轮轨激励下高速列车轴箱轴承故障诊断方法研究  

Research on Fault Diagnosis Method of Axle-box Bearing of High-speed Train under Wheel-rail excitation

作　　者：刘文朋 杨绍普[1] 刘永强 顾晓辉[1] 王久健[1] LIU Wenpeng;YANG Shaopu;LIU Yongqiang;GU Xiaohui;WANG Jiujian(State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures,Shijiazhuang Tiedao University,Shijiazhuang 050043;School of Mechanical Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050043)

机构地区：[1]石家庄铁道大学省部共建交通工程结构力学行为与系统安全国家重点实验室,石家庄050043 [2]石家庄铁道大学机械工程学院,石家庄050043

出　　处：《机械工程学报》2025年第6期249-259,共11页Journal of Mechanical Engineering

基　　金：国家自然科学基金(12032017,12393780,11902205);河北省教育厅科学技术研究(QN2023071,JZX2024006)资助项目。

摘　　要：受轮轨激励和复杂振动传递路径的干扰,轴箱轴承的微弱故障特征易被强背景噪声所湮没,难以有效提取。为此,基于高速列车单轴滚振台,开展轮轨激励下轴箱振动响应特征及故障诊断方法的研究。首先,通过开展速度等级在50~300 km/h范围内的高频激励试验,采集轴承健康状态、踏面损伤、轴承含外圈故障等条件下轴箱垂向振动响应数据,并对其时域波形、傅里叶频谱和包络谱等特征进行对比分析。分析结果表明:随着速度等级升高,系统的背景噪声逐渐增强,轴箱轴承故障特征逐渐被湮没;踏面损伤会激起周期性的瞬态冲击,在频域具有明显的稀疏性,表征为以转频为间隔的谐波簇,进一步加剧了轴承故障特征提取的难度。随后,在此基础上,提出一种倒频谱预白化与快速谱中值峭度图相结合的方法,用于轴箱轴承故障特征的最优共振参数识别,可以同时避免随机冲击和踏面损伤诱发的周期性冲击的影响。最后,通过试验信号对所提方法的有效性进行了验证。Due to the interference of wheel-rail excitation and complex vibration transmission path,the weak fault features of axle box bearings are easily drowned by strong background noise and are difficult to be extracted effectively.Therefore,the vibration response characteristics of axle-box under wheel-rail excitation and the fault diagnosis method are studied based on a high-speed train’s single-axle roller vibration rig.Firstly,the vertical vibration response data of axle-box under the condition of bearing health state,tread damage,and bearing with outer race fault are collected by carrying out the high-frequency excitation experiment with the speed level in the range of 50-300 km/h,and the characteristics of the time-domain waveform,Fourier spectrum,and envelope spectrum are compared and analyzed.The results show that with the increase of the speed,the background noise of the system is gradually enhanced,and the fault characteristics of the axle-box bearing are gradually submerged.However,the tread damage will provoke periodic transient impacts,which have obvious sparsity in the frequency-domain and are characterized as harmonic clusters spaced by frequency rotation,which further aggravate the difficulty of bearing fault feature extraction.Then,on this basis,a method combining cepstrum prewhitening(CPW)and fast median kurtogram(FMK)is proposed to identify the optimal resonance parameters of axle-box bearing fault signals.The effect of random impact and periodic impact induced by tread damage can be avoided simultaneously.Finally,the effectiveness of the proposed method is verified by experimental signals.

关 键 词：高速列车 轴箱轴承 故障诊断 轮轨激励 中值峭度 倒频谱预白化 

分 类 号：V221[航空宇航科学与技术—飞行器设计]