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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。
The application of gray box identification in the estimation of second-line suspension parameters of railway vehicles is introduced. The gray-box identification method is used to estimate the mass, damping and stiffness parameters of second-line suspension. The identification results of two gray box identification software tools, MoCaVa and CTSM, are compared . The results show that MoCaVa accurately estimates the structural parameters of the linear model in the presence of measurement noise, and the identification results are robust to initial parameters. The method is of great significance for monitoring the running status of the vehicle and diagnosing the fault of the vehicle.