基于参数优化VMD和SPWVD的轨道波磨辨识方法

张海强; 王楠; 刘松; 李柄奎

基于参数优化VMD和SPWVD的轨道波磨辨识方法

1. 广州地铁集团有限公司运营事业总部, 广州 510335;
2. 南京理工大学自动化学院, 南京 210094;
3. 中国移动江苏公司扬州分公司, 扬州 225000

基金项目:

国家重点研发计划项目(2017YFB1201202)

详细信息

作者简介:
张海强,工程师;王楠,在读硕士研究生。

中图分类号: U213.42;TP39
计量
- 文章访问数: 85
- HTML全文浏览量: 1
- PDF下载量: 9
出版历程
- 收稿日期: 2020-01-11

Rail corrugation identification method based on parameter optimization VMD and SPWVD

1. Operation Headquarters, Guangzhou Metro Group Co. Ltd., Guangzhou 510335, China;
2. School of Automation, Nanjing University of Science&Technology, Nanjing 210094, China;
3. Yangzhou Branch, China Mobile Jiangsu Company, Yangzhou 225000, China

摘要

摘要: 为了有效检测轨道波磨故障,提出一种基于参数优化变分模态分解(VMD,Variable Mode Decomposition)和平滑伪维格纳分布(SPWVD,Smooth Pseudo Wigner Ville Distribution)的轨道波磨辨识方法。采用变步长最小均方(VSSLMS,Variable Step Size Least Mean Square)算法对列车轴箱振动加速度原始信号滤波;对滤波后的信号进行变分模态分解,将分解信号包络熵作为轨道波磨辨识的指标;采用平滑伪维格纳分布对分解后的信号进行时频分析,确定波磨发生的位置及波长;通过仿真信号与实例验证方法的有效性。验证结果表明,该方法可提高轨道波磨辨识的准确性,辅助轨道维修和养护。
- 轨道波磨 /
- 识别方法 /
- 变步长最小均方(VSSLMS) /
- 参数优化 /
- 变分模态分解(VMD) /
- 平滑伪维格纳分布(SPWVD)
Abstract: In order to detect the rail corrugation fault effectively, this paper proposed a method of rail corrugation identification based on parameter optimization Variational Mode Decomposition (VMD) and Smooth Pseudo Wigner Ville Distribution (SPWVD). The paper used the VSSLMS (Variable Step Size Least Mean Square) algorithm to filter the original acceleration signal of train axle box vibration, decomposed the filtered signal into variational mode, took the envelope entropy of the decomposed signal as the index of the identification of the rail corrugation, used the SPWVD to carry out the time-frequency analysis of decomposed signal, and determine the location and wavelength of the corrugation. The effectiveness of the method was verified by simulation signals and examples. The results show that the method can be used to improve the accuracy of rail corrugation identification and assist rail maintenance.
- rail corrugation /
- identification method /
- Variable Step Size Least Mean Square(VSSLMS) /
- parameter optimization /
- Variable Mode Decomposition(VMD) /
- Smooth Pseudo Wigner-Ville-Distribution(SPWVD)

HTML全文

参考文献(18)

[1]	Li Y, Liu H, Ma Z, et al. Rail Corrugation Broadband Measurement Based on Combination-Chord Model and LS[J]. IEEE Transactions on Instrumentation & Measurement, 2018, 67(4):938-949.
[2]	殷华,朱洪涛. 基于ZFFT的轨道波磨高精度弦测算法研究[J]. 铁道科学与工程学报, 2017, 14(9):1851-1858.
[3]	刘力,赵晓男,陈光雄. 基于惯性基准法地铁钢轨波磨检测方法研究[J]. 机械, 2018, 45(8):30-34.
[4]	余振华. 惯性位移法轨道短波不平顺测量系统设计[D]. 南昌:南昌大学, 2015.
[5]	孙锐. 基于车辆动态响应的高速铁路钢轨波磨仿真与分析[D]. 北京:北京建筑大学, 2018.
[6]	张厚贵. 北京地铁钢轨波磨的机理及整治方案研究[D]. 北京:北京交通大学, 2015.
[7]	Oyarzabal O, J. Gómez, J. Santamaría, et al. Dynamic optimization of track components to minimize rail corrugation[J]. Journal of Sound & Vibration, 2009, 319(3):904-917.
[8]	Valehrach J, Guziur P, Riha T, et al. Assessment of rail longpitch corrugation[C]//IOP Conference Series:Materials Science and Engineering, Volume 236, Building up Efficient and Sustainable Transport Infrastructure 2017(BESTInfra2017). Prague,Czeh Republic:IOP Publishing Ltd.,2017.
[9]	Kurzeck B. Combined friction induced oscillations of wheelset and track during the curving of metros and their influence on corrugation[J]. Wear, 2011, 271(1):299-310.
[10]	Zhai G, He Y, Wei X. Detection technique research of rail corrugation in urban rail transit[J]. Journal of Beijing Jiaotong University, 2017, 41(4):77-84, 90.
[11]	黄文. 基于小波包能量熵的轨道波磨在线检测方法研究[D]. 南京:南京理工大学, 2017.
[12]	王乃珍,王福田. 基于灰色区间预测模型的轨道不平顺状态预测[J]. 铁路计算机应用, 2015, 24(1):1-3 , 7.
[13]	李坤合,芮义斌. 一种改进的外辐射源雷达直达波对消算法[J]. 电讯技术, 2019, 59(11):1275-1280.
[14]	Bismor D, Czyz K, Ogonowski Z. Review and Comparison of Variable Step-Size LMS Algorithms[J]. International Journal of Acoustics and Vibration, 2016, 21(1):24-39.
[15]	Dragomiretskiy K, Zosso D. Variational Mode Decomposition[J]. IEEE Transactions on Signal Processing, 2014, 62(3):531-544.
[16]	李肖,冯志鹏. 基于变分模式分解的行星齿轮箱齿轮组合故障频率解调分析[J]. 振动与冲击, 2020, 39(3):38-45 , 51.
[17]	郝国成,谈帆,程卓,等. 强鲁棒性和高锐化聚集度的BGabor-NSPWVD时频分析算法[J]. 自动化学报, 2019, 45(3):566-576.
[18]	Kalra M, Kumar S, Das B. Target Detection Using Smooth Pseudo Wigner-Ville Distribution[C]//2018 IEEE Recent Advances in Intelligent Computational Systems. Thiruvananthapuram, India:IEEE Press, 2018.

施引文献(5)

期刊类型引用(2)

1.	史永胜，容璇. 基于特征匹配的飞机外表面缺陷差异检测研究. 航空计算技术. 2023(01): 6-10 . 百度学术
2.	杨凯，张淼，祁苗苗. 铁路车辆监测图像识别模型训练及验证平台研究. 铁路计算机应用. 2023(06): 26-30 . 本站查看