Monitoring and modelling of false brinelling for railway bearings

方位(导航) 振动 轮廓仪 材料科学 流离失所(心理学) 结构工程 有限元法 打滑(空气动力学) 火车 声学 机械 计算机科学 工程类 复合材料 物理 航空航天工程 人工智能 表面粗糙度 地图学 心理学 地理 心理治疗师
作者
Khosro Fallahnezhad,Sheng Liu,Osama Brinji,Malcolm Marker,Paul A. Meehan
出处
期刊:Wear [Elsevier BV]
卷期号:424-425: 151-164 被引量:32
标识
DOI:10.1016/j.wear.2019.02.004
摘要

An adaptive finite element model was developed to predict false brinelling in a cylindrical bearing, during the transportation of new trains and then compared with experimental measurements. The model was developed, based on the Archard wear equation, using ABAQUS and developing an ABAQUS UMESHMOTION code. A false brinelling monitoring system was designed and installed to record the vibration and rotational motion of the bearing, during the train's road and sea transportations and were used as inputs for the FE model. A set of laboratory experiments were conducted to determine wear and friction coefficients and the threshold energy for the bearing that were used in the simulation process. To compare the FE results with a real case, a profilometry measurement of false brinelling marks in a damaged bearing was performed. According to the FE wear profile results, rotational displacement of the bearing is the most likely cause for false brinelling during transportation. Due to the wear energy being below the threshold, it was predicted that no false brinelling occurred due to lateral and axial vibrations at the roller. The existence of the partial slip area, in the contact, causes the development of W shape wear marks that was seen in the profilometry measurement of the damaged sample.

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
研友_8op0RL完成签到,获得积分10
1秒前
sakura完成签到,获得积分10
2秒前
2秒前
boblee发布了新的文献求助200
3秒前
盘菜应助宇文天思采纳,获得10
3秒前
4秒前
hzp完成签到,获得积分10
5秒前
充电宝应助热情曲奇采纳,获得10
6秒前
7秒前
7秒前
7秒前
biackgao发布了新的文献求助10
8秒前
8秒前
8秒前
初景发布了新的文献求助10
9秒前
9秒前
10秒前
蔺铁身发布了新的文献求助10
11秒前
11秒前
kk发布了新的文献求助10
12秒前
123发布了新的文献求助10
12秒前
岸部发布了新的文献求助10
12秒前
深情惜梦发布了新的文献求助10
13秒前
dxp发布了新的文献求助10
14秒前
15秒前
扶绥发布了新的文献求助10
15秒前
红彤彤完成签到,获得积分20
15秒前
15秒前
Hsy完成签到 ,获得积分10
16秒前
wyg_gzed发布了新的文献求助30
16秒前
充电宝应助蔺铁身采纳,获得10
17秒前
简单的语风完成签到,获得积分10
18秒前
xsss完成签到 ,获得积分10
18秒前
云御风行发布了新的文献求助10
18秒前
无花果应助尼克采纳,获得10
19秒前
yangsun完成签到,获得积分10
19秒前
sssttt关注了科研通微信公众号
19秒前
20秒前
21秒前
21秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Pediatric Dermoscopy Trichoscopy & Onychoscopy 2030
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7576346
求助须知:如何正确求助?哪些是违规求助? 9155933
关于积分的说明 19587431
捐赠科研通 7160381
什么是DOI,文献DOI怎么找? 3264993
关于科研通互助平台的介绍 2430152
邀请新用户注册赠送积分活动 2255622