摘要
介绍了灰箱辨识在铁道车辆二系悬挂参数估计中的应用,运用灰箱辨识方法估计二系悬挂的质量、阻尼和刚度参数,并比较了两种灰箱辨识软件工具MoCaVa和CTSM的辨识结果。分析辨识结果发现MoCaVa在测量噪声存在时比较精确的估计出线性模型的结构参数,且辨识结果对参数初值具有鲁棒性。该方法对监测车辆的运行状态,诊断车辆故障具有重要意义。
Application of grey box identification in the parameters estimation for secondary suspension on railway vehicle is introduced.The parameters of mass, damp and stiffness of secondary suspension are estimated by grey box identification method, and the identification results of two software tools MoCaVa and CqSM are compared.It is found that MoCaVa can identify the structure parameters of linear models with measurement noise, and the results are robust to the initial values of parameters after analyzing identification them.The method is important in inspection of vehicle running status and vehicle faults diagnosis.
出处
《铁道机车车辆》
2006年第4期26-28,共3页
Railway Locomotive & Car
关键词
灰箱辨识
参数估计
车辆系统
极大似然估计
KALMAN滤波
grey box identification
parameters estimation
vehicle system
maximum likelihood estimation
kalman filtering
