Search

In order to address the impact of various parameters of non-metallic pipelines on the response of ground penetrating radar, the factors that affect the response of ground penetrating radar are identified. A forward model was established by combining the finite time domain difference method and the vector component finite difference method. Using the electromagnetic wave simulation software GPRMax3. 0, a large number of practical situations were simulated, and different antenna frequencies were used to detect the shape, material, burial depth, and other characteristics of different pipelines. The influence of different parameters of non-metallic pipelines on radar response was simulated using this model, where the diameter of the pipeline has a decisive impact on the echo intensity. The simulation results are consistent with the actual situation, proving the effectiveness of this model. [ABSTRACT FROM AUTHOR]

According to the key technology of TBM underground starting chamber group construction in metal mines, the design basis of TBM underground starting chamber group was analyzed, and the composition and layout of integrated assembly starting chamber group and split assembly starting chamber group, as well as the design and calculation method of structural parameters of each chamber were proposed. Taking the TBM project of a metal mine as an example, the structural parameters of the starting chamber group in the two schemes were obtained by comprehensively considering the TBM equipment, assembly and hoisting equipment, geological conditions and safety factors, etc. Finally, the optimal scheme was selected by analyzing the engineering quantity, construction period, etc. According to the optimal scheme, the key construction technologies of the TBM starting chamber group were introduced. The research results can provide reference for similar projects. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to quickly and accurately detect the internal defects and diseases of asphalt pavement, so as to take maintenance or other treatment measures in time to ensure road driving safety. At the same time, in order to promote the development of nondestructive testing technology for hidden diseases and defects in asphalt pavement, the existing nondestructive testing technology for internal defects of asphalt pavement was reviewed. The basic principles of ground penetrating radar, its application in asphalt pavement detection, the intelligent identification of ground penetrating radar spectrum, the detection principle of ultrasonic detection technology, the study of the attenuation law of ultrasonic wave and its application and research in the detection of internal defects in pavement were reviewed, the detection principle of infrared thermal imaging technology, nuclear densitometer, nuclear-free densitometer and Rayleigh wave method and the application and research in the detection of internal defects in asphalt pavement were summarized. The types of detection defects, advantages and disadvantages were discussed, and the existing problems and future development directions of each detection technology were discussed, so as to provide a reference and basis for the further application and research of nondestructive testing technology for internal defects of asphalt pavement. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ground penetrating radar (GPR) is a non-destructive exploration technology that utilizes high-frequency ultra-wideband signals to detect the distribution of subsurface objects and media. Benefiting from the advantages of non-destructiveness, high efficiency, and high resolution, GPR has been widely applied in underground defect detection task of urban roads. Illustrating the radar echo wave of subsurface structure, GPR B-scan images are a main means to detect underground disaster; however, compared to natural images, automatic interpretation of GPR B-scan ones is a more challenging task because of same objects with different spectra, different objects with same spectrum as well as heavy noise pollution. Aiming to improve the accuracy of subsurface disasters detection methods, a disasters classification network, i.e., MA-ResNeXt, based on ResNetXt50 is proposed by combining multi-dimensional attention mechanism, atrous space pyramid pool and multi-scale feature extraction structure. The proposed network is trained and tested on real GPR B-scan images of three common subsurface disasters, e.g., void, cavity underneath pavement (CUP) and loosely infilled void (LIV). The comparison results show that classification accuracy of the proposed network approaches 98.2%, and illustrate that the network can effectively realize accurate classification of underground disasters. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Earth Science (1001-8166) is the property of Advances in Earth Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

