Analysis and prediction of high-speed train wheel wear based on SIMPACK and backpropagation neural networks
文献类型：期刊论文
| 作者 | Wang, Shuwen3; Yan, Hao3 ; Liu, Caixia3; Fan, Ning3; Liu XM(刘小明)2; Wang, Chengguo1
|
| 刊名 | EXPERT SYSTEMS
 |
| 出版日期 | 2021-11-01 |
| 卷号 | 38期号:7页码:11 |
| 关键词 | BP neural networks high-speed train SIMPACK wheel wear |
| ISSN号 | 0266-4720 |
| DOI | 10.1111/exsy.12417 |
| 通讯作者 | Wang, Shuwen(shuwenwang66@163.com) |
| 英文摘要 | As train running speeds increase, the wheel-rail interactions of high-speed trains are becoming more complicated, and predicting and monitoring wheel wear are becoming increasingly important for the safe operation of high-speed trains. Therefore, identifying the critical factors that affect the wear of wheel-rail interactions and developing novel methods to predict wheel wear are of great importance. In this work, SIMPACK is used to establish a dynamic model of a high-speed train and to investigate the normal and lateral contact forces of the wheel-rail interfaces and the wear of the wheels for a train passing through a specially designed route that consists of straight-line, smooth-curved, and circular tracks. The wheel wear is predicted by means of the Archard wear model based on the SIMPACK analysis, and the wear is validated by a backpropagation neural network (BPNN) classification based on daily measured data provided by the Beijing Railway Administration. The results from the SIMPACK dynamic simulation and the BPNN classification show that the position of a wheel in a bogie has a significant effect on the wheel wear, but the position of a carriage in a train does not have a significant effect on the wheel wear. The findings from this study are very useful for the maintenance and safe operation of high-speed trains. |
| 分类号 | 二类 |
| WOS关键词 | RAIL CONTACT ; STRESSES |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000703196300004 |
| 其他责任者 | Wang, Shuwen |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/87516]  |
| 专题 | 力学研究所_非线性力学国家重点实验室 |
| 作者单位 | 1.China Acad Railway Sci, Res Ctr, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Mech, Beijing, Peoples R China; 3.Univ Shanghai Sci & Technol, Coll Mech Engn, Shanghai 200093, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Wang, Shuwen,Yan, Hao,Liu, Caixia,et al. Analysis and prediction of high-speed train wheel wear based on SIMPACK and backpropagation neural networks[J]. EXPERT SYSTEMS,2021,38(7):11. |
| APA | Wang, Shuwen,Yan, Hao,Liu, Caixia,Fan, Ning,刘小明,&Wang, Chengguo.(2021).Analysis and prediction of high-speed train wheel wear based on SIMPACK and backpropagation neural networks.EXPERT SYSTEMS,38(7),11. |
| MLA | Wang, Shuwen,et al."Analysis and prediction of high-speed train wheel wear based on SIMPACK and backpropagation neural networks".EXPERT SYSTEMS 38.7(2021):11. |
入库方式： OAI收割
来源：力学研究所
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