摘要
获取铁道车辆构架空簧、附属部件、轴箱弹簧及橡胶节点等关键接口在服役过程中的载荷特征是落实轨道车辆结构健康监测工作需要解决的关键问题。文章建立车辆系统动力学模型,推导了考虑转臂轴箱局部细化的车辆横向、垂向的动力学模型,并以此为基础使用卡尔曼滤波方法,通过系统状态方程对系统状态量进行估计反演计算,探索转向架构架载荷的估计方法。研究结果表明:考虑轨道不平顺激励的情况下,转向架构架的垂向载荷估计值与仿真值的相关性达到0.8以上,横向载荷估计值与仿真值的相关性超过0.6,估计值与仿真值时频域的变化趋势一致性较好。综合以上结果,可以证明该载荷估计方法在针对轨道车辆构架的关键接口载荷的反演计算中具有足够的精确性和稳定性,能够为后续对转向架关键位置的损伤监测与评估、剩余寿命计算和结构设计优化提供数据依据。
It is critical in the implementation of structural health monitoring for rolling stock to acquire load characteristics of vital interfaces such as air suspensions,auxiliary components,axle box springs,and rubber joints during the service life.This paper explored an estimation method for loads on bogie frames.Based on an initially established vehicle system dynamics model,lateral and vertical dynamics models were derived,incorporating localized refinements specific to rocker type axle boxes.Based on these models,Kalman filtering was applied for inversion estimation of system state quantities through the system state equation.The study results,which considered excitations from track irregularities,show a correlation surpassing 0.8 between the estimated and simulated values for vertical loads on the bogie frame,while a correlation exceeding 0.6 for lateral loads.These findings indicate consistent change trends in the time-frequency domain between the estimated and simulated values.Moreover,as the vehicle speed increases,the accuracy of the inversion results based on Kalman filtering progressively improve in correlation with the simulated values.Based on the above outcomes,conclusions can be drawn that the proposed load estimation method is sufficiently accurate and stable in the inversion calculations for loads on the critical interfaces of bogie frames.This method can serve as a data foundation for subsequent damage monitoring and evaluation,remaining life calculations,and optimizing the structural design for key bogie components.
作者
龚敬
吴兴文
刘阳
池茂儒
GONG Jing;WU Xingwen;LIU Yang;CHI Maoru(School of Mechanical Engineering,Southwest Jiaotong University,Chengdu,Sichuan 610031,China;State Key Laboratory of Rail Transit Vehicle System,Southwest Jiaotong University,Chengdu,Sichuan 610031,China)
出处
《机车电传动》
2024年第3期28-37,共10页
Electric Drive for Locomotives
基金
国家自然科学基金区域联合基金(U21A20168)。
关键词
铁道车辆
构架
振动加速度
卡尔曼滤波
载荷反演
rolling stock
bogie frame
vibration acceleration
Kalman filtering
load inversion