Wheel Wear Prediction of High-Speed Train Using NAR and BP Neural Networks

IMECH-IR > 非线性力学国家重点实验室

	Wheel Wear Prediction of High-Speed Train Using NAR and BP Neural Networks
	Fan N; Wang SW; Liu CX; Liu XM(刘小明)
会议录名称	2017 IEEE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA)
	2017
会议名称	EEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
会议日期	JUN 21-23, 2017
会议地点	Exeter, ENGLAND
摘要	In this paper, the field measured wheel wear data of high-speed trains are studied by variance analysis, and prediction models are developed using NAR and BP neural networks. The results show that the wheel position has a significant effect on the wheel wear, and the position of the carriage has little influence on the wheel wear. The NAR neural network can be used to predict the dynamic change of wheel diameter and therefore to predict the wheel wear of high-speed trains. The wheel diameter data are classified and the range of wheel wear can be predicted by means of training the BP neural network.
关键词	Big Data Wheel Wear Variance Analysis Nar Neural Network Prediction
WOS记录号	WOS:000426972400018
资助信息	The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (No. 51275126).
ISBN号	978-1-5386-3066-2
URL	查看原文
收录类别	CPCI-S ; EI
语种	英语
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	会议论文
条目标识符	http://dspace.imech.ac.cn/handle/311007/75556
专题	非线性力学国家重点实验室
推荐引用方式 GB/T 7714	Fan N,Wang SW,Liu CX,et al. Wheel Wear Prediction of High-Speed Train Using NAR and BP Neural Networks[C]2017 IEEE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA),2017.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
CPCI2017011.pdf（753KB）	会议论文		开放获取	CC BY-NC-SA	浏览下载