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Underground Pipeline Identification into a Non-Destructive Case Study Based on Ground-Penetrating Radar Imaging

Authors :
Nicoleta Iftimie
Adriana Savin
Rozina Steigmann
Gabriel Silviu Dobrescu
Source :
Remote Sensing, Vol 13, Iss 17, p 3494 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Ground-penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in nondestructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR has proven its ability to work in electromagnetic frequency range for subsoil investigations, and it is a risk-reduction strategy for surveying underground various targets and their identification and detection. This paper presents the results of a case study which exceeds the laboratory level being realized in the field in a real case where the scanning conditions are much more difficult using GPR signals for detecting and assessing underground drainage metallic pipes which cross an area with large buildings parallel to the riverbed. The two urban drainage pipes are detected based on GPR imaging. This provides an approximation of their location and depth which are convenient to find from the reconstructed profiles of both simulated and practical GPR signals. The processing of data recorded with GPR tools requires appropriate software for this type of measurement to detect between different reflections at multiple interfaces located at different depths below the surface. In addition to the radargrams recorded and processed with the software corresponding to a GPR device, the paper contains significant results obtained using techniques and algorithms of the processing and post-processing of the signals (background removal and migration) that gave us the opportunity to estimate the location, depth, and profile of pipes, placed into a concrete duct bank, under a structure with different layers, including pavement, with good accuracy.

Details

Language :
English
ISSN :
20724292
Volume :
13
Issue :
17
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.26ff8d5cfd04f4c91316e94e1ba9417
Document Type :
article
Full Text :
https://doi.org/10.3390/rs13173494