scholarly journals Application of Combining YOLO Models and 3D GPR Images in Road Detection and Maintenance

2021 ◽  
Vol 13 (6) ◽  
pp. 1081
Author(s):  
Zhen Liu ◽  
Wenxiu Wu ◽  
Xingyu Gu ◽  
Shuwei Li ◽  
Lutai Wang ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Detection Efficiency ◽  
Rapid Identification ◽  
Detection Methods ◽  
Maintenance Cost ◽  
Surface Conditions ◽  
3D Gpr ◽  
Internal Information ◽  
Road Testing ◽  
Ground Penetrating

Improving the detection efficiency and maintenance benefits is one of the greatest challenges in road testing and maintenance. To address this problem, this paper presents a method for combining the you only look once (YOLO) series with 3D ground-penetrating radar (GPR) images to recognize the internal defects in asphalt pavement and compares the effectiveness of traditional detection and GPR detection by evaluating the maintenance benefits. First, traditional detection is conducted to survey and summarize the surface conditions of tested roads, which are missing the internal information. Therefore, GPR detection is implemented to acquire the images of concealed defects. Then, the YOLOv5 model with the most even performance of the six selected models is applied to achieve the rapid identification of road defects. Finally, the benefits evaluation of maintenance programs based on these two detection methods is conducted from economic and environmental perspectives. The results demonstrate that the economic scores are improved and the maintenance cost is reduced by $49,398/km based on GPR detection; the energy consumption and carbon emissions are reduced by 792,106 MJ/km (16.94%) and 56,289 kg/km (16.91%), respectively, all of which indicates the effectiveness of 3D GPR in pavement detection and maintenance.

Model Track Studies by Ground Penetrating Radar (GPR) on Ballast With Different Fouling and Geotechnical Properties

2015 ◽  
Author(s):  
Hamed Faghihi Kashani ◽  
Carlton L. Ho ◽  
Charles P. Oden ◽  
Stanley S. Smith
Keyword(s):  
Ground Penetrating Radar ◽  
Large Scale ◽  
Empirical Studies ◽  
Geotechnical Properties ◽  
Maintenance Cost ◽  
Non Invasive ◽  
Section Area ◽  
University Of Massachusetts ◽  
Ground Penetrating ◽  
The University

In recent years there has been an increase in the knowledge of, and need for, non-invasive monitoring of ballast in order to identify the problematic sections of track and decrease the maintenance cost. Various technologies such as Ground Penetrating Radar (GPR) are becoming accepted for investigating the condition of ballast. However since these techniques were not originally developed for engineering applications, their applicability in ballast evaluations can be sometimes uncertain. Continued empirical studies and condition specific calibrations are needed to demonstrate repeatable and quantifiable results. In this study large-scale track models with trapezoidal section area were constructed at the University of Massachusetts to investigate the effects of breakdown fouling, and the effects of changing geotechnical properties on GPR traces. This paper presents the design and construction of large scale track models, and methods used for GPR data collection. GPR data are presented in this paper that demonstrate sensitivity to the track model properties and variables. In particular, the experiments are being used to evaluate changes in GPR data with changing geotechnical properties of the ballast such as density, water content, grain size distribution (GSD), and fouling percentage.

The Application of Ground Penetrating Radar in Railway Tunnel Concrete Quality Detection

2011 ◽  
Vol 228-229 ◽  
pp. 1185-1189
Author(s):  
Su Qi ◽  
Xing Xing Chen
Keyword(s):  
Ground Penetrating Radar ◽  
Traditional Method ◽  
Detection Methods ◽  
Railway Tunnel ◽  
Testing Method ◽  
Quality Detection ◽  
Quality Testing ◽  
Concrete Quality ◽  
Ground Penetrating ◽  
Drilling Core

The priority of traditional tunnel concrete quality testing method is drilling core .The traditional method damage tunnel structure and detection speed is slowly.we use this method cann’t effectively meet the demand of rapid growth of tunnel concrete qulity testing. So the more fast and effective detection methods are needed.A new fast and effective kind of concrete quality detection methods is ground penetrating radar can meet the extensive tunnel concrete nondestructive testing. This paper introduces the basic principle of ground penetrating radar.I illustrate the application of railway tunnel testing by the testing in Ju Gan runnel of Lan Yue railway.TI is significance for railway tunnel concrete in future.

