3D GPR Research Articles

Evaluation of grouting effectiveness for Semi-Rigid pavement base layer cracks based on Time-Frequency domain signal characteristics of 3D GPR

This study aims to address the deficiency of rapid, comprehensive, and non-destructive methods for evaluating the effectiveness of grouting treatment on semi-rigid pavement base layer cracks. By integrating radar simulation with empirical measurements, we establish a comprehensive evaluation method for the grouting treatment effectiveness of pavement base layer cracks. Initially, we propose a GprMax simulation of crack models with varying grout-filled volumes, analyzing the time–frequency domain signal characteristics before and after grouting. Based on data sensitivity, thirteen time–frequency domain signal characteristics are selected as grading evaluation indicators. Subsequently, relying on an engineering case study, we conduct a graded evaluation of the grouting effect on base layer cracks, analyzing the correlation and weight of evaluation indicators to derive a comprehensive evaluation method. Field coring results confirm the accuracy of the comprehensive graded evaluation method.

Underground Target Extraction by Local Entropy Feature of Voxelized 3D Ground Penetrating Radar

Abstract. To solve the current problem of insufficient exploration of three-dimensional spatial information detected by 3D ground penetrating radar (3D GPR) and the data processing mainly based on the analysis and interpretation of two-dimensional slice images, a method is proposed to extract underground target based on the local entropy feature of discrete point clouds after the voxelization of 3D GPR data. First, the acquired 3D GPR data was voxelized into discrete three-dimensional point clouds. Then the local entropy feature of the voxelized point clouds over the entire region were calculated. The soil background and underground targets were distinguished by classifying them from multiple dimensions through Support Vector Machine (SVM). Finally, the urban road underground environment was taken as the research object, and this method was used for experimental analysis using measured data. The experimental results show that the accuracy of this method in extracting underground targets is as high as 90.1%, and the missing detection rate of missing underground targets is as low as 7.8%. The proposed method is accurate and effective, providing a new approach for 3D GPR to extract underground target.

A Multi-Level Robust Positioning Method for Three-Dimensional Ground Penetrating Radar (3D GPR) Road Underground Imaging in Dense Urban Areas

Three-Dimensional Ground Penetrating Radar (3D GPR) detects subsurface targets non-destructively, rapidly, and continuously. The complex environment around urban roads affects the positioning accuracy of 3D GPR. The positioning accuracy directly affects the data quality, as inaccurate positioning can lead to distortion and misalignment of 3D GPR data. This paper proposed a multi-level robust positioning method to improve the positioning accuracy of 3D GPR in dense urban areas in order to obtain more accurate underground data. In environments with good GNSS signals, fast and high-precision positioning can be achieved based on GNSS data using differential GNSS technology; in scenes with weak GNSS signals, high-precision positioning of subsurface data can be achieved by using GNSS and IMU as well as using GNSS/INS tightly coupled solution technology; in scenes with no GNSS signals, SLAM technology is used for positioning based on INS data and 3D point cloud data. In summary, this method ensures a positioning accuracy of 3D GPR better than 10 cm and high-quality 3D images of underground urban roads in any environment. This provides data support for urban road underground structure surveys and has broad application prospects in underground disease detection and prevention.

3D GPR 자료를 활용한 인공지능 기반 배관 탐지 시스템 개발 및 검증

3D GPR 자료를 활용한 인공지능 기반 배관 탐지 시스템 개발 및 검증

Critical Technical Problems of 3D GPR Road Cavity Detection Based on Vast Field Experiment Data Analysis

Utilizing 3D GPR to conduct road cavity detection can well prevent the occurrence of collapse. However, the problems existing in the application of 3D GPR in road cavity detection are not very clear. Hence, we have carried out more than 1000 km road cavity detection work and summarized the main points of data acquisition, processing and interpretation in engineering applications. The main points we found are related to the complexity of the pavement environment and the diversity of above and below ground interference sources, which are difficult to obtain in laboratory experiments. Then the solutions and ideas are put forward, aiming at accelerating the development of 3D GPR cavity detection technology in the field of engineering application.

