首页> 外文期刊>Journal of Transportation Engineering >Research on a Short-Range Prediction Model for Track Irregularity over Small Track Lengths
【24h】

Research on a Short-Range Prediction Model for Track Irregularity over Small Track Lengths

机译:小轨道长度轨道不平顺的短程预测模型研究

获取原文
获取原文并翻译 | 示例
           

摘要

Based on analysis of some existing prediction methods and models for track irregularities, according to the characteristics of track irregularity development for China railroad, this paper has proposed a short-range prediction model (SRPM) which applies the calculus thinking and method to estimate track irregularities over small track lengths on a single-day basis using track waveform data generated by track geometry car. We applied the SRPM to make predictions for track irregularities of many unit track sections of the up-going tacks of Beijing-Shanghai Railway Line (Jing-Hu Line) using the past two-year waveform data of this railway line. To confirm the efficiency of the SRPM, we compared the actual and estimated irregularities in both time and railway distance dimensions. The comparison shows that the SRPM can accurately predict track irregularities of unit track sections along Jing-Hu Railway Line on each day within a future short period.
机译:在分析现有轨道不平顺预测方法和模型的基础上,结合中国铁路轨道不平顺发展的特点,提出了一种基于微积分思想和方法估算轨道不平顺的短程预测模型(SRPM)。使用轨道几何车生成的轨道波形数据,在一天的时间内就可以在较小的轨道长度上运行。我们使用SRPM使用该铁路线过去两年的波形数据来预测京沪铁路线(京沪线)上行大头钉的许多单位轨道段的轨道不规则性。为了确认SRPM的效率,我们比较了时间和铁路距离尺寸中的实际和估计的不规则性。对比表明,SRPM可以在未来的短时间内准确预测京沪铁路沿线各单元区段的轨道不平顺度。

著录项

  • 来源
    《Journal of Transportation Engineering》 |2010年第12期|p.1085-1091|共7页
  • 作者单位

    Dept. of Transportation Information Management, School of Traffic and Transportation, Beijing Jiaotong Univ., No. 3 of Shangyuan Residence Haidian District, Beijing 100044, People's Republic of China;

    rnState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong Univ., Beijing 100044, People's Republic of China;

    rnDept. of Transportation Information Management, School of Traffic and Transportation, Beijing Jiaotong Univ.,Beijing 100044, People's Republic of China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    railroad; track irregularity; track geometry data; prediction; model;

    机译:铁路;跟踪违规行为;跟踪几何数据;预测;模型;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号