Ground‐penetratinng radar reflection profiling of groundwater and bedrock in an area of discontinuous permafrost

Geophysics ◽  
1998 ◽  
Vol 63 (5) ◽  
pp. 1573-1584 ◽  
Author(s):  
Steven A. Arcone ◽  
Daniel E. Lawson ◽  
Allan J. Delaney ◽  
Jeffrey C. Strasser ◽  
Jodie D. Strasser
Keyword(s):  
Ground Penetrating Radar ◽  
Relative Dielectric Permittivity ◽  
Well Log ◽  
Surface Conditions ◽  
Continuous Contact ◽  
Interior Alaska ◽  
Discontinuous Permafrost ◽  
Radar Reflection ◽  
Ground Penetrating ◽  
Scattering Losses

We have used ground‐penetrating radar to profile the depth of permafrost, to groundwater beneath permafrost, and to bedrock within permafrost in alluvial sediments of interior Alaska. We used well log data to aid the interpretations and to calculate dielectric permittivities for frozen and unfrozen materials. Interfaces between unfrozen and frozen sediments above permafrost were best resolved with wavelet bandwidths centered at and above 100 MHz. The resolution also required consideration of antenna configuration, season, and surface conditions. Depths to subpermafrost groundwater were profiled where it was in continuous contact with the bottom of the permafrost, except near transitions to unfrozen zones, where the contact appeared to dip steeply. The complexity of the responses to intrapermafrost bedrock, detected at a maximum depth of 47 m, appears to distinguish these events from those of subpermafrost saturated sediments. The relative dielectric permittivity ranged between 4.4 and 8.3 for the permafrost, and between 12 and 45 for partially to fully saturated, unfrozen silts and sands. Scattering losses are evident from intrapermafrost diffractions and from the improved penetration achieved by lowering the midband radar frequency from 100 to 50 MHz.

scholarly journals Rapid Detection Methods for Asphalt Pavement Thicknesses and Defects by a Vehicle-Mounted Ground Penetrating Radar (GPR) System

Sensors ◽  
2016 ◽  
Vol 16 (12) ◽  
pp. 2067 ◽  
Author(s):  
Zehua Dong ◽  
Shengbo Ye ◽  
Yunze Gao ◽  
Guangyou Fang ◽  
Xiaojuan Zhang ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Rapid Detection ◽  
Asphalt Pavement ◽  
Detection Methods ◽  
Ground Penetrating

scholarly journals Mapping of Agricultural Subsurface Drainage Systems Using a Frequency-Domain Ground Penetrating Radar and Evaluating Its Performance Using a Single-Frequency Multi-Receiver Electromagnetic Induction Instrument

2020 ◽  
Author(s):  
Triven Koganti ◽  
Ellen Van De Vijver ◽  
Barry J. Allred ◽  
Mogens H. Greve ◽  
Jørgen Ringgaard ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Ground Penetrating Radar ◽  
Electromagnetic Induction ◽  
Subsurface Drainage ◽  
Single Frequency ◽  
Drainage Systems ◽  
Local Soil ◽  
3D Gpr ◽  
Ground Penetrating ◽  
Emi Sensor

Subsurface drainage systems remove excess water from the soil profile thereby improving crop yields in poorly drained farmland. Knowledge of the position of the buried drain lines is important: 1) to improve understanding of leaching and offsite release of nutrients and pesticides, and 2) for the installation of a new set of drain lines between the old ones for enhanced soil water removal efficiency. Traditional methods of drainage mapping involve the use of tile probes and trenching equipment. While these can be effective, they are also time-consuming, labor-intensive, and invasive, thereby entailing an inherent risk of damaging the drainpipes. Non-invasive geophysical soil sensors provide a potential alternative solution. Previous research has focused on the use of time-domain ground penetrating radar (GPR), with variable success depending on local soil and hydrological conditions and the central frequency of the specific equipment employed. The objectives of this study were 1) to test the use of a stepped-frequency continuous wave (SFCW) 3D-GPR (GeoScope Mk IV 3D-Radar with DXG1820 antenna array) for subsurface drainage mapping, and 2) to evaluate the performance of a 3D-GPR with the use of a single-frequency multi-receiver electromagnetic induction (EMI) sensor (DUALEM) in-combination. The 3D-GPR system offers more flexibility for application to different (sub)surface conditions due to the coverage of wide frequency bandwidth. The EMI sensor simultaneously provides information about the apparent electrical conductivity (ECa) for different soil volumes, corresponding to different depths. This sensor combination was evaluated on twelve different study sites with various soil types with textures ranging from sand to clay till. While the 3-D GPR showed a high success rate in finding the drainpipes at five sites (sandy, sandy loam, loamy sand, and organic topsoils), the results at the other seven sites were less successful due to limited penetration depth (PD) of the 3D-GPR signal. The results suggest that the electrical conductivity estimates produced by the inversion of ECa data measured by the DUALEM sensor could be a useful proxy to explain the success achieved by the 3D-GPR in finding the drain lines. The high attenuation of electromagnetic waves in highly conductive media limiting the PD of the 3D-GPR can explain the findings obtained in this research.

