基于改进的Hilbert-Huang高速铁路轨道短波不平顺识别研究

周素霞1, 2, 纪泽1, 2, 曲直3, 靳雨松1, 2

振动与冲击 ›› 2025, Vol. 44 ›› Issue (10) : 241-249.

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振动与冲击 ›› 2025, Vol. 44 ›› Issue (10) : 241-249.
交通运输科学

基于改进的Hilbert-Huang高速铁路轨道短波不平顺识别研究

  • 周素霞1,2,纪泽*1,2,曲直3,靳雨松1,2
作者信息 +

Identification of short wave irregularities in high speed railway tracks based on improved techniques Hilbert-Huang transform

  • ZHOU Suxia1,2, JI Ze*1,2, QU Zhi3, JIN Yusong1,2
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文章历史 +

摘要

为准确可靠识别高速铁路轨道上的短波不平顺特征,针对Hilbert-Huang变换方法中的模态混叠和端点效应问题,提出了改进的Hilbert-Huang算法。运用修正Akima方法,优化分段三次Hermite插值法,对构建的调幅调频信号区间重新赋予权重,有效避免了包络曲线的过冲和欠冲问题并保持光滑性;基于边界局部特征尺度延拓法,对构建的复合信号进行处理,抑制了端点效应中的发散现象。采用改进的Hilbert-Huang算法与EEMD算法进行对比分析,结果表明,改进的Hilbert-Huang算法具有更好的信号分离效果。基于改进的Hilbert-Huang算法对高速铁路轨道短波不平顺实测信号进行分解,应用边际谱和Hilbert谱对IMF分量进行分析,得到的波长与位置信息与实际测量结果吻合度较高。

Abstract

In order to accurately and reliably identify short-wave irregularities on high-speed railway tracks, an improved Hilbert-Huang algorithm is proposed to solve the problem of modal aliasing and endpoint effects in the Hilbert-Huang transform method. The modified Akima method is used to optimize the piecewise cubic Hermite interpolation method, and re-weight the interval of the constructed AM and FM signal, which effectively avoids the overshoot and undershoot problems of the envelope curve and maintains smoothness; based on the local characteristic scale extension method of the boundary, the constructed composite signal is processed to suppress divergence in endpoint effects. The improved Hilbert-Huang algorithm is compared with EEMD algorithm. The results show that the improved Hilbert-Huang algorithm has better signal separation effect. Based on the improved Hilbert-Huang algorithm, the measured signal of short-wave irregularities on high-speed railway tracks is decomposed, and the marginal spectrum and Hilbert spectrum are used to analyze the IMF component. The obtained wavelength and position information are in good agreement with the actual measurement results. 

关键词

轨道短波不平顺 / Hilbert-Huang变换 / 模态混叠 / 包络曲线

Key words

Track shortwave roughness / Hilbert Huang Transform / mode mixing / Envelope curve 

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周素霞1, 2, 纪泽1, 2, 曲直3, 靳雨松1, 2. 基于改进的Hilbert-Huang高速铁路轨道短波不平顺识别研究[J]. 振动与冲击, 2025, 44(10): 241-249
ZHOU Suxia1, 2, JI Ze1, 2, QU Zhi3, JIN Yusong1, 2. Identification of short wave irregularities in high speed railway tracks based on improved techniques Hilbert-Huang transform[J]. Journal of Vibration and Shock, 2025, 44(10): 241-249

