact on the maximum stress of the bolt from large to small is ranked as follows: P, N, Z, α, θ. To improve the overall performance of a four-point contact ball slewing bearing, increase α, N, Z, and θ.

MachinesVol. 12(11)
Zhengzhou University (CN), Luoyang Institute of Science and Technology (CN)
U.S. Department of Transportation, Henan Provincial Department of Transportation
Openalex Percentile: Top 35%
Gear and Bearing Dynamics Analysis
0.64
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Study on Comprehensive Performance of Four-Point Contact Ball Slewing Bearings Based on a Bearing Support Bolt-Integrated Model — Xinghui Xie, Dongchen Qin, et al. · Machines (2024) | TGRS Research Map | TGRS