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Road Roughness Evaluation by Curve-Fitting and Subspace-Identification Methods

机译:通过曲线拟合和子空间识别方法评估道路不平度

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摘要

In this paper, for a quarter-car model, root-mean square response variables are calculated for roads classified by the international standard organization, based on the straight-line spectrum models. Covariance expressions are derived for vehicle response variables assuming that the road spectrum is that of a Motor Industry Research Association (MIRA) spectrum and compared with the existing results in the literature. The international standard and the MIRA spectra are then compared with the models delivered by high resolution frequency-domain subspace identification algorithms. The IRI statistic of the quarter-car response is calculated for the road models built by the curve fitting and the identification methods from the measured road spectrum assuming that the road excitation is a zero-mean Gaussian process
机译:在本文中,对于四分之一车模型,基于直线谱模型,计算了由国际标准组织分类的道路的均方根响应变量。假设道路频谱是汽车工业研究协会(MIRA)的频谱,则针对车辆响应变量推导出协方差表达式,并将其与文献中的现有结果进行比较。然后将国际标准和MIRA光谱与高分辨率频域子空间识别算法提供的模型进行比较。在假定道路激励是零均值高斯过程的情况下,针对通过曲线拟合和识别方法构建的道路模型,根据测得的道路频谱计算了四分之一车响应的IRI统计量

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