Pretreatment patient-specific quality assurance prediction based on 1D complexity metrics and 3D planning dose: classification, gamma passing rates, and DVH metrics

PurposeHighly modulated radiotherapy plans aim to achieve target conformality and spare organs at risk, but the high complexity of the plan may increase the uncertainty of treatment. Thus, patient-specific quality assurance (PSQA) plays a crucial role in ensuring treatment accuracy and providing clinical guidance. This study aims to propose a prediction model based on complexity metrics and patient planning dose for PSQA results.Materials and methodsPlanning dose, measurement-based reconstructed dose and plan complexity metrics of the 687 radiotherapy plans of patients treated in our institution were collected for model establishing. Global gamma passing rate (GPR, 3%/2mm,10% threshold) of 90% was used as QA criterion. Neural architecture models based on Swin-transformer were adapted to process 3D dose and incorporate 1D metrics to predict QA results. The dataset was divided into training (447), validation (90), and testing (150) sets. Evaluation of predictions was performed using mean absolute error (MAE) for GPR, planning target volume (PTV) HI and PTV CI, mean absolute percentage error (MAPE) for PTV D95, PTV D2 and PTV Dmean, and the area under the receiver operating characteristic (ROC) curve (AUC) for classification. Furthermore, we also compare the prediction results with other models based on either only 1D or 3D inputs.ResultsIn this dataset, 72.8% (500/687) plans passed the pretreatment QA under the criterion. On the testing set, our model achieves the highest performance, with the 1D model slightly surpassing the 3D model. The performance results are as follows (combine, 1D, and 3D transformer): The AUCs are 0.92, 0.88 and 0.86 for QA classification. The MAEs of prediction are 0.039, 0.046, and 0.040 for 3D GPR, 0.018, 0.021, and 0.019 for PTV HI, and 0.075, 0.078, and 0.084 for PTV CI. Specifically, for cases with 3D GPRs greater than 90%, the MAE could achieve 0.020 (combine). The MAPE of prediction is 1.23%, 1.52%, and 1.66% for PTV D95, 2.36%, 2.67%, and 2.45% for PTV D2, and 1.46%, 1.70%, and 1.71% for PTV Dmean.ConclusionThe model based on 1D complexity metrics and 3D planning dose could predict pretreatment PSQA results with high accuracy and the complexity metrics play a leading role in the model. Furthermore, dose-volume metric deviations of PTV could be predicted and more clinically valuable information could be provided.

A Multimodal Research Approach to Assessing the Karst Structural Conditions of the Ceiling of a Cave with Palaeolithic Cave Art Paintings: Polychrome Hall at Altamira Cave (Spain).

Integrating geomatics remote sensing technologies, including 3D terrestrial laser scanning, unmanned aerial vehicles, and ground penetrating radar enables the generation of comprehensive 2D, 2.5D, and 3D documentation for caves and their surroundings. This study focuses on the Altamira Cave's karst system in Spain, resulting in a thorough 3D mapping encompassing both cave interior and exterior topography along with significant discontinuities and karst features in the vicinity. Crucially, GPR mapping confirms that primary vertical discontinuities extend from the near-surface (Upper Layer) to the base of the Polychrome layer housing prehistoric paintings. This discovery signifies direct interconnections helping with fluid exchange between the cave's interior and exterior, a groundbreaking revelation. Such fluid movement has profound implications for site conservation. The utilization of various GPR antennas corroborates the initial hypothesis regarding fluid exchanges and provides concrete proof of their occurrence. This study underscores the indispensability of integrated 3D mapping and GPR techniques for monitoring fluid dynamics within the cave. These tools are vital for safeguarding Altamira, a site of exceptional significance due to its invaluable prehistoric cave paintings.

