A Study of Tribological Performance Prediction Based on Surface Texture Parameters

Surface texture parameters are a quantitative way of characterising surface topographical features and are closely related to tribological properties. In this paper, the correlation between surface topographic features and friction coefficient is investigated on the basis of the proposed improved correlation analysis model for high-speed milling surface topography of hardened steel. It was found that the friction coefficient could not be accurately reflected by a single parameter, so a prediction model for the friction coefficient based on Sxp, Sq, Sp, Sz, Sku and Sdq was developed. In this paper, the parameter screening was completed based on the changing characteristics of the data, and a multi-parameter prediction model of the friction coefficient in the stable wear stage was established, which provides a new idea to investigate the influence of the characteristics of surface topography on tribological performance.

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Publication Details

Journal
Crystals
Published
2024-09-28
DOI
https://doi.org/10.3390/cryst14100848
Citations
1
Primary Topic
Tribology and Lubrication Engineering
Type
article
Field-Weighted Citation Impact
0.21
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article

A Study of Tribological Performance Prediction Based on Surface Texture Parameters

Zhongxun Liu, Wei Zhang, Ben Wang, Jingwen Sun
1 citations
Crystals
Tribology and Lubrication Engineering
0.21
article

A Study of Tribological Performance Prediction Based on Surface Texture Parameters

Zhongxun Liu, Wei Zhang, Ben Wang, Jingwen Sun
article en
1 citations

Abstract

Surface texture parameters are a quantitative way of characterising surface topographical features and are closely related to tribological properties. In this paper, the correlation between surface topographic features and friction coefficient is investigated on the basis of the proposed improved correlation analysis model for high-speed milling surface topography of hardened steel. It was found that the friction coefficient could not be accurately reflected by a single parameter, so a prediction model for the friction coefficient based on Sxp, Sq, Sp, Sz, Sku and Sdq was developed. In this paper, the parameter screening was completed based on the changing characteristics of the data, and a multi-parameter prediction model of the friction coefficient in the stable wear stage was established, which provides a new idea to investigate the influence of the characteristics of surface topography on tribological performance.

CrystalsVol. 14(10)
Harbin University of Science and Technology (CN), Huanghuai University (CN)
Openalex Percentile: Top 52%
Tribology and Lubrication Engineering
0.21
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A Study of Tribological Performance Prediction Based on Surface Texture Parameters — Zhongxun Liu, Wei Zhang, et al. · Crystals (2024) | TGRS Research Map | TGRS