Discrimination of wear performance based on surface roughness parameters arithmetic mean height (Sa) and skewness (Ssk)

Duo, Yang; Tang, Jinyuan; Zhao, Zemin; Shengyu, You; Li, Guihua; Zhu, Guangzao

doi:10.1016/j.wear.2024.205397

Wear

2024

DOI: 10.1016/j.wear.2024.205397

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Discrimination of wear performance based on surface roughness parameters arithmetic mean height (Sa) and skewness (Ssk)

Yang Duo,

Jinyuan Tang,

Zemin Zhao

et al.

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2024

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Cited by 3 publications

References 25 publications

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Characterization and correlation analysis of surface topography in ball-end milling

Wang,

Liu,

Sun

2024

Surf. Topogr.: Metrol. Prop.

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Surface texture is the most commonly used parameter for the quantitative characterization of surface topography. It is important for the study of the topography characteristics and functional properties of surfaces. In this paper, the surface topography characteristics, surface texture parameters, and change rule of the bearing area curve when the cutting vibration of the adjacent teeth of the ball-end milling cutter is asymmetric were analyzed, and the correlation between the inflection points and the surface texture parameters of the bearing area curve were studied according to the improved correlation analysis model. This study provides essential insights into the mechanism that drives the formation of the surface topography of ball-end milling and the intrinsic characteristic laws of the surface topography.

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Characterization and correlation analysis of surface topography in ball-end milling

Wang,

Liu,

Sun

2024

Surf. Topogr.: Metrol. Prop.

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Effect of Y Addition on Microstructure and Mechanical Properties of CoCrFeNi HEA Coatings by Laser Cladding

Shu,

Su,

et al. 2024

Coatings

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In this study, CoCrFeNiYx (x = 0, 0.1, 0.2, 0.3) high entropy alloy (HEA) coatings were produced on Ti6Al4V by laser cladding. The influence of Y on the microstructure and mechanical properties of CoCrFeNi HEA coatings was systematically examined. The analysis uncovered that the coatings primarily consist of three principal phases: α(Ti), Ti2Ni, and TiC. The incorporation of Y led to enhanced lattice distortion, which positively influenced solid solution strengthening. Moreover, grain refinement resulted in a denser microstructure, significantly reducing internal defects and thereby enhancing the coating’s performance. The average microhardness of the CoCrFeNiY0.2 coating was 702.46 HV0.2. The wear rates were 1.16 × 10−3 mm3·N−1·m−1 in air and 3.14 × 10−3 mm3·N−1·m−1 in a neutral solution, which were 27.0% and 30.8% lower than those of the CoCrFeNi coatings, respectively, indicating superior wear resistance. The Y content in the CoCrFeNiY0.3 coating was excessively high, resulting in the formation of Y-rich clusters. The accumulation of these impurities at the grain boundaries led to crack and pore formation, thereby reducing the wear resistance of the coating. Our study demonstrated that laser cladding an optimal amount of Y-doped CoCrFeNi HEA coatings on the Ti6Al4V substrate significantly enhanced the microstructure and mechanical properties of the substrate, particularly its wear resistance in both air and neutral environments, thereby improving the durability and reliability of titanium alloys in practical applications.

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A Study of Tribological Performance Prediction Based on Surface Texture Parameters

Wang,

Sun,

Liu

et al. 2024

Crystals

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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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Discrimination of wear performance based on surface roughness parameters arithmetic mean height (Sa) and skewness (Ssk)

Cited by 3 publications

References 25 publications

Characterization and correlation analysis of surface topography in ball-end milling

Characterization and correlation analysis of surface topography in ball-end milling

Effect of Y Addition on Microstructure and Mechanical Properties of CoCrFeNi HEA Coatings by Laser Cladding

A Study of Tribological Performance Prediction Based on Surface Texture Parameters

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