Study on the interlayer bonding state of an asphalt pavement based on the stacking peak ratio method

The interlayer bonding of an asphalt pavement significantly influences the mechanical properties and long-term durability of the pavement structure. In order to develop a rapid and comprehensive evaluation method for assessing the interlayer condition of asphalt pavements using 3D GPR, we propose the stacking peak ratio (SPR) method. This method involves stacking the ratio between the amplitude peak of the interlayer and that of surface reflection to evaluate the interlayer state. Comparative analysis with direct shear tests and field measurements leads us to draw several conclusions: the optimal test parameters for the SPR method are a stacking peak ratio at 35 ns with a residence time of 1 us; the SPR method is compatible with various bonding materials and pollution layers, demonstrating its ability to effectively assess the bonding state of asphalt pavements; field tests further validate that the SPR approach can identify insufficient layer bonding and predict potential flaws in advance. Through our test findings and data analysis, it is evident that this SPR approach provides theoretical support and technological assistance for promptly evaluating the bonding status in asphalt pavements.

Non-destructive prediction techniques for asphalt mixture based on back propagation neural networks

ABSTRACT The density of the asphalt mixture surface is an important indicator to evaluate the quality of construction and is of great importance to ensure the quality of construction and maintain the long-term serviceability of the pavement. The 3D ground-penetrating radar (3D GPR) and density prediction model can achieve rapid and continuous prediction of the density of asphalt pavement. In this study, a back propagation neural network (BPNN) density prediction model was established and combined with 3D GPR to conduct field experiments on a new asphalt concrete mid-surface layer to compare the density values obtained by the coring method in order to verify the model performance. The results show that the BPNN prediction model established in this study has good application to the overall density diagnosis of the road in the field. The average prediction error of the BPNN density prediction model is 0.184%, which is highly reproducible in practical applications.

Study on Crystallization Mechanism of Asphalt Mixture in Bridge Deck Pavement

This study focuses on unknown crystal precipitates from an asphalt mixture used in bridge deck pavement layers. X-ray fluorescence spectroscopy was used to analyze the composition and source of crystals in the asphalt mixture used in bridge deck pavement, and infiltration tests, porosity tests, splitting tests and multi-wheel rutting tests were carried out to determine the precipitation area and non-precipitation area to explain the influence of crystals on the road performance of an asphalt pavement. A nuclear-free densitometer and 3D ground-penetrating radar (3D GPR) were used to detect the porosity and thickness uniformity of the whole section to study the formation mechanism of crystals. The results showed that the main components of crystals were water molecules, while the rest mainly came from machine-made sand, and there was no significant difference in pavement performance in the areas where crystals precipitated. The crystals were mainly caused by rainwater penetrating into the pavement through coarse segregation areas and collecting in the depression of the lower bearing layer. Under high temperature, the solution precipitated out of the pavement and formed crystals.

3D GPR Model in the Military District of San Giacomo Degli Spagnoli (Palermo)

The georadar method was used to try to find some anthropic structures in a large square inside the Carabinieri barracks in the former military complex of San Giacomo degli Spagnoli in Palermo (Italy). These investigations are part of a broader context of a study of the entire area. The purpose of the investigations is to try to understand if under the ground there are the remains of an ancient horse passage that connected the Royal Palace of Palermo with the sea gate of the city. Furthermore, in the Middle Ages, on the site of the present square, there were most likely two churches, which no longer exist, as evidenced by numerous historical testimonies. One of the two, San Giacomo la Mazara, is known to have was placed right in front of the church of San Paolo, the subject of previous investigations. The investigations carried out on the main square of the military district allowed us to reconstruct a 3D georadar model in which numerous anomalies are highlighted. Some superficial anomalies have been attributed to the presence of sub-services, the deeper ones could be caused by the remains of the medieval underground way or those of the no longer existing medieval churches, but identifying their true nature requires further investigations and archaeological tests.