SignificanceSoil stands as the fundamental pillar of agricultural production, with its quality being intrinsically linked to the efficiency and sustainability of farming practices. Historically, the intensive cultivation and soil erosion have led to a marked deterioration in some arable lands, characterized by a sharp decrease in soil organic matter, diminished fertility, and a decline in soil's structural integrity and ecological functions. In the strategic framework of safeguarding national food security and advancing the frontiers of smart and precision agriculture, the march towards agricultural modernization continues apace, intensifying the imperative for meticulous soil quality management. Consequently, there is an urgent need for the rrapid acquisition of soil's physical and chemical parameters. Interdisciplinary scholars have delved into soil monitoring research, achieving notable advancements that promise to revolutionize the way we understand and manage soil resource.ProgressUtilizing the the Web of Science platform, a comprehensive literature search was conducted on the topic of "soil," further refined with supplementary keywords such as "electrochemistry", "spectroscopy", "electromagnetic", "ground-penetrating radar", and "satellite". The resulting literature was screened, synthesized, and imported into the CiteSpace visualization tool. A keyword emergence map was yielded, which delineates the trajectory of research in soil physical and chemical parameter detection technology. Analysis of the keyword emergence map reveals a paradigm shift in the acquisition of soil physical and chemical parameters, transitioning from conventional indoor chemical and spectrometry analyses to outdoor, real-time detection methods. Notably, soil sensors integrated into drones and satellites have garnered considerable interest. Additionally, emerging monitoring technologies, including biosensing and terahertz spectroscopy, have made their mark in recent years. Drawing from this analysis, the prevailing technologies for soil physical and chemical parameter information acquisition in agricultural fields have been categorized and summarized. These include: 1. Rapid Laboratory Testing Techniques: Primarily hinged on electrochemical and spectrometry analysis, these methods offer the dual benefits of time and resource efficiency alongside high precision; 2. Rapid Near-Ground Sensing Techniques: Leveraging electromagnetic induction, ground-penetrating radar, and various spectral sensors (multispectral, hyperspectral, and thermal infrared), these techniques are characterized by their high detection accuracy and swift operation. 3. Satellite Remote Sensing Techniques: Employing direct inversion, indirect inversion, and combined analysis methods, these approaches are prized for their efficiency and extensive coverage. 4. Innovative Rapid Acquisition Technologies: Stemming from interdisciplinary research, these include biosensing, environmental magnetism, terahertz spectroscopy, and gamma spectroscopy, each offering novel avenues for soil parameter detection. An in-depth examination and synthesis of the principles, applications, merits, and limitations of each technology have been provided. Moreover, a forward-looking perspective on the future trajectory of soil physical and chemical parameter acquisition technology has been offered, taking into account current research trends and hotspots.Conclusions and Prospects]Current advancements in the technology for rapaid acquiring soil physical and chemical parameters in agricultural fields have been commendable, yet certain challenges persist. The development of near-ground monitoring sensors is constrained by cost, and their reliability, adaptability, and specialization require enhancement to effectively contend with the intricate and varied conditions of farmland environments. Additionally, remote sensing inversion techniques are confronted with existing limitations in data acquisition, processing, and application. To further develop the soil physical and chemical parameter acquisition technology and foster the evolution of smart agriculture, future research could beneficially delve into the following four areas: Designing portable, intelligent, and cost-effective near-ground soil information acquisition systems and equipment to facilitate rapid on-site soil information detection; Enhancing the performance of low-altitude soil information acquisition platforms and refine the methods for data interpretation to ensure more accurate insights; Integrating multifactorial considerations to construct robust satellite remote sensing inversion models, leveraging diverse and open cloud computing platforms for in-depth data analysis and mining; Engaging in thorough research on the fusion of multi-source data in the acquisition of soil physical and chemical parameter information, developing soil information sensing algorithms and models with strong generalizability and high reliability to achieve rapaid, precise, and intelligent acquisition of soil parameters.

