基于轴箱振动加速度小波包分解的高速列车车轮多边形特征识别

doi:10.3901/JME.2025.14.223

机械工程学报 ›› 2025, Vol. 61 ›› Issue (14): 223-232.doi: 10.3901/JME.2025.14.223

• 运载工程 • 上一篇

扫码分享

基于轴箱振动加速度小波包分解的高速列车车轮多边形特征识别

李新一^1,2, 刘金安¹, 肖新标³, 黄振鑫³, 刘晓龙³, 金学松³

1. 中国中车长春轨道客车股份有限公司长春 130113;
2. 西南交通大学机械工程学院成都 610031;
3. 西南交通大学轨道交通运载系统全国重点实验室成都 610031

收稿日期:2024-12-26 修回日期:2025-03-28 发布日期:2025-08-25
作者简介:李新一，男，1987年出生。主要研究方向为轨道交通减振降噪。E-mail:lixinyi0906@163.com;肖新标(通信作者)，男，1978年出生，博士，研究员，博士研究生导师。主要研究方向为轨道交通减振降噪。E-mail:xinbiaoxiao@163.com
基金资助:
国家自然科学基金资助项目(11202128)。

Wheel Polygon Feature Recognition of High-speed Trains Based on Axle-box Acceleration and Wavelet Packet Decomposition

LI Xinyi^1,2, LIU Jinan¹, XIAO Xinbiao³, HUANG Zhenxin³, LIU Xiaolong³, JIN Xuesong³

1. CRRC Changchun Railway Vehicles Co., Ltd., Changchun 130113;
2. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031;
3. State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031

Received:2024-12-26 Revised:2025-03-28 Published:2025-08-25

摘要/Abstract

摘要： 高效的车轮多边形检测对于指导高速列车车轮镟修具有重要意义，现有研究在识别多边形幅值上还不够精确。提出了基于轴箱振动加速度小波包分解的车轮多边形特征动态检测方法，首先建立高速列车车辆-轨道耦合动力学模型，计算了不同阶次、不同幅值车轮多边形状态下的轴箱振动响应；利用小波包分解对轴箱振动信号进行时频分析，以小波包节点能量级作为量化多边形幅值的指标；然后使用克里金插值建立了车轮多边形特征与轴箱振动特征之间的映射关系；最后通过实际测试对该方法进行了验证，预测结果与测试结果相比平均误差为10.28%，对于多边形磨耗较严重的车轮，其显著阶次预测平均误差仅为5.68%。一定程度上弥补了动态检测方法在多边形幅值量化方面的不足，为高速列车车轮多边形特征检测提出了新的技术途径，具有良好的工程价值。

关键词: 高速列车, 多边形磨耗, 轴箱振动加速度, 小波包分解, 特征识别, 车辆-轨道耦合动力学

Abstract: Efficient wheel polygon detection is of great significance for wheel re-profiling of high-speed trains. A dynamic detection method of wheel polygon features based on wavelet packet decomposition(WPD) of axle-box acceleration is proposed. Firstly, the vehicle-track coupled dynamics model of high-speed train is established, and the axle-box accelerations caused by wheel polygon with different orders and amplitudes are calculated; WPD is used to conduct time-frequency analysis of axle-box accelerations, and the WPD node energy levels is taken as an indicator to quantify the amplitude of wheel polygons; then the mapping between the wheel polygon features and axle-box accelerations features is established by Kriging interpolation model; Finally, the method is verified by direct measurement, the average error of estimated results compared with test results is 10.28%, and for wheels with more serious polygon wear, the average error of estimated of significant order is only 5.68%. To a certain extent, it makes up for the shortage of dynamic detection methods in polygon amplitude quantification, and proposes a new technical way for high-speed train wheel polygon feature detection, which has good engineering value.

Key words: high-speed train, wheel polygonal wear, axle-box acceleration, wavelet packet decomposition, feature recognition, vehicle-track coupled dynamics

中图分类号:

U271

李新一, 刘金安, 肖新标, 黄振鑫, 刘晓龙, 金学松. 基于轴箱振动加速度小波包分解的高速列车车轮多边形特征识别[J]. 机械工程学报, 2025, 61(14): 223-232.

LI Xinyi, LIU Jinan, XIAO Xinbiao, HUANG Zhenxin, LIU Xiaolong, JIN Xuesong. Wheel Polygon Feature Recognition of High-speed Trains Based on Axle-box Acceleration and Wavelet Packet Decomposition[J]. Journal of Mechanical Engineering, 2025, 61(14): 223-232.

