Title: Pavement profile analysis using ensemble empirical mode decomposition

Authors: Y.O. Adu-Gyamfi, Nii O. Attoh-Okine, A.Y. Ayenu-Prah

Addresses: Department of Civil and Environmental Engineering, University of Delaware, Newark, DE 19711, USA. ' Department of Civil and Environmental Engineering, University of Delaware, Newark, DE 19711, USA. ' Department of Civil and Environmental Engineering, University of Delaware, Newark, DE 19711, USA

Abstract: Pavement profile analysis is a major component in pavement infrastructure management decision making for maintenance and rehabilitation. Road profile data are non-stationary and inherently non-Gaussian. This paper presents the application ensemble empirical mode decomposition (EEMD) to profile data analysis. The EEMD employs multiple applications of empirical mode decomposition (EMD), to which white noise is added, with constant amplitude relative to the target data. The uniform distribution of white noise over the entire time frequency space provides a reference frame for signals of comparative scale to collate in one intrinsic mode function, thus eliminating mode mixing. The EEMD approach was compared with the traditional EMD and it appears that the EEMD outperforms the traditional EMD.

Keywords: HHT; Hilbert-Huang transform; pavement profile analysis; EEMD; ensemble empirical mode decomposition; EMD; empirical mode decomposition; road profiles; infrastructure management; decision making; road maintenance; road rehabilitation.

DOI: 10.1504/IJVSMT.2009.032020

International Journal of Vehicle Systems Modelling and Testing, 2009 Vol.4 No.4, pp.277 - 287

Received: 23 Mar 2009
Accepted: 16 Sep 2009

Published online: 04 Mar 2010 *

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