Pavement Distress Detection Using Three-Dimension Ground Penetrating Radar and Deep Learning

Three-dimensional ground penetrating radar (3D GPR) is a non-destructive examination technology for pavement distress detection, for which its horizontal plane images provide a unique perspective for the task. However, a 3D GPR collects thousands of horizontal plane images per kilometer of the investigated pavement. The existing detection methods using GPR images are time-consuming and risky for subjective judgment. To solve the problem, this study used deep learning methods and 3D GPR horizontal plane images to detect pavement structural distress, including cracks, repairs, voids, poor interlayer bonding, and mixture segregation. In this study, two deep learning methods, called CP-YOLOX and SViT, were used to achieve the aim. A dataset for anomalous waveform localization (3688 images) was first created by pre-processing 3D-GPR horizontal plane images. A CP-YOLOX model was then trained to localize anomalous waveforms. Five SViT models with different numbers of encoders were adopted to perform the classification of anomalous waveforms using the localization results from the CP-YOLOX model. The numerical experiment results showed that 3D GPR horizontal plane images have the potential to be an assistant for pavement structural distress detection. The CP-YOLOX model achieved 87.71% precision, 80.64% mAP, and 33.57 sheets/s detection speed in locating anomalous waveforms. The optimal SViT achieved 63.63%, 68.12%, and 75.57% classification accuracies for the 5-category, 4-category, and 3-category datasets, respectively. The proposed models outperformed other deep learning methods on distress detection using 3D GPR horizontal plane images. In the future, more radar images should be collected to improve the accuracy of SViT.

Evaluation of Concrete Bridge Deck Condition Using 3D GPR System

Evaluation of Concrete Bridge Deck Condition Using 3D GPR System

Use of NDT systems to investigate pavement reconstruction needs and improve maintenance treatment decision-making

ABSTRACT The objective is to improve the accuracy of the test results and establish a maintenance treatment decision-making system using the non-destructive testing (NDT) technology. Firstly, the evaluation unit length was theoretically determined and statistically verified. Secondly, the test frequency of falling weight deflector (FWD) test was statistically analysed and the deflection acceptance criterionwas obtained based on the probability density distribution curve. Meanwhile, the relationship between the FWD deflection and the pavement internal damage obtained by drilling was analysed. Subsequently, the test parameters of the three-dimensional ground-penetrating radar (3D GPR) were optimised by using the non-reference image quality assessing technology. Followed, pavement internal damage index of GPR was proposed for locating the defect structural layer. Lastly, the decision-making systemwas established. Results showed that the suitable evaluation unit length is 20 m, the deflection test frequency is no more than 10 m/point, the deflection accept criterion is 29.5 (0.01 mm) with 95% reliability and the optimal detection parameters of GPR is 1 cm, 10 µs and 25 ns respectively. The established decision-making system fully considering the surface and the interior conditions as well as the functional and structural conditions can effectively guide the maintenance plan formulation for similar reconstruction and expansion projects.

Plastic scintillation dosimeter with a conical mirror for measuring 3D dose distribution.

To test the measurement technique of the three-dimensional (3D) dose distribution measured image by capturing the scintillation light generated using a plastic scintillator and a scintillating screen. Our imaging system constituted a column shaped plastic scintillator covered by a Gd2 O2 S:Tb scintillating screen, a conical mirror and a cooled CCD camera. The scintillator was irradiated with 6 MV photon beams. Meanwhile, the irradiated plan was prepared for the static field plans, two-field plan (2F plan) and the conformal arc plan (CA plan). The 2F plan contained 16 mm2 and 10 mm2 fields irradiated from gantry angles of 0° and 25°, respectively. The gantry was rotated counterclockwise from 45° to 315° for the CA plan. The field size was then obtained as 10 mm2 . A Monte Carlo simulation was performed in the experimental geometry to obtain the calculated 3D dose distribution as the reference data. Dose response was acquired by comparing between the reference and the measurement. The dose rate dependence was verified by irradiating the same MU value at different dose rates ranging from 100 to 600 MU/min. Deconvolution processing was applied to the measured images for the correction of light blurring. The measured 3D dose distribution was reconstructed from each measured image. Gamma analysis was performed to these 3D dose distributions. The gamma criteria were 3% for the dose difference, 2mm for the distance-to-agreement and 10% for the threshold. Dose response for the scintillation light was linear. The variation in the light intensity for the dose rate ranging from 100 to 600 MU/min was less than 0.5%, while our system presents dose rate independence. For the 3D dose measurement, blurring of light through deconvolution processing worked well. The 3D gamma passing rate (3D GPR) for the 10 × 10 mm2 , 16 × 16 mm2 , and 20 × 20 mm2 fields were observed to be 99.3%, 98.8%, and 97.8%, respectively. Reproducibility of measurement was verified. The 3D GPR results for the 2F plan and the CA plan were 99.7% and 100%, respectively. We developed a plastic scintillation dosimeter and demonstrated that our system concept can act as a suitable technique for measuring the 3D dose distribution from the gamma results. In the future, we will attempt to measure the 4D dose distribution for clinical volumetric modulated arc radiation therapy (VMAT)-SBRTplans.