参考文献

[1] TAO G，WEN Z，JIN X，et al. Polygonisation of railway wheels:A critical review[J]. Railway Engineering Science，2020，28(4):317-345.
[2] BARKE D W，CHIU W K. A review of the effects of out-of-round wheels on track and vehicle components[J]. Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit，2005，219(3):151-175.
[3] WU P，LI G，WU X，et al. Wheel polygonalization- induced axle box vibrations and bolt self-loosening for high speed train[C]//Proceedings of the 25th International Symposium on Dynamics of Vehicles on Roads and Tracks(IAVSD 2017)，14-18 August 2017，Rockhampton，Queensland，Australia:1191-1196.
[4] WANG Z，MEI G，ZHANG W，et al. Effects of polygonal wear of wheels on the dynamic performance of the gearbox housing of a high speed train[J]. Proceedings of the Institution of Mechanical Engineers Part F-Journal of Rail and Rapid Transit，2018，232(6):1852-1863
[5] XIAO J，HU H，YAN Z，et al. The influence of wheel/rail vibration on the damage of rail fastening system of high speed railway in China[C]//Proceedings of 11th international conference on contact mechanics and wear of rail/wheel system (CM2018)，24-27 September 2018，Delft，The Netherlands:1122-1127.
[6] ZHANG J，HAN G，XIAO X，et al. Influence of wheel polygonal wear on interior noise of high-speed trains[J]. Journal of Zhejiang University-Science A(Applied Physics & Engineering)，2014，15(12):1002-1018.
[7] 周陆，孙祥涛，倪一清. 高速列车轮轨检测和监测方法综述[J]. 电力机车与城轨车辆，2021，44(1):1-10. ZHOU Lu，SUN Xiangtao，NI Yiqing. Review of inspection and monitoring methods of high speed train wheels and rails[J]. Electric Locomotives & Mass Transit Vehicles，2021，44(1):1-10.
[8] SECO M，SANCHEZ E，VINOLAS J. Monitoring wheel defects on a metro line:System description，analysis and results[C]// Tenth International Conference on Computer System Design and Operation in the Railway and other Transit Systems，10-12 July 2006，Prague，Czech Republic:973-982.
[9] 丁建明，林建辉，易彩，等. 车轮不圆顺动态检测的时频特征圈内定位比较法[J]. 振动与冲击，2013，32(19):39-43. DING Jianming，LIN Jianhui，YI Cai，et al. Dynamic detection of out-of-round wheels using a comparison of time-frequency feature locatings[J]. Journal of Vibration and Shock，2013，32(19):39-43.
[10] 李奕璠，刘建新，李忠继. 基于Hilbert-Huang变换的列车车轮失圆故障诊断[J]. 振动.测试与诊断，2016，36(4):734-739，812-813. LI Yifan，LIU Jianxin，LI Zhongji. The fault diagnosis method of railway out-of-round wheels using Hilbert- Huang transform[J]. Journal of Vibration，Measurement and Diagnosis，2016，36(4):734-739，812-813.
[11] 陈博，陈光雄. 基于MEEMD和GA-SVM的列车车轮多边形故障识别方法[J]. 噪声与振动控制，2018，38(3):157-161，197. CHEN Bo，CHEN Guangxiong. Fault diagnosis method of wheel polygonization of trains based on MEEMD and GA-SVM[J]. Noise and Vibration Control，2018，38(3):157-161，197.
[12] SONG Y，LIANG L，DU Y，et al. Railway polygonized wheel detection based on numerical time-frequency analysis of axle-box acceleration[J]. Applied Sciences，2020，10(5):1613.
[13] SUN Q，CHEN C，KEMP A H，et al. An on-board detection framework for polygon wear of railway wheel based on vibration acceleration of axle-box[J]. Mechanical Systems and Signal Processing，2021，153:107540.
[14] WANG Q，XIAO Z，ZHOU J，et al. A new DFT-based dynamic detection framework for polygonal wear state of railway wheel[J]. Vehicle System Dynamics，2022，61(8):2051-2073.
[15] 翟婉明. 车辆—轨道耦合动力学(上册)[M]. 4版. 北京:科学出版社，2015. ZHAI Wanming. Vehicle-track coupled dynamics (Volume1)[M]. 4th ed. Beijing:Science Press，2015.
[16] 秦斌. 基于小波包和支持向量机的滚动轴承故障诊断方法研究[D]. 北京:北京理工大学，2018. QIN Bin. Research on fault diagnosis method of rolling bearing based on wavelet packet and support vector machine[D]. Beijing:Beijing Institute of Technology，2018.
[17] LIU X，HAN J，XU H，et al. An indirect method for rail corrugation measurement based on numerical models and wavelet packet decomposition[J]. Measurement，2022191:110726.
[18] 金学松，吴越，梁树林，等. 高速列车车轮多边形磨耗、机理、影响和对策分析[J]. 机械工程学报，2020，56(16):118-136. JIN Xuesong，WU Yue，LIANG Shulin，et al. Characteristics，mechanism，influences and countermeasures of polygonal wear of high-speed train wheels[J]. Journal of Mechanical Engineering，2020，56(16):118-136.

