车辆路面纵向振动信号再现方法研究

基于自回归滑动平均模型(ARMA)的方法，实现了不同车速和路面条件下的随机振动信号的实验室再现。并对某货车的半主动悬架物理模型进行了路面随机振动信号再现和平顺性试验，通过对实际信号和再现信号的统计数据、累积频率分布(CFD)和功率谱密度(PSD)的效果比较，表明其优点是方法简单、准确度高、周期短、费用低。

A Research on Reconstruction of Vehicle Longitudinal Vibration Signal

The reconstruction of vehicle random vibration signal under different vehicle speed and road conditions is realized in laboratory, based on an auto regressive moving average (ARMA) time series model. A riding test is conducted on a physical model for semi-active suspension of a specific truck. The comparison between real signals and reconstructed signals in terms of statistical data, cumulative frequency distribution (CFD) and power spectral density (PSD) show that the ARMA time series model has the advantage of simple, accurate and less costly.