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Published in: Innovative Infrastructure Solutions 3/2020

01-12-2020 | Technical paper

Ultrasonic rock microcracking characterization and classification using Hilbert–Huang transform

Authors: Soufien Ezzeiri, Essaieb Hamdi

Published in: Innovative Infrastructure Solutions | Issue 3/2020

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Abstract

This study aims to set up a non-destructive method to control the quality of aggregates using ultrasonic wave acquisition and processing. Two applications are presented proving the applicability of the proposed methodology. The first is the characterization and classification of four limestone rocks from cement quarries in the northern part of Tunisia selected from different geological ages (Lower Jurassic, Upper Cretaceous, and Lower Eocene). The second application deals with assessing rock crushing-induced microcracking evolution in quarried rock from the first initial source rock mass to the final aggregate. Five stages were considered: before the blast (bench front), after the blast round (muck pile), after the primary crusher, after the secondary crusher, and after the tertiary crusher. A physico-chemical and ultrasonic characterization was performed on aggregates and core samples in order to identify their characteristics namely the crack porosity and P-wave velocity. A cluster statistical analysis was then adopted to classify the investigated samples into several groups where crack porosity is the most relevant factor in classifying their quality. In addition to measuring ultrasonic parameters such as the spatial attenuation and P-wave velocity, the ultrasonic study looks at the spectrum of the received signal (non-stationary and nonlinear signal) by measuring the instantaneous energy density with the Hilbert–Huang transform. Beyond the fact that the high negative correlation between the P-wave velocity and the instantaneous energy was identified, the methodology developed allowed to prove that the latter is a relevant factor for the classification of limestone rocks.

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Metadata
Title
Ultrasonic rock microcracking characterization and classification using Hilbert–Huang transform
Authors
Soufien Ezzeiri
Essaieb Hamdi
Publication date
01-12-2020
Publisher
Springer International Publishing
Published in
Innovative Infrastructure Solutions / Issue 3/2020
Print ISSN: 2364-4176
Electronic ISSN: 2364-4184
DOI
https://doi.org/10.1007/s41062-020-00347-2

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