参考文献

[1] 刘金朝,徐晓迪,牛留斌,等.高速铁路轨道短波健康状态动态诊断模型和方法[J].铁道学报,2021,43(10):69-74.
Liu Jinchao, Xu Xiaodi, Niu Liubin, et al. Dynamic diagnosis model and method for shortwave health status of high-speed railway tracks [J]. Journal of Railway, 2021, 43 (10): 69-74
[2] Chen X, Chai X, Cao X. The time-frequency analysis of the train Axle box acceleration signals using empirical mode decomposition[J].[2024-04-09].
[3] Liu N, Gao J, Jiang X, et al. Seismic Time–Frequency Analysis via STFT-Based Concentration of Frequency and Time[J]. IEEE Geoscience and Remote Sensing Letters,2017, 14(1): 127-131
[4] Ne. H, Sr. L, Mlc. W, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society. Mathematical, physical and engineering sciences,1998(1971):454.
[5] 毛炜,金荣洪,耿军平,等.一种基于改进Hilbert-Huang变换的非平稳信号时频分析法及其应用[J].上海交通大学学报,2006,(05):724-729.
Mao Wei, Jin Ronghong, Geng Junping, et al. A non-stationary signal time-frequency analysis method based on improved Hilbert Huang transform and its application [J]. Journal of Shanghai Jiao Tong University, 2006, (05): 724-729
[6] Hsin-Chu,Tsai,Chung-Yue,et al.Railway track inspection based on the vibration responseto a scheduled train and the Hilbert–Huang transform[J].Proceedings of the Institution ofMechanical Engineers Part F Journal of Rail & Rapid Transit, 2015.
[7] 曹西宁,柴晓冬,郑树彬.基于 Hilbert-Huang 变换的轨道车辆轴箱加速度信号分析[J].仪表技术与传感器,2015,(03):92-95.
Cao Xining, Chai Xiaodong, Zheng Shubin. Analysis of Axle Box Acceleration Signal of Rail Vehicles Based on Hilbert Huang Transform [J]. Instrument Technology and Sensors, 2015, (03): 92-95
[8] 江桦.基于EMD算法的轮轨表面缺陷检测研究[D].西南交通大学,2020.
Jiang Hua. Research on Wheel Rail Surface Defect Detection Based on EMD Algorithm [D]. Southwest Jiaotong University, 2020
[9] Tsunashima H , Hirose R .Condition monitoring of railway track from car-body vibrationusing time–frequency analysis[J].Vehicle System Dynamics[2024-04-09].
[10] 范文健,毛万鑫,吴疆.车辆加速度信号的 EMD 和 IIR 滤波联合降噪方法[J].振动与冲击,2021,40(20):307-312.
Fan Wenjian, Mao Wanxin, Wu Jiang. Joint denoising method of EMD and IIR filtering for vehicle acceleration signals [J]. Vibration and Shock, 2021, 40 (20): 307-312
[11] Ne. H, Sr. L, Mlc. W, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J].Proceedings of the Royal Society. Mathematical, physical and engineering sciences, 1998(1971):454.
[12] 张义平.爆破震动信号的HHT分析与应用研究[D].中南大学,2006.
Zhang Yiping. Research on HHT Analysis and Application of Blasting Vibration Signals [D]. Central South University, 2006
[13] Wang G , Chen X Y , Qiao F L ,et al.ON INTRINSIC MODE FUNCTION[J].Advances in Adaptive Data Analysis, 2010, 02(03):1000054-.
[14] 霍延.基于EEMD 与改进EMD的脑电信号的特征提取方法[D].南京邮电大学,2020.
Huo Yan. Feature Extraction Method for EEG Signals Based on EEMD and Improved EMD [D]. Nanjing University of Posts and Telecommunications, 2020
[15] Akima H .A Method of Bivariate Interpolation and Smooth Surface Fitting Based on Local Procedures[J].Communications of the ACM, 1974, 17(1):18-20.
[16] Akima,Hiroshi.A New Method of Interpolation and Smooth Curve Fitting Based on LocalProcedures[J].Journal of the Acm, 1970, 17(4):589-602.
[17] 乔金.基于EMD和SVD的地震噪声压制方法研究[D].西安石油大学,2023.
Qiao Jin. Research on Seismic Noise Suppression Method Based on EMD and SVD [D]. Xi'an University of Petroleum, 2023
[18] Wu J , Wu L , Sun M ,et al.Application of Boundary Local Feature Scale Adaptive Matching Extension EMD Endpoint Effect Suppression Method in Blasting Seismic Wave Signal Processing[J].Hindawi Limited, 2021.
[19] 黄诚惕.希尔伯特—黄变换及其应用研究[D].西南交通大学,2006.
Huang Chengti. Hilbert Huang Transform and Its Application Research [D]. Southwest Jiaotong University, 2006

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