Analysis and Evaluation of the Synergistic Effect of Ceramic Materials and Surface Texture on Anti-Abrasive Particle Wear under Rolling Conditions

磨料 材料科学 陶瓷 纹理(宇宙学) 冶金 粒子(生态学) 粒径 复合材料 工程类 化学工程 计算机科学 地质学 海洋学 人工智能 图像(数学)
作者
Xudong Zhao,Yimin Zhang,Shuzhi Gao
出处
期刊:Tribology International [Elsevier]
卷期号:197: 109821-109821 被引量:2
标识
DOI:10.1016/j.triboint.2024.109821
摘要

Damage to mechanical components caused by contaminant ingress is a common failure. In response to this issue, this study introduces a synergistic abrasion reduction method based on the combined application of ceramic materials and surface texturing. Using cylindrical thrust roller bearings as an illustration, circular textures were applied to the raceways, and a small number of steel rollers were substituted with ceramic ones. Moreover, alumina was introduced into the lubricant as a contaminant. The frictional and dynamic performance of the "ceramic-textured surface" combination under lubricant contamination conditions was explored and compared with corresponding single abrasion reduction techniques. The synergistic abrasion reduction mechanism of the "ceramic-textured surface" combination was also examined. The findings reveal that under lubricant contamination conditions, the synergistic abrasion reduction method surpasses individual abrasion reduction methods and demonstrates a certain degree of complementarity. Compared with traditional all-steel bearings, textured bearings with four ceramic rollers have reduced the average frictional force by approximately 56.82%, and the mass loss of the shaft washer and seat washer has been reduced by approximately 81.01% and 80.86%, respectively. Rolling elements treated with the synergistic abrasion reduction method exhibit enhanced resistance to abrasive particle wear. This improvement is attributed to the collaborative effects of various mechanisms, including crushing and refinement, capture and storage, grinding and finishing, as well as self-healing and smoothing.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
小田发布了新的文献求助10
刚刚
sankumao发布了新的文献求助30
刚刚
奋斗的盼柳完成签到 ,获得积分10
1秒前
2秒前
Jasper应助handsomecat采纳,获得10
2秒前
2秒前
李雪完成签到,获得积分10
3秒前
3秒前
sv发布了新的文献求助10
5秒前
小田完成签到,获得积分10
5秒前
茶茶完成签到,获得积分20
5秒前
苏兴龙完成签到,获得积分10
5秒前
坚强的亦云-333完成签到,获得积分10
5秒前
Ava应助dan1029采纳,获得10
6秒前
6秒前
6秒前
奶糖最可爱完成签到,获得积分10
7秒前
7秒前
mojomars发布了新的文献求助10
8秒前
幽壑之潜蛟应助茶茶采纳,获得10
8秒前
9秒前
9秒前
9秒前
迅速海云完成签到,获得积分10
9秒前
sjxx发布了新的文献求助10
9秒前
9秒前
乐乐应助Rachel采纳,获得10
10秒前
10秒前
10秒前
天天快乐应助孤独的珩采纳,获得10
11秒前
帅气鹭洋发布了新的文献求助20
11秒前
12秒前
孙悦发布了新的文献求助10
12秒前
知性的绮兰完成签到,获得积分10
12秒前
12秒前
13秒前
Zzzoey完成签到,获得积分10
14秒前
14秒前
14秒前
英姑应助桂魄采纳,获得10
14秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527849
求助须知:如何正确求助?哪些是违规求助? 3107938
关于积分的说明 9287239
捐赠科研通 2805706
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716893
科研通“疑难数据库(出版商)”最低求助积分说明 709794