scholarly journals Ground-penetrating radar imaging reveals glacier's drainage network in 3D

2021 ◽  
Vol 15 (8) ◽  
pp. 3975-3988
Author(s):  
Gregory Church ◽  
Andreas Bauder ◽  
Melchior Grab ◽  
Hansruedi Maurer
Keyword(s):  
High Resolution ◽  
Ground Penetrating Radar ◽  
Radar Imaging ◽  
Drainage Network ◽  
Direct Impact ◽  
3D Images ◽  
Drainage Networks ◽  
Glacier Dynamics ◽  
3D Gpr ◽  
Ground Penetrating

Abstract. Hydrological systems of glaciers have a direct impact on the glacier dynamics. Since the 1950s, geophysical studies have provided insights into these hydrological systems. Unfortunately, such studies were predominantly conducted using 2D acquisitions along a few profiles, thus failing to provide spatially unaliased 3D images of englacial and subglacial water pathways. The latter has likely resulted in flawed constraints for the hydrological modelling of glacier drainage networks. Here, we present 3D ground-penetrating radar (GPR) results that provide high-resolution 3D images of an alpine glacier's drainage network. Our results confirm a long-standing englacial hydrology theory stating that englacial conduits flow around glacial overdeepenings rather than directly over the overdeepening. Furthermore, these results also show exciting new opportunities for high-resolution 3D GPR studies of glaciers.

DETECTION OF ROAD CAVITIES IN URBAN CITIES BY 3D GROUND PENETRATING RADAR

Geophysics ◽  
2021 ◽  
pp. 1-44
Author(s):  
Hai Liu ◽  
Zhenshi Shi ◽  
Jianhui Li ◽  
Chao Liu ◽  
Xu Meng ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Antenna Arrays ◽  
Ground Penetrating Radar ◽  
Data Interpretation ◽  
Cavity Depth ◽  
Near Surface ◽  
Horizontal Size ◽  
3D Gpr ◽  
One Year ◽  
Ground Penetrating

Cavities under urban roads have increasingly become a great threat to the traffic safety in many cities. As a quick, effective, and high-resolution geophysical method, ground penetrating radar (GPR) has been widely used to detect and image near-surface objects. However, the interpretation of field GPR data is still challenging. For example, it is hard to distinguish reflections caused by road cavities or other urban utilities by a conventional 2D GPR survey. The superiority of 3D GPR in data interpretation is demonstrated by a laboratory experiment. Two pipes and a glass-made cavity buried in a sandpit show similar hyperbolic reflections in the 2D GPR profiles, and are hard to be discriminated. In contrast, their geometric shapes and dimensions are readily identified in the 3D image reconstructed from the synthetic 3D GPR dataset. Thus, a car-mounted 3D GPR system with two antenna arrays oriented in different polarization directions is developed, and has detected over 100 cavities in three Chinese cities over the past one year. The field data of two of the cavities are presented. As a result, the cavity depth, horizontal size and height can be accurately estimated from the 3D GPR dataset. Both laboratory and field experimental results indicate that 3D GPR possesses a great potential in detection and recognition of road cavities and utilities in the complicated urban environment.

scholarly journals 3D ground-penetrating radar imaging of ice complex deposits in northern East Siberia

Geophysics ◽  
2016 ◽  
Vol 81 (1) ◽  
pp. WA195-WA202 ◽  
Author(s):  
Stephan Schennen ◽  
Jens Tronicke ◽  
Sebastian Wetterich ◽  
Niklas Allroggen ◽  
Georg Schwamborn ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Structural Model ◽  
Late Quaternary ◽  
The Arctic ◽  
Field Site ◽  
East Siberia ◽  
Borehole Data ◽  
3D Gpr ◽  
Ground Penetrating ◽  
Ice Complex

