轨道交通车辆模态参数辨识方法研究

运用子空间辨识数值算法直接辨识出轨道交通车辆动力学系统的状态方程,对系统矩阵进行特征值分解后获得模态频率和阻尼比,运用稳态图来确定系统的物理极点,最后获得所识别系统的模态参数。利用此法,对轨道交通车辆垂向仿真模型进行了模态参数辨识研究。研究结果表明:如以轨道不平顺作为车辆输入、以车体和构架的位移响应作为系统输出进行辨识,则即使在噪声信号较大时,仍能获得良好的识别效果;运用仿真模型的加速度输出信号进行辨识时,车辆模态参数的识别精度受噪声影响很大;当噪声信号为原信号的5%时,以构架加速度作为输入、车体振动响应作为输出,仍能有效地识别车体的模态参数。

Research on Modal Parameters Identification Method for Rail Transit Vehicle

In this paper,the N4SID algorithm is applied to di-rectly identify the state space equations of rail transit vehicle dynamic system. Through eigenvalue decomposition of the system matrix,the mode frequencies and damping ratios are obtained,then,the physical poles are selected based on the stable diagram,the vehicle dynamic mode parameters are final-ly received. With this method,the modal parameters identifi-cation of a vertical rail transit virtual prototype is studied. The result shows that with the track irregularity as the input,the carbody and bogie displacement response as the system out-put,even when the noise signal is relatively large,the identi-fied parameters still have very good consistency with the theo-retical data. But when the acceleration is taken as the output, the identification precision is vulnerable to the noise signal intensity. When the noise is 5% of the original signals,the modal parameters of carbody can be successfully identified by using the bogie acceleration response as the input and the vi-bratory response of carbody as the output.