Highlighting the Potential of 3D ERT by Comparing its Results with GPR and the Excavation Map of a Roman Building

– Comparative measurements and analysis of 3D ERT and GPR results. – Evaluation of different ERT data processing methods.

Analysis of 2D and 3D GPR responses in the Federal University of Paraná Forensic Geophysics Controlled Site – a Case Study

ABSTRACT. In 2016, the Laboratory for Research in Applied Geophysics (LPGA), at the Federal University of Paraná, in partnership with the Federal Police of the State of Paraná and the University of Brasília built a Forensic Geophysics Controlled Site (FGCS-UFPR) to calibration of the applied geophysical method and strengthen forensic sciences in the State of Paraná. In the FGCS, several objects that simulate forensic, archaeological and paleontological targets were installed at extremely shallow depths. The materials were covered with clayey soil, typical of the region, and in some pits, fine sandy sediments were deposited. This study aims to verify the 2D and 3D responses of the ground penetrating radar (GPR) method applied to targets installed in the FGCS, in a post-precipitation period. In the acquisition of GPR data, a 700 MHz shielded antenna was used, with parallel 2D profiles and spaced 0.1 meters. The results indicated that the high clay content present in the soil, below 0.5 meters deep, caused a high attenuation of the electromagnetic signal and defined patterns of reflectors associated with the targets, excavations and the investigated environment. Thus, only targets with high electrical impedance were visualized in 2D and 3D GPR images.Keywords: ground penetrating radar, clay soil, targets, forensic sciences, archaeogeophysics. Análise dos resultados 2D e 3D de GPR no Sitio Controlado de Geofísica Forense da UFPRRESUMO. Em 2016, o Laboratório de Pesquisas em Geofísica Aplicada (LPGA), da Universidade Federal do Paraná, em parceria com a Polícia Federal do Paraná e a Universidade de Brasília, instalou um Sítio Controlado de Geofísica Forense (SCGF-UFPR) para a calibração do método geofísico aplicado e o fortalecimento das ciências forenses no Estado do Paraná. No SCGF foram instalados, em profundidades extremamente rasas, diversos objetos que simulam alvos forenses, arqueológicos e paleontológicos. Os materiais foram recobertos com solos argilosos, típicos da região, e em algumas cavas foram depositados sedimentos arenosos finos. Este estudo objetiva a verificação das respostas 2D e 3D do método radar de penetração no solo (GPR) aplicada aos alvos instalados no SCG, em um período pós-precipitação pluviométrica. Nas aquisições de dados de GPR foi aplicada a antena blindada de 700 MHz, com perfis 2D paralelos e equiespaçados em 0,1 metro. Os resultados indicaram que o alto teor de argila presente no solo, abaixo de 0,5 metro de profundidade, causou uma elevada atenuação do sinal eletromagnético e definiu-se padrões de refletores associados aos alvos, as escavações e ao meio investigado. Assim, apenas os alvos com alta impedância elétrica foram visualizados nas imagens GPR 2D e 3D.Palavras-chave: ground penetrating radar, solo argiloso, artefatos, ciência forense, arqueogeofísica.

