Title: Decomposing pavement surface profiles into a Gaussian sequence

Authors: Vincent Rouillard

Addresses: School of Engineering and Science, Victoria University of Technology, P.O. Box 14428, Melbourne City, MC VIC 8001, Australia

Abstract: This paper proposes that the non-Gaussian (leptokurtic) nature of pavement surface elevation data is a direct result of the inherent level-type non-stationarity of the process manifested as variations in magnitude or roughness. The hypothesis that random pavement profiles are essentially composed of a sequence of zero-mean random Gaussian processes of varying standard deviations is put forward and tested. This paper introduces a numerical approach for decomposing non-stationary random vibration signals into constituent Gaussian elements by extracting Gaussian component of varying root mean square (RMS) levels from the distribution estimates using a curve fitting algorithm. The validity of the method was tested using a representative set of pavement profiles. The decomposition method presented is significant in that it affords great simplicity for the synthesis of non-stationary pavement profiles which can be achieved without much difficulty when the process is represented by a sequence of Gaussian events.

Keywords: non-stationary pavement profiles; road profiles; random vibration signals; Gaussian sequence; non-Gaussian sequence; kurtosis; spectrum; decomposition; synthesis; road surface elevation; curve fitting.

DOI: 10.1504/IJVSMT.2009.032021

International Journal of Vehicle Systems Modelling and Testing, 2009 Vol.4 No.4, pp.288 - 305

Received: 03 Apr 2009
Accepted: 16 Sep 2009

Published online: 04 Mar 2010 *

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