文章基本信息

标题：A neural network driving curve generation method for the heavy-haul train
本地全文：下载
作者：Youneng Huang ; Litian Tan ; Lei Chen 等
期刊名称：Advances in Mechanical Engineering
印刷版ISSN：1687-8140
电子版ISSN：1687-8140
出版年度：2016
卷号：8
期号：5
DOI：10.1177/1687814016647883
语种：English
出版社：Sage Publications Ltd.
摘要：The heavy-haul train has a series of characteristics, such as the locomotive traction properties, the longer length of train, and the nonlinear train pipe pressure during train braking. When the train is running on a continuous long and steep downgrade railway line, the safety of the train is ensured by cycle braking, which puts high demands on the driving skills of the driver. In this article, a driving curve generation method for the heavy-haul train based on a neural network is proposed. First, in order to describe the nonlinear characteristics of train braking, the neural network model is constructed and trained by practical driving data. In the neural network model, various nonlinear neurons are interconnected to work for information processing and transmission. The target value of train braking pressure reduction and release time is achieved by modeling the braking process. The equation of train motion is computed to obtain the driving curve. Finally, in four typical operation scenarios, comparing the curve data generated by the method with corresponding practical data of the Shuohuang heavy-haul railway line, the results show that the method is effective.
关键词：Heavy-haul train; neural network; driving curve; modeling; operation scenarios