基于轴箱振动加速度小波包分解的高速列车车轮多边形特征识别

Wheel Polygon Feature Recognition of High-speed Trains Based on Axle-box Acceleration and Wavelet Packet Decomposition

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	王高见, 叶延洪, 康丹丹, 邓德安. 焊接热输入对高速列车转向架耐候钢焊缝金属微观组织、力学性能及腐蚀行为的影响[J]. 机械工程学报, 2025, 61(8): 148-158.
[2]	盛旭高, 于梦阁, 戴志远, 张骞. 雨滴粒径分布对高速列车气动性能的影响[J]. 机械工程学报, 2025, 61(6): 238-248.
[3]	刘文朋, 杨绍普, 刘永强, 顾晓辉, 王久健. 轮轨激励下高速列车轴箱轴承故障诊断方法研究[J]. 机械工程学报, 2025, 61(6): 249-259.
[4]	杨逸凡, 陈是扦, 王开云, 肖绯雄, 马呈祥. 基于模态共振原理的重载机车一系钢弹簧结构优化研究[J]. 机械工程学报, 2025, 61(2): 247-256.
[5]	杨云帆, 王瑞晨, 常宇健, 陈美, 刘鹏飞. 车轮镟修对重载机车车轮非圆化磨耗消除及演化发展影响研究[J]. 机械工程学报, 2025, 61(14): 184-196.
[6]	刘志强, 石怀龙, 刘沿修. 高速车辆低频晃动的主动控制方法及适应性研究[J]. 机械工程学报, 2025, 61(12): 226-240.
[7]	盛旭高, 于梦阁, 李美香, 刘加利. 强降雨环境高速列车气流流场及雨场的耦合机理[J]. 机械工程学报, 2025, 61(12): 241-250.
[8]	杨林川, 楚明, 王权, 王志伟, 莫继良. 轨道不平顺激励下高速列车制动系统动态响应[J]. 机械工程学报, 2025, 61(12): 281-292.
[9]	周仲荣. 关于高速列车超级制动研究的思考[J]. 机械工程学报, 2025, 61(11): 208-215.
[10]	胡彦霖, 凌亮, 张恒, 王开云. 强风环境下山区铁路隧道出口的高速列车运行安全性研究[J]. 机械工程学报, 2025, 61(10): 349-358.
[11]	楚明, 杨林川, 王志伟, 江志伟, 王权, 莫继良. 曲线几何参数及制动工况对列车轴箱轴承动态特性影响研究[J]. 机械工程学报, 2025, 61(1): 187-198.
[12]	柴依扬, 张乐乐, 窦伟元, 张海峰. 基于并行NSGA-III算法的高速列车车体侧墙结构高维多目标优化[J]. 机械工程学报, 2024, 60(6): 321-333.
[13]	陈清华, 杨云帆, 閤鑫, 凌亮, 王开云. 基于电磁力作用的地铁列车防滑控制研究[J]. 机械工程学报, 2024, 60(6): 334-341.
[14]	周素霞, 巴馨悦, 王君艳, 李光, 曲直. 鳞片仿生制动盘散热性能研究[J]. 机械工程学报, 2024, 60(6): 354-362.
[15]	项载毓, 莫继良, 贺德强, 朱松, 翟财周, 杜利清. 基于三明治阻尼结构的高速列车制动摩擦振动噪声抑制[J]. 机械工程学报, 2024, 60(5): 196-208.