Analysis and prediction of high-speed train wheel wear based on SIMPACK and backpropagation neural networks

doi:10.1111/exsy.12417

IMECH-IR > 非线性力学国家重点实验室

	Analysis and prediction of high-speed train wheel wear based on SIMPACK and backpropagation neural networks
	Wang, Shuwen 1; Yan, Hao1 ; Liu, Caixia 1; Fan, Ning 1; Liu XM(刘小明)2 ; Wang, Chengguo 3
通讯作者	Wang, Shuwen(shuwenwang66@163.com)
发表期刊	EXPERT SYSTEMS
	2021-11-01
卷号	38 期号:7 页码:11
ISSN	0266-4720
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.
关键词	BP neural networks high-speed train SIMPACK wheel wear
DOI	10.1111/exsy.12417
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000703196300004
关键词[WOS]	RAIL CONTACT ; STRESSES
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
论文分区	二类
力学所作者排名	3+
RpAuthor	Wang, Shuwen
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://dspace.imech.ac.cn/handle/311007/87517
专题	非线性力学国家重点实验室
作者单位	1.Univ Shanghai Sci & Technol, Coll Mech Engn, Shanghai 200093, Peoples R China; 2.Chinese Acad Sci, Inst Mech, Beijing, Peoples R China; 3.China Acad Railway Sci, Res Ctr, Beijing, 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.

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