Analysis and Modeling of GPR Signals to Detect Cavities: Case Studies in Morocco

Past research shows that the Ground Penetrating Radar (GPR) can be an effective and efficient way to map buried pipeline systems. This paper presents a GPR data analysis technique, which is first generated by applying the Finite Differences Time Domain (FDTD) method to estimate the thickness of the subsurface layers and characterize the piping systems buried in the underground. In practical investigations, the GPR unit with a 400 MHz antenna was used to detect imbalances and underground pipes. The GPR profiles provided details on the shapes and nature of the target in the underground. These profiles can, therefore, detect water pipes, utility systems up to a depth than 2 m.

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“…Note that all these B-scans are done on the same color scale. Similar results were obtained in [22][23][24][25].…”

Section: Numerical Simulationssupporting

confidence: 88%

Ground Penetrating Radar Data Acquisition to Detect Imbalances and Underground Pipes

Bachiri

Alsharahi

Khamlichi

et al. 2021

Lecture Notes in Electrical Engineering

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“…The network system of pre-existing public services, which includes underground hoppers and tunnels, drinking water and sewer pipes, gas pipes, storm water pipes, telecommunications cables, electricity and street lighting cables is a diverse, complex and often poorly defined network. Due to a need for knowledge of underground utility development, civil construction projects can easily cause, for example, gas explosion, road collapse, water leaks, infiltration of the road surface, cavities, fragile areas and void spaces [1], [2], [3], [4], [5], [6].…”

Section: Introductionmentioning

confidence: 99%

GPR application in Civil Engineering to search and detect underground Networks

Bachiri¹

2020

IJETER

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The industrial development and the intensive use of urban space lead to several problems in the management and operation of public services such as drinking water networks, sewer, telephone, gas, electricity, street lighting, and various cables and pipes that are buried either at footpaths or roadways. Damage or malfunction of pre-existing public services can potentially cause danger to humans. In order to minimize risks, GPR profiling was constructed as a tool of advanced non-destructive technologies leading to practical solutions to detect buried networks and reduce problems related to the destruction of existing underground utilities. The main objective of this study is to search and identify the various hidden systems to map them and indicate them on-site to avoid possible incidents. The purpose of this operation is to produce GPR profiles on the surface to be examined, while respecting a fairly regular spacing between patterns, using non-destructive techniques such as the GPR and the radio detector.

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“…A popular method for nondestructive detection of underground targets is the remote sensing techniques. One of the most successful modalities for remote sensing of underground targets is the ground-penetrating radar (GPR), and it has been extensively used in many fields, such as military, 1,2 civil engineering, 3,4 and geological survey. 5 GPR emits electromagnetic wave toward the ground, due to the different relative permittivity of the underground medium, the electromagnetic wave will be reflected back.…”

Section: Introductionmentioning

confidence: 99%

Buried target detection method for ground penetrating radar based on deep learning

Hui

Ouyang

Liu

et al. 2022

J. Appl. Rem. Sens.

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Deep learning method has been extensively applied to ground penetrating radar twodimensional profile (GPR B-SCAN) hyperbola detection recently. We propose a B-SCAN image feature extraction method based on the constraints of the GPR physical model, and further detect the weak boundary feature curve of the target in the local space. A deep convolutional neural network (DCNN) is first designed to extract high-level semantic features from B-SCAN images to remove direct wave. Next, a multiscale feature fusion DCNN is used to extract the features of the B-SCAN image with the direct wave removed, and the classifier network is used to identify the hyperbola of the upper boundary feature of the target. Finally, according to the hyperbola, the local space corresponding to the target in the B-SCAN image is determined. On this basis, the amplitude and phase information of the scattered electric field are used to segment the lower boundary characteristic curve of the target through convolution operation. Experimental results on simulation and field data show that feature information of the buried target in the GPR B-SCAN image can be efficiently extracted when the proposed method is adopted. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Analysis and Modeling of GPR Signals to Detect Cavities: Case Studies in Morocco

Cited by 13 publications

References 12 publications

Ground Penetrating Radar Data Acquisition to Detect Imbalances and Underground Pipes

Ground Penetrating Radar Data Acquisition to Detect Imbalances and Underground Pipes

GPR application in Civil Engineering to search and detect underground Networks

Buried target detection method for ground penetrating radar based on deep learning

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