Wavelet-Based Multiresolution Analysis of Pavement Profiles as a Diagnostic Tool

Abstract

Discrete wavelet transform (DWT) was proposed as a new diagnostic tool for locating various frequency-related features of profiles, such as repeated waves and short-lived surface distress, that affect ride quality. The shortcomings of power spectrum density (PSD) analysis in evaluating the distribution of energy of a profile between various frequency band-widths were pointed out. The theoretical background and the basics of the DWT decomposition algorithm are discussed. Advantages of DWT analysis over PSD analysis in detection of short-lived features of the profile are illustrated by an example. The results of both the PSD and DWT analyses of three profile data, taken from data collected as a part of an ongoing research project sponsored by New Jersey Department of Transportation, are presented. The results indicate that DWT analysis can capture both short-lived high-frequency and long-lived low-frequency features of the profile and, consequently, provides a better representation of the profile characteristics. The application of DWT in the development of new ride indices is also discussed.