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基于经验模式分解的钢轨波浪弯曲不平顺提取方法
引用本文:刘秀波. 基于经验模式分解的钢轨波浪弯曲不平顺提取方法[J]. 中国铁道科学, 2006, 27(2): 26-30
作者姓名:刘秀波
作者单位:北京交通大学,土木建筑工程学院,北京,100044;铁道科学研究院,基础设施检测中心,北京,100081
摘    要:钢轨波浪弯曲不平顺隐藏在轨道不平顺中。采用小波分析和经验模式分解相结合的方法,对钢轨波浪弯曲不平顺进行识别和提取分析。利用对称双正交小波对轨检车监测到的车体垂向加速度响应和高低轨道不平顺信号进行小波变换,滤除波长1 m以下成分后,基本可以保证用经验模式分解得到的第1个固有模态函数包含全部钢轨弯曲不平顺信息。对提取得到的钢轨波浪弯曲不平顺的分析表明,不同钢轨上存在的弯曲不平顺不同,钢轨存在的波浪弯曲不平顺是波长在3 m附近变化的准周期不平顺;钢轨波浪弯曲不平顺是引起车体颤振的原因。建议在提速线路和客运专线上应限制波浪弯曲钢轨上道。

关 键 词:轨道检测  钢轨不平顺  钢轨波浪弯曲  小波分析  经验模式分解
文章编号:1001-4632(2006)02-0026-05
收稿时间:2005-11-16
修稿时间:2005-11-16

Method for Picking up Rail Wavy Irregularities Based on Empirical Mode Decomposition Method
LIU Xiu-bo. Method for Picking up Rail Wavy Irregularities Based on Empirical Mode Decomposition Method[J]. China Railway Science, 2006, 27(2): 26-30
Authors:LIU Xiu-bo
Affiliation:1. School of Civil Engineering and Architecture, Beijing Jiaotong University, Beijing; 2. Infrastructure Inspection Center, China Academy of Railway Sciences, Beijing 100044, China; 100081, China
Abstract:Rail wavy irregularities are hided in track geometry irregularities.Rail wavy irregularities can be identified and picked up by the combined method between wavelet and Empirical Mode Decomposition(EMD) method.The signals below 1 m wavelength are filtered out from vertical acceleration of car-body and surface irregularities from track inspection car by using biorthogonal wavelet analysis.The remained signals of vertical acceleration of car-body and surface irregularities are decomposed by using EMD.This method can ensure that first Internal Mode Function(IMF) gotten by EMD includes all the rail wavy irregularities.Rail wavy irregularities picked up by this method are analyzed and compared.Different type of rails have different rail wavy irregularities.Rail wavy irregularities are pseudo-period irregularities whichose wavelengths are about 3 m.The shock of car-body is caused by rail wavy irregularities.The wavy irregularities rails should be restricted on the speed-up railway line and passenger special railway line.
Keywords:Track inspection  Rail irregularity  Rail wavy irregularity  Wavelet analysis  Empirical mode decomposition
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