Studying the Construction of Floor Mosaics in the Roman Villa of Pisões (Portugal) Using Noninvasive Methods: High-Resolution 3D GPR and Photogrammetry

Over the past decade, high-resolution noninvasive sensors have been widely used in explorations of the first few meters underground at archaeological sites. However, remote sensing actions aimed at the study of structural elements that require a very high resolution are rare. In this study, layer characterization of the floor mosaic substrate of the Pisões Roman archaeological site was carried out. This work was performed with two noninvasive techniques: 3D ground penetrating radar (3D GPR) operating with a 1.6 GHz central frequency antenna, which is a very high-resolution geophysical method, and photogrammetry with imagery obtained by an unmanned aerial vehicle (UAV), which is a very high-resolution optical method. The first method allows penetration up to 30–40 cm depth and 3D models can be obtained, and with the second method, very high detail surface images and digital surface models can be obtained. In this study, we analyze a combination of data from both sensors to study a portion of the floor mosaic of the Pisões Roman Villa (Beja, Portugal) to obtain evidence of the inner structure. In this context, we have detected the main structural levels of the Roman mosaic and some internal characteristics, such as etched guides, internal cracking, and detection of higher humidity areas. The methodology that we introduce in this work can be referenced for the documentation of ancient pavements and may be used prior to carrying out preservation activities. Additionally, we intend to show that a Roman mosaic, understood as an archaeological structure, does not consist of only beautiful superficial drawings defined by the tesserae, but these mosaics are much more complex elements that must be considered in their entirety for preservation.

GPR imaging criteria

GPR has been widely acknowledged as an effective and efficient technique for imaging the subsurface. But the process of constructing 3D GPR images (C-scans) is still subjective and mainly relies upon the operator's knowledge and experience. This study reviews the parameters that affect GPR imaging quality: namely, profile spacing (PS), slice thickness (ST) and interpolations. Feature characteristics that have a crucial influence on imaging quality were also identified. Through conducting 25 carefully designed empirical experiments on concrete as well as subsurface structures, the relationship between 3D imaging parameters and feature characteristics were observed. A general workflow was derived for GPR C-scan generation, which is analogous to the typical signal processing steps used in 2D radargram signal processing (Jol, 2009). Empirical values in workflow were based on the retrieval of known ground-truth data and comparison with the processed images, i.e. the closest to reality. Unlike 2D processing, the workflow for 3D is feature-oriented and case-specific, and the proposed workflow gives guidelines on suitable ranges for 3 major parameters when used in a variety of applications. It was identified that feature shapes and the ratios of feature size to radar footprint are of vital importance. With the proposed flowchart, the often vague “survey experience” is parametrized and standardized, and the upper and lower limits governing the generation of objective and trustworthy 3D GPR images are defined. This workflow for GPR 3D slice imaging also paves the way for GPR feature extraction and change detection commonly adopted in remote sensing.

Indirect preservation of Egyptian historical sites using 3D GPR survey

Non-invasive geophysical techniques are used to collect information about the environmental risks that threaten the historical sites in Egypt and indirectly preserve them. In this study the modern 3D-GPR imaging at two important Egyptian sites was applied for preservation purposes. The first site is the internal Piazza of Al-Azhar Mosque, while the second site is the proposed route through which the Ramesses-II statue will be transported to the main entrance of the Grand Egyptian Museum. The 3D-GPR surveys were performed using the 100 MHz GSSI antenna at Al-Azhar Piazza and the Hi-Mode IDS GPR system with 200 and 600 MHz dual antenna at the Grand Egyptian Museum. The analysis and interpretation of the 3D-GPR data at the first site led to image large voids and walls objects, which are very likely to represent shallow water tanks that were frequently used in the past. One main water tank was recently discovered at the southern part of the piazza, which causes water leakage to the walls of Al-Azhar Mosque. Moreover, the GPR results at the second site have showed that the proposed route is totally covered by sand and has neither cracks nor cavities or any other archeological features. There is only a PVC water pipe, which is buried at a relatively shallow depth of 0.25 m. Such PVC pipe might collapse during the transportation of Ramesses-II Statue and should be taken into consideration.