Reflection characteristics of typical road defects in 3D GPR images for collapse mitigation

Pan, Jingwen; Shi, Zhenshi; Meng, Xu; Yue, Yunpeng; Lin, Caide; Chen, Jie; Liu, Hai; Cui, Jie

doi:10.1016/j.jappgeo.2023.105166

Cited by 11 publications

(3 citation statements)

References 28 publications

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“…Three-dimensional ground-penetrating radar (GPR) nondestructive testing technology is capable of analyzing phase and amplitude changes in electromagnetic waves within pavement structures. This technology is widely applied for diagnosing internal pavement issues, assessing subbase conditions, and locating underground utilities [18][19][20][21][22][23][24][25]. In the present study, we propose the integration of artificial neural networks to expedite the diagnosis of pavement diseases using GPR data.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional orthorectified simulation and ground penetrating radar detection of interlayer bonding condition in asphalt pavements

Yang,

Yao

et al. 2024

Meas. Sci. Technol.

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To evaluate the applicability of three-dimensional ground-penetrating radar (GPR) in assessing interlayer bonding within asphalt pavements featuring semi-rigid base layers, we conducted an analysis of the GPR detection mechanism. Employing forward simulation, various medium models were created to analyze electromagnetic wave transmission in air, water, and sand. GPR testing was applied to four distinct pavement structures, utilizing amplitude intensity levels and image processing techniques to assess asphalt pavement interlayer bonding. The results were validated by comparing them with core samples. The findings revealed a significant influence of medium uniformity on electromagnetic wave transmission processes. Non-uniform media models generate a large number of clutter waves, which refers to amplitudes and phases that have no predictable regularity in time and space i.e., they show irregular ups and downs and fluctuations. It is similar to the clutter that occurs during actual detection. Poorly bonded areas exhibited clearer hyperbolic ripples, primarily attributed to significant differences in the dielectric constants of filling materials. Amplitude strength effectively evaluated bonding across different asphalt pavement configurations and lanes, typically following a normal distribution. Enhanced interlayer contact correlated with smaller amplitudes, while weaker bonding led to larger amplitudes. The amplitude distribution in the center of lanes differed significantly from wheel track areas, indicating better interlayer bonding conditions in the center lanes compared to the wheel track belt. Moreover, radar plan views demonstrated considerable variation across different interlayer contact conditions. The image processing method proved effective in evaluating the interlayer contact condition of various pavement structures across full cross-sections.

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Section: Introductionmentioning

confidence: 99%

Three-dimensional orthorectified simulation and ground penetrating radar detection of interlayer bonding condition in asphalt pavements

Yang,

Yao

et al. 2024

Meas. Sci. Technol.

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“…GPR is a nondestructive device that functions as an echo-listener to capture electromagnetic waves reflected from interfaces with dielectric variations [7,8]. It has the capacity to discriminate between new and worn rock masses.…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Real-time Monitoring of Urban Roadway Health: Utilizing GPR Techniques for Early Detection and Classification of Subsurface Cavity Diseases

Shrestha,

Zhang

2024

Preprint

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The effectiveness of ground penetrating radar (GPR) in identifying and categorizing diseases that occur underground beneath the surfaces of urban roads is investigated in this study. Both 2D and 3D forward modeling use simulation with the GprMax program to show the response characteristics of common cavity illnesses, which facilitates interpretation in practical situations. The cavity morphology classification accuracy is improved to 90.5% by using convolutional neural networks (CNNs), specifically transfer learning with AlexNet. This method outperforms existing approaches even with minimal data. Four primary types are identified from an analysis of 1965 subsurface cavity data: hollow bodies, empty bodies, loose bodies, and water-rich bodies. These categories are important for evaluating road risks such as voids and subsidence. However, it is still difficult to interpret picture features linked to cavity diseases accurately because of a variety of elements, such as anthropogenic, environmental, and geological influences. However, the accurate interpretation and recognition of image features related to cavity diseases remain challenging. Moreover, there are various factors involved in the formation of underground diseases and cavities, including geological and environmental factors, physical and chemical properties of the geotechnical materials, anthropogenic engineering activity and social population or commercial effects.

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“…GPR has been commonly chosen to delineate the shallow geometry of subsurface materials or buried objects in a nondestructive and cost-effective manner. This technology has been widely applied in geology investigations [ 13 , 14 , 15 , 16 ], cultural heritage protection [ 9 , 17 , 18 , 19 ], urban infrastructure detection [ 20 , 21 , 22 , 23 ], water dynamics investigation [ 24 ], etc. Owing to the relative electrical property contrasts in the different media, the shallow geometry of subsurface materials or buried objects was revealed on a gray or color two-dimensional (2D) GPR profile.…”

Section: Introductionmentioning

confidence: 99%

Multisensor and Multiscale Data Integration Method of TLS and GPR for Three-Dimensional Detailed Virtual Reconstruction

Zhang,

Jia,

Ren

et al. 2023

Sensors

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Integrated TLS and GPR data can provide multisensor and multiscale spatial data for the comprehensive identification and analysis of surficial and subsurface information, but a reliable systematic methodology associated with data integration of TLS and GPR is still scarce. The aim of this research is to develop a methodology for the data integration of TLS and GPR for detailed, three-dimensional (3D) virtual reconstruction. GPR data and high-precision geographical coordinates at the centimeter level were simultaneously gathered using the GPR system and the Global Navigation Satellite System (GNSS) signal receiver. A time synchronization algorithm was proposed to combine each trace of the GPR data with its position information. In view of the improved propagation model of electromagnetic waves, the GPR data were transformed into dense point clouds in the geodetic coordinate system. Finally, the TLS-based and GPR-derived point clouds were merged into a single point cloud dataset using coordinate transformation. In addition, TLS and GPR (250 MHz and 500 MHz antenna) surveys were conducted in the Litang fault to assess the feasibility and overall accuracy of the proposed methodology. The 3D realistic surface and subsurface geometry of the fault scarp were displayed using the integration data of TLS and GPR. A total of 40 common points between the TLS-based and GPR-derived point clouds were implemented to assess the data fusion accuracy. The difference values in the x and y directions were relatively stable within 2 cm, while the difference values in the z direction had an abrupt fluctuation and the maximum values could be up to 5 cm. The standard deviations (STD) of the common points between the TLS-based and GPR-derived point clouds were 0.9 cm, 0.8 cm, and 2.9 cm. Based on the difference values and the STD in the x, y, and z directions, the field experimental results demonstrate that the GPR-derived point clouds exhibit good consistency with the TLS-based point clouds. Furthermore, this study offers a good future prospect for the integration method of TLS and GPR for comprehensive interpretation and analysis of the surficial and subsurface information in many fields, such as archaeology, urban infrastructure detection, geological investigation, and other fields.

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Reflection characteristics of typical road defects in 3D GPR images for collapse mitigation

Cited by 11 publications

References 28 publications

Three-dimensional orthorectified simulation and ground penetrating radar detection of interlayer bonding condition in asphalt pavements

Three-dimensional orthorectified simulation and ground penetrating radar detection of interlayer bonding condition in asphalt pavements

Real-time Monitoring of Urban Roadway Health: Utilizing GPR Techniques for Early Detection and Classification of Subsurface Cavity Diseases

Multisensor and Multiscale Data Integration Method of TLS and GPR for Three-Dimensional Detailed Virtual Reconstruction

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