Using FFT-Based Data Processing Techniques to Characterize Asphaltic Concrete Mixtures

Authors

Scott A. Starks, The University of Texas at El PasoFollow
Vladik Kreinovich, The University of Texas at El PasoFollow
Roberto Araiza, The University of Texas at El PasoFollow
Soheil Nazarian, The University of Texas at El PasoFollow
J. Adidhela

Publication Date

5-2004

Comments

UTEP-CS-04-16.

Published in Proceedings of the 11th IEEE Digital Signal Processing Workshop, Taos, New Mexico, August 1-4, 2004, pp. 241-245.

Abstract

A natural way to test the quality of a pavement is to send signals with different frequencies through the pavement and compare the results with the signals passing through an ideal pavement. For this comparison, we must determine how, for the corresponding mixture, the elasticity E depends on the frequency f in the range from 0.1 to 10^5 Hz. It is very expensive to perform measurements in high frequency area (above 20 Hz). To avoid these measurements, we can use the fact that for most of these mixtures, when we change a temperature, the new dependence changes simply by scaling. Thus, instead of performing expensive measurements for different frequencies, we can measure the dependence of E on moderate frequencies f for different temperatures, and then combine the resulting curves into a single "master" curve. In this paper, we show how DSP techniques can help to automate this "combination".