Airport Asphalt Pavement Profile Analysis: Ensemble Empirical Mode Decomposition Approach
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Pavement surface unevenness affects the ride quality, safety and the overall aircraft operation costs. Through profile analysis, important interventions can be made to improve the lifetime and safety of pavements. The purpose of this study is to develop a methodology that will be used to analyze the ride quality of pavements in terms of roughness. Several studies have been conducted on airport pavement roughness recently. However, most of these studies use signal processing routines that are based on linear and stationary methods such as Fourier and Wavelets analysis. Using such approaches limits their general application to real datasets due to their averaging effect. This study presents the application of the Hilbert-Huang Transform (HHT), an adaptive signal processing technique to profile analysis. The algorithm operates at the scale of every oscillation decomposing the original data into oscillations that characterize the measured pavement profile. These oscillations are called Intrinsic Mode Functions (IMFs). After decomposition, a minimum wave number gradient algorithm is used to reconstruct IMFs which may be contributing to the roughness of the pavement. Next, a roughness criterion based on local wavelength, height and velocity of aircraft is used to determine the response of an aircraft to sections with roughness issues. Finally, an intervention procedure is developed to repair the sections with roughness issues through a milling and filling process. Overall, the methodology developed is straightforward, effective and practical; providing solutions for the design and management of airport pavement infrastructure.