基于铁道车辆振动加速度的轴承载荷反演研究

On inverse identification method of bearing load based on railway vehicle acceleration

轴承作为高速列车传动系统中的关键部件,一旦发生故障会直接影响高速列车的运行安全。准确获取轴承在高速列车运行过程中的动载荷,能够为轴承的前期设计、疲劳寿命与服役性能研究提供真实的边界输入,具有重要的工程实际价值。推导了考虑Maxwell减振器模型和转臂轴箱装置的18自由度垂向与21自由度横向车辆动力学模型,进而确定车辆系统空间状态方程,在卡尔曼滤波框架下提出一种由高速列车车辆振动加速度反演轴承载荷的方法。最后利用SIMPACK软件建立整车动力学模型,分别施加典型的轨道不平顺随机激励与车轮多边形周期性高频激励对该方法进行验证。研究结果表明:反演得到的轴承横垂向载荷与仿真值的时频域变化趋势以及幅值具有较好的一致性。在轨道不平顺激励下各轴箱轴承垂向相关系数均大于0.7,横向相关系数均大于0.6;在车轮多边形高频激励下轴承垂向相关系数为0.97,横向相关系数为0.96;在轨道不平顺与车轮多边形激励共同作用下轴承垂向相关系数为0.79,横向相关系数为0.77。综上,该轴承载荷反演方法在传统车辆模型的基础上考虑了轴箱轴承本身的运动,具有较高的反演精度和线路适应性,能够获取准确的轴承载荷,为轴承的剩余寿命研究、结构设计与优化提供数据基础。

The bearings,as key parts of the drive system of high-speed trains,directly affect the operation safety of high-speed train once the fault occurs.Accurately obtaining the dynamic load of the bearing during the highspeed train operation can provide real boundary input conditions for the early design,fatigue life and service performance of the bearing,which has important engineering practical value.In this paper,18-DOF vertical and 21-DOF lateral vehicle dynamics models were established considering Maxwell shock absorber model and axle box rotary arm,and then the state-space equation of the vehicle system was determined.Aninverse methodfor identifying bearing load from vibration acceleration of high-speed train vehiclewas proposed by using theKalman filter algorithm.Finally,the vehicle dynamics model was established by using the SIMPACK®software program,and the method was verified by applying typical random excitation of track irregularity and periodic highfrequency excitation of wheel polygon,respectively.The results show that the variation trend and amplitude of thevertical bearing load identified by the inverse methodwere consistent with simulation results in time-frequency domain.Under the random excitation of track irregularity,the vertical correlation coefficient of each axle box bearing is greater than 0.7,and the lateral correlation coefficient is greater than 0.6.Under high-frequency excitation of polygon wheel,the vertical correlation coefficient of bearing is 0.97,and the lateral correlation coefficient is 0.96.Under the combined action of track irregularity and wheel polygon excitation,the vertical correlation coefficient of bearing is 0.79 and the lateral correlation coefficient is 0.77.To sum up,theinverse methodfor identifying bearing load takes into account the movement of the axle box bearing itself based on the traditional vehicle model.It has high inversion accuracy and line adaptability,and can obtain accurate bearing load to provide data basis for studyingthe remaining service lifeof the bearings andtheir structural design and optimization.