Tosti, Fabio ORCID: https://orcid.org/0000-0003-0291-9937, Munisami, Kevin, Sofroniou, Anastasia, Alani, Amir and Benedetto, Francesco (2018) A sampling investigation of GPR wave propagation velocity data to improve migration processing of concrete rebars. In: 41st International Conference on Telecommunications and Signal Processing, 4-6 July 2018, Athens, Greece.
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Abstract
In this study, a demonstration of the potential of ground-penetrating radar (GPR) for improving location of rebars is given. To this purpose, a high-frequency GPR system with a 2000 MHz dual-polarised antenna (HH/VV polarisations) has been used to collect data on a reinforced concrete floor of dimensions 1m×0.80m (longitudinal and transversal acquisitions). The high-dense grid mesh of rebars and the use of the hyperbola fitting method allowed for the acquisition of a dataset of wave propagation velocity values. Hence, an analysis of the statistic distribution of propagation velocity values was carried out to assess the data dispersion throughout the area. A data sampling approach was then proposed and velocity values were sampled at different percentages and in an evenly-distributed manner throughout the inspected area. Corresponding values of velocity were therefore used for data migration purposes and C-scan maps were produced as a combination of longitudinal/transversal acquisitions and HH/VV polarisations. The optimum sampling rate of wave propagation velocity was then assessed by way of comparison of the migrated maps.
Item Type: | Conference or Workshop Item (Paper) |
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ISBN: | 9781538646953 |
Identifier: | 10.1109/TSP.2018.8441373 |
Identifier: | 10.1109/TSP.2018.8441373 |
Keywords: | GPR; data sampling; hyperbola fitting; data migration; rebars location |
Subjects: | Construction and engineering > Civil and environmental engineering Construction and engineering > Digital signal processing Construction and engineering > Electrical and electronic engineering Construction and engineering > Civil and structural engineering |
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Depositing User: | Fabio Tosti |
Date Deposited: | 19 Apr 2018 08:06 |
Last Modified: | 04 Nov 2024 12:50 |
URI: | https://repository.uwl.ac.uk/id/eprint/4844 |
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