Research on Improving the Tribological Properties of Bearings under Cryogenic Conditions

Author:

Wang Bin,Liu Zhuanghua,Liu Dongchang,Tian Zhen,Xie Saipeng,Wang Xiaodong,Dai Jun,Bu Chunguang

Abstract

Abstract Bearings, as one of the most central components of rotating equipment, are widely used both in servo steering gear, aerospace and other fields. However, for extremely cryogenic conditions, the life of bearings is low, so it is necessary to carry out the tribological design of bearings to improve its cryogenic performance. In this paper, four kinds of optimized and improved plain bearings are designed. The tribological tests of these four bearings under extreme cryogenic working conditions were carried out using the developed bearing simulation test rig. The results show that under the same load and rotational speed conditions, the preparation of micro-weave structure on the surface of the shaft tile or the preparation of composite coating on the surface of the journal can improve the friction and wear performance of the bearings to a certain extent. When both methods are used at the same time, the friction reduction and anti-friction wear effect of the sliding bearing is better. This study not only provides theoretical guidance and technical support for improving the cryogenic tribological performance of bearings, but also has important practical significance for the future development of rotating equipment in the low-temperature field.

Publisher

IOP Publishing

Subject

Computer Science Applications,History,Education

Reference14 articles.

1. A review on cryogenic machining of super alloys used in aerospace industry;Kale;Procedia Manufacturing,2017

2. Performance evaluation of deep cryogenic processed carbide inserts during dry turning of Nimonic 90 aerospace grade alloy;Ghosh;Tribology international,2017

3. Improving Tribological Behaviors of Invar 36 Alloy under Extremely Cryogenic and Dry Conditions Through Surface Micro-Texturing;Wang;Journal of Physics: Conference Series,2023

4. Artificial intelligence for fault diagnosis of rotating machinery: A review;Liu;Mechanical Systems and Signal Processing,2018

5. A novel deep autoencoder feature learning method for rotating machinery fault diagnosis;Shao;Mechanical Systems and Signal Processing,2017

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3