路面粗糙度的随机建模

J.J. Zhu, Wenli Zhu
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引用次数: 3

摘要

路面粗糙度通常用路面轮廓数据的一位数统计来表示。这种方法在路面轮廓数据中丢弃了大量有用的路面信息。在本研究中,开发了路面粗糙度的信息参数模型,其中路面粗糙度被视为随机信号。在此基础上,提出了一种新的随机粗糙度指数(SRI)。对18个FACE Dipstick剖面数据和使用Ames剖面仪收集的25个剖面数据进行的案例研究表明,无论剖面设备如何,新的SRI都与国际粗糙度指数具有良好的相关性。
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Stochastic modelling of pavement roughness
Pavement roughness is usually characterized by a one figure statistic of pavement profile data. This approach discards a rich body of useful pavement information in the pavement profile data. In this study, informative parametric models for pavement roughness are developed where pavement roughness is treated as a stochastic signal. Based on this stochastic modeling of roughness, a new stochastic roughness index (SRI) is proposed. Case studies conducted on 18 FACE Dipstick profile data and 25 profile data collected using an Ames Profilograph shows that the new SRI, irrespective to the profiling devices, has a good correlation with the International Roughness Index.
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