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为了进一步提高对虚拟路面的重构精度,根据路面不平度是实平稳随机过程这一特点,按给定的标准路面不平度功率谱密度建立其相应的时间序列模型—AR模型。以此对路面不平度进行重构并对重构结果作相应的谱分析。通过对重构不平度的功率谱密度与标准功率谱密度之间的相对误差控制来确定AR模型的最优阶数,即当相对误差在某一阶数下取得最小值时,则此阶数就为模型的最优阶数。利用该方法对标准路面进行重构,结果表明,重构的功率谱和不平度均方根值的拟合精度相对传统的阶数确定方法都有较大的提高,从而证明此阶数确定方法的可行性和优越性。
In order to further improve the reconstruction accuracy of the virtual road surface, according to the characteristic that the road roughness is a real stationary random process, the corresponding time series model-AR model is established according to the given standard road roughness power spectral density. In this way, the roughness of road surface can be reconstructed and the corresponding spectrum analysis can be made. The optimal order of the AR model is determined by the relative error control between the reconstructed power spectral density and the standard power spectral density. That is, when the relative error reaches the minimum value under a certain order, then the order It is the optimal order of the model. Reconstruction of the standard pavement using this method shows that the fitting accuracy of the reconstructed power spectrum and the root mean square roughness value is greatly improved compared with the traditional order determination method. The feasibility and superiority.