Ice complex deposits are characteristic, ice-rich formations in northern East Siberia and represent an important part in the arctic carbon pool. Recently, these late Quaternary deposits are the objective of numerous investigations typically relying on outcrop and borehole data. Many of these studies can benefit from a 3D structural model of the subsurface for upscaling their observations or for constraining estimations of inventories, such as the local carbon stock. We have addressed this problem of structural imaging by 3D ground-penetrating radar (GPR), which, in permafrost studies, has been primarily used for 2D profiling. We have used a 3D kinematic GPR surveying strategy at a field site located in the New Siberian Archipelago on top of an ice complex. After applying a 3D GPR processing sequence, we were able to trace two horizons at depths below 20 m. Taking available borehole and outcrop data into account, we have interpreted these two features as interfaces of major lithologic units and derived a 3D cryostratigraphic model of the subsurface. Our data example demonstrated that a 3D surveying and processing strategy was crucial at our field site and showed the potential of 3D GPR to image geologic structures in complex ice-rich permafrost landscapes.

scholarly journals Mapping of Agricultural Subsurface Drainage Systems Using a Frequency-Domain Ground Penetrating Radar and Evaluating Its Performance Using a Single-Frequency Multi-Receiver Electromagnetic Induction Instrument

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3922 ◽  
Author(s):  
Triven Koganti ◽  
Ellen Van De Vijver ◽  
Barry J. Allred ◽  
Mogens H. Greve ◽  
Jørgen Ringgaard ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Ground Penetrating Radar ◽  
Electromagnetic Induction ◽  
Subsurface Drainage ◽  
Single Frequency ◽  
Drainage Systems ◽  
Local Soil ◽  
3D Gpr ◽  
Ground Penetrating ◽  
Emi Sensor

Subsurface drainage systems are commonly used to remove surplus water from the soil profile of a poorly drained farmland. Traditional methods for drainage mapping involve the use of tile probes and trenching equipment that are time-consuming, labor-intensive, and invasive, thereby entailing an inherent risk of damaging the drainpipes. Effective and efficient methods are needed in order to map the buried drain lines: (1) to comprehend the processes of leaching and offsite release of nutrients and pesticides and (2) for the installation of a new set of drain lines between the old ones to enhance the soil water removal. Non-invasive geophysical soil sensors provide a potential alternative solution. Previous research has mainly showcased the use of time-domain ground penetrating radar, with variable success, depending on local soil and hydrological conditions and the central frequency of the specific equipment used. The objectives of this study were: (1) to test the use of a stepped-frequency continuous wave three-dimensional ground penetrating radar (3D-GPR) with a wide antenna array for subsurface drainage mapping and (2) to evaluate its performance with the use of a single-frequency multi-receiver electromagnetic induction (EMI) sensor in-combination. This sensor combination was evaluated on twelve different study sites with various soil types with textures ranging from sand to clay till. While the 3D-GPR showed a high success rate in finding the drainpipes at five sites (sandy, sandy loam, loamy sand, and organic topsoils), the results at the other seven sites were less successful due to the limited penetration depth of the 3D-GPR signal. The results suggest that the electrical conductivity estimates produced by the inversion of apparent electrical conductivity data measured by the EMI sensor could be a useful proxy for explaining the success achieved by the 3D-GPR in finding the drain lines.

scholarly journals 3D GPR Image-based UcNet for Enhancing Underground Cavity Detectability

2019 ◽  
Vol 11 (21) ◽  
pp. 2545 ◽  
Author(s):  
Man-Sung Kang ◽  
Namgyu Kim ◽  
Seok Been Im ◽  
Jong-Jae Lee ◽  
Yun-Kyu An
Keyword(s):  
Ground Penetrating Radar ◽  
Super Resolution ◽  
Data Interpretation ◽  
Dependent Data ◽  
Test Results ◽  
Underground Cavity ◽  
Cavity Detection ◽  
3D Gpr ◽  
Ground Penetrating

This paper proposes a 3D ground penetrating radar (GPR) image-based underground cavity detection network (UcNet) for preventing sinkholes in complex urban roads. UcNet is developed based on convolutional neural network (CNN) incorporated with phase analysis of super-resolution (SR) GPR images. CNNs have been popularly used for automated GPR data classification, because expert-dependent data interpretation of massive GPR data obtained from urban roads is typically cumbersome and time consuming. However, the conventional CNNs often provide misclassification results due to similar GPR features automatically extracted from arbitrary underground objects such as cavities, manholes, gravels, subsoil backgrounds and so on. In particular, non-cavity features are often misclassified as real cavities, which degrades the CNNs’ performance and reliability. UcNet improves underground cavity detectability by generating SR GPR images of the cavities extracted from CNN and analyzing their phase information. The proposed UcNet is experimentally validated using in-situ GPR data collected from complex urban roads in Seoul, South Korea. The validation test results reveal that the underground cavity misclassification is remarkably decreased compared to the conventional CNN ones.

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