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Significance] Soil stands as the fundamental pillar of agricultural production, with its quality being intrinsically linked to the efficiency and sustainability of farming practices. Historically, the intensive cultivation and soil erosion have led to a marked deterioration in some arable lands, characterized by a sharp decrease in soil organic matter, diminished fertility, and a decline in soil's structural integrity and ecological functions. In the strategic framework of safeguarding national food security and advancing the frontiers of smart and precision agriculture, the march towards agricultural modernization continues apace, intensifying the imperative for meticulous soil quality management. Consequently, there is an urgent need for the rapid acquisition of soil's physical and chemical parameters. Interdisciplinary scholars have delved into soil monitoring research, achieving notable advancements that promise to revolutionize the way we understand and manage soil resource. [Progress] Utilizing the the Web of Science platform, a comprehensive literature search was conducted on the topic of "soil," further refined with supplementary keywords such as "electrochemistry", "spectroscopy", "electromagnetic", "ground-penetrating radar", and "satellite". The resulting literature was screened, synthesized, and imported into the CiteSpace visualization tool. A keyword emergence map was yielded, which delineates the trajectory of research in soil physical and chemical parameter detection technology. Analysis of the keyword emergence map reveals a paradigm shift in the acquisition of soil physical and chemical parameters, transitioning from conventional indoor chemical and spectrometry analyses to outdoor, real-time detection methods. Notably, soil sensors integrated into drones and satellites have garnered considerable interest. Additionally, emerging monitoring technologies, including bio-sensing and terahertz spectroscopy, have made their mark in recent years. Drawing from this analysis, the prevailing technologies for soil physical and chemical parameter information acquisition in agricultural fields have been categorized and summarized. These include: 1. Rapid Laboratory Testing Techniques: Primarily hinged on electrochemical and spectrometry analysis, these methods offer the dual benefits of time and resource efficiency alongside high precision; 2. Rapid Near-Ground Sensing Techniques: Leveraging electromagnetic induction, ground-penetrating radar, and various spectral sensors (multispectral, hyperspectral, and thermal infrared), these techniques are characterized by their high detection accuracy and swift operation. 3. Satellite Remote Sensing Techniques: Employing direct inversion, indirect inversion, and combined analysis methods, these approaches are prized for their efficiency and extensive coverage. 4. Innovative Rapid Acquisition Technologies: Stemming from interdisciplinary research, these include biosensing, environmental magnetism, terahertz spectroscopy, and gamma spectroscopy, each offering novel avenues for soil parameter detection. An in-depth examination and synthesis of the principles, applications, merits, and limitations of each technology have been provided. Moreover, a forward-looking perspective on the future trajectory of soil physical and chemical parameter acquisition technology has been offered, taking into account current research trends and hotspots. [Conclusions and Prospects] Current advancements in the technology for rapaid acquiring soil physical and chemical parameters in agricultural fields have been commendable, yet certain challenges persist. The development of near-ground monitoring sensors is con‐ strained by cost, and their reliability, adaptability, and specialization require enhancement to effectively contend with the intricate and varied conditions of farmland environments. Additionally, remote sensing inversion techniques are confronted with existing limitations in data acquisition, processing, and application. To further develop the soil physical and chemical parameter acquisition technology and foster the evolution of smart agriculture, future research could beneficially delve into the following four areas: Designing portable, intelligent, and cost-effective near-ground soil information acquisition systems and equipment to facilitate rapid on-site soil information detection; Enhancing the performance of low-altitude soil information acquisition platforms and refine the methods for data interpretation to ensure more accurate insights; Integrating multifactorial considerations to construct robust satellite remote sensing in‐ version models, leveraging diverse and open cloud computing platforms for in-depth data analysis and mining; Engaging in thorough research on the fusion of multi-source data in the acquisition of soil physical and chemical parameter information, developing soil in‐ formation sensing algorithms and models with strong generalizability and high reliability to achieve rapaid, precise, and intelligent acquisition of soil parameters. [ABSTRACT FROM AUTHOR]

