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Wavelet Analysis and interpretation of Road Roughness

机译：小波分析与路面不平度的解释

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摘要

Road roughness indices such as the International Roughness Index, Quarter-car Index, and root-mean-square vertical acceleration are useful as indicators of the level of pavement serviceability performance. Each of these summary roughness statistics offers a convenient index for monitoring the trend of pavement roughness deterioration with time. However, they do not retain the actual contents of pavement surface roughness. Such detailed roughness information may be useful for maintenance operations, detection of pavement surface distresses, and detailed analysis of the trend of pavement roughness deterioration. This paper presents an application procedure based on wavelet theory to offer supplementary information to a roughness index and provide additional information on the characteristics of the roughness profile of interest. The procedure is able to identify the characteristics of a pavement roughness profile in both the frequency and distance domains. This study proposes methods of roughness data processing using different wavelet transformation and analysis techniques to extract useful information for pavement maintenance management. Numerical examples based on measured roughness profiles of the Long Term Pavement Performance (LTPP) database are presented to illustrate the types of useful information derivable with the proposed method of analysis. It is demonstrated that using appropriately selected analysis methods and wavelet parameters, detailed roughness features of interest to pavement engineers not currently available from summary roughness statistics can be obtained together with summary roughness statistics as part of the roughness survey report for highway agencies.
机译：道路粗糙度指数（例如国际粗糙度指数，四分之一车辆指数和均方根垂直加速度）可用作路面可使用性性能水平的指标。这些摘要粗糙度统计数据中的每一个都提供了一个方便的指标，用于监视路面粗糙度随时间的恶化趋势。但是，它们不保留路面表面粗糙度的实际含量。这种详细的粗糙度信息可用于维护操作，检测路面表面应力以及对路面粗糙度恶化趋势进行详细分析。本文提出了一种基于小波理论的应用程序，以提供粗糙度指数的补充信息，并提供有关目标粗糙度轮廓的特征的其他信息。该程序能够在频域和距离域中识别路面粗糙度轮廓的特征。这项研究提出了使用不同的小波变换和分析技术来处理粗糙度数据的方法，以提取有用的信息，用于路面维护管理。给出了基于长期路面性能（LTPP）数据库测得的粗糙度轮廓的数值示例，以说明所提出的分析方法可得出的有用信息的类型。结果表明，使用适当选择的分析方法和小波参数，可以从汇总粗糙度统计信息中获得当前未获得的路面工程师感兴趣的详细粗糙度特征，以及汇总粗糙度统计信息，作为公路机构粗糙度调查报告的一部分。

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