Abstract
Pavement profile analysis is a major component in pavement infrastructure management decision making for maintenance and rehabilitation. This paper takes an in-depth look at pavement profile characterization and evaluation, taking into account the inherent nature of road profile data, i.e., nonstationary and non-Gaussian. Although there have been several studies aimed at the analysis and characterization of pavement profile, the bulk have been limited to applying relatively conventional signal processing techniques, such as the Fourier analysis. Using this approach, only the average condition of the local conditions can be represented. Most transient and changing signals will not be handled well due to the averaging effect of the technique. The Hilbert-Huang transform operates at the scale of every oscillation, an extremely important property for obtaining localized profile information. In this paper, the different algorithms of the Hilbert-Huang transform: empirical mode decomposition (EMD), ensemble EMD...
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