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 | |
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 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论