Analysis and Prediction of Wear Performance of Different Topography Surface

Analysis and Prediction of Wear Performance of Different Topography Surface

Surface roughness parameters are an important factor affecting surface wear resistance, but the relevance between the wear resistance and the surface roughness parameters has not been well studied. This paper based on the finite element simulation technology, through the grey incidence analysis (GIA...

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Main Authors: Ben Wang, Minli Zheng, Wei Zhang
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Materials
Subjects:
surface topography
finite element simulation
surface texture roughness parameters
wear resistance
GM(0,6) model
Online Access:https://www.mdpi.com/1996-1944/13/22/5056
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spelling doaj-7aabace20f38452aac1aaad47659265f2020-11-25T04:09:10ZengMDPI AGMaterials1996-19442020-11-01135056505610.3390/ma13225056Analysis and Prediction of Wear Performance of Different Topography SurfaceBen Wang0Minli Zheng1Wei Zhang2Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, ChinaKey Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, ChinaKey Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, ChinaSurface roughness parameters are an important factor affecting surface wear resistance, but the relevance between the wear resistance and the surface roughness parameters has not been well studied. This paper based on the finite element simulation technology, through the grey incidence analysis (GIA) method to quantitatively study the relevance between the wear amount of per unit sliding distance (Δ<i>V<sub>s</sub></i>) and the surface texture roughness parameters under dry friction conditions of the different surface topography. A zeroth order six-variables grey model, GM(0,6), for prediction the wear characteristic parameter Δ<i>V<sub>s</sub></i> was established, and the experiment results verified that the prediction model was accurate and reasonable.https://www.mdpi.com/1996-1944/13/22/5056surface topographyfinite element simulationsurface texture roughness parameterswear resistanceGM(0,6) model
collection DOAJ
language English
format Article
sources DOAJ
author Ben Wang
Minli Zheng
Wei Zhang
spellingShingle Ben Wang
Minli Zheng
Wei Zhang
Analysis and Prediction of Wear Performance of Different Topography Surface
Materials
surface topography
finite element simulation
surface texture roughness parameters
wear resistance
GM(0,6) model
author_facet Ben Wang
Minli Zheng
Wei Zhang
author_sort Ben Wang
title Analysis and Prediction of Wear Performance of Different Topography Surface
title_short Analysis and Prediction of Wear Performance of Different Topography Surface
title_full Analysis and Prediction of Wear Performance of Different Topography Surface
title_fullStr Analysis and Prediction of Wear Performance of Different Topography Surface
title_full_unstemmed Analysis and Prediction of Wear Performance of Different Topography Surface
title_sort analysis and prediction of wear performance of different topography surface
publisher MDPI AG
series Materials
issn 1996-1944
publishDate 2020-11-01
description Surface roughness parameters are an important factor affecting surface wear resistance, but the relevance between the wear resistance and the surface roughness parameters has not been well studied. This paper based on the finite element simulation technology, through the grey incidence analysis (GIA) method to quantitatively study the relevance between the wear amount of per unit sliding distance (Δ<i>V<sub>s</sub></i>) and the surface texture roughness parameters under dry friction conditions of the different surface topography. A zeroth order six-variables grey model, GM(0,6), for prediction the wear characteristic parameter Δ<i>V<sub>s</sub></i> was established, and the experiment results verified that the prediction model was accurate and reasonable.
topic surface topography
finite element simulation
surface texture roughness parameters
wear resistance
GM(0,6) model
url https://www.mdpi.com/1996-1944/13/22/5056
work_keys_str_mv AT benwang analysisandpredictionofwearperformanceofdifferenttopographysurface
AT minlizheng analysisandpredictionofwearperformanceofdifferenttopographysurface
AT weizhang analysisandpredictionofwearperformanceofdifferenttopographysurface
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