Copyright of Railway Investigation & Surveying is the property of Railway Investigation & Surveying Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Zhengzhou University: Engineering Science is the property of Editorial Office of Journal of Zhengzhou University: Engineering Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In view of the disadvantages of time consuming and low efficiency caused by single frequency band of Ground Penetrating Radar (GPR) products, a dual-frequency integrated composite array antenna with center frequency of 400 MHz and 1 000 MHz and bandwidth of 200~1 500 MHz is designed and implemented, and is applied in Ultra-Wide Band (UWB)GPR system. The array antenna consists of three butterfly antennas with a center frequency of 400 MHz and six butterfly antennas with a center frequency of 1 000 MHz, and has the capability of simultaneous detection of dual frequency bands, which can realize the detection results of two different frequency bands in one survey line, overcome the problem of repeated detection of different frequencies of traditional GPR and enhance the practicability of GPR system. The proposed dual-frequency integrated GPR antenna has the characteristics of ultra-wideband, high gain and narrow beam. Its relative bandwidth is 153%, the maximum peak gain of 17.6 dBi is achieved in the whole bandwidth, and the narrowest half-power beam width is 7.6°. It provides a new antenna scheme for high resolution and high efficiency GPR applications. [ABSTRACT FROM AUTHOR]

Unmanned scraper is an important part of intelligent mine construction, in order to achieve unmanned underground mining in high-altitude and cold areas, this article summarizes the current development status of unmanned driving systems for scrapers both domestically and internationally .analyzes the relevant theories and key technologies of autonomous driving systems for scrapers, and summarizes them from the perspectives of trajectory deviation prediction technology for underground scrapers, autonomous driving multi deviation control technology, and collision prevention prediction and control technology. Taking Huatailong mine in Tibet as an example, the latest network communication technology 5G was used to build a 5G+scraper unmanned system. It is of great significance for the development of unmanned scraper systems in high-altitude and cold areas. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Geology / Gongcheng Dizhi Xuebao is the property of Journal of Engineering Geology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The epikarst zone is widely distributed in the karst area of Southwest China, and it is the intersection zone of four circles (lithosphere, atmosphere, biosphere and hydrosphere). It is sensitive to environmental changes, in which rapid chemical reactions and strong karst actions are likely to take place. It records much information on short-term environmental change. It also has the function of regulating and storing karst water, and thus can effectively provide water resources for residents in karst mountainous areas. Therefore, the exploration and interpretation of the structure of epikarst zone is of great significance to the study of water cycle and the storage function of epikarst zone. In this study, comprehensive geophysical methods such as high-density resistivity method, spontaneous potential method and ground penetrating radar method have been used to explore and interpret the spatial structure characteristics of epikarst zone in slope runoff field of Guohua town ecological experiment base in Pingguo City. The high-density resistivity method can obtain the electrical structure section of slope runoff field by data inversion, and divide karst development areas by electrical structure. As an important method to interpret the development position of strong runoff belt, the spontaneous potential method can obtain the spatial position of polarization source through data inversion, and the generation of polarization source is closely related to water flow and electrochemical reaction between water and surrounding rock. With high resolution, the ground penetrating radar method is effective to interpret the development thickness of epikarst zone. The high-density resistivity method and the spontaneous potential method can be used to detect and comprehensively interpret the spatial position of the strong runoff belt in slope runoff field, and the ground penetrating radar method can be used to detect the thickness of the epikarst zone in the slope runoff field. In this study, according to the resistivity inversion cross-section and polarization source inversion results, the spatial positions of three strong runoff zones have been comprehensively explained, and their development depths vary between 5 m and 10 m. The development depth of the epikarst zone has been interpretated by the ground penetrating radar image. According to the development characteristics of epikarst zone in this area, the antenna frequency of the ground penetrating radar has been set as 400 MHz, and the radar wave reflection time has been converted into depth with the combination of the relevant geotechnical dielectric parameters of rock and soil. The development depth of epikarst zone in the slope runoff field is about 2.5 m (about 50 ns, with the speed of 10 cm·ns-1) The lateral variation of development thickness is significant. The accurate depth needs to be calibrated by the results of velocity measurement through drilling. In addition, there are deep karst fractures in the northwest of the slope runoff field, which gradually descend to the southeast and gradually expand to the surface. The research results show that the location of polarization source obtained by the inversion of spontaneous potential data can directly indicate the location of groundwater; therefore, the spontaneous potential method is effective to detect karst water-bearing structures. Combined with the results of high-density resistivity inversion section, the development location and spatial characteristics of strong runoff belt can be accurately interpreted, and the ground penetrating radar can detect the development thickness of epikarst zone and the development of shallow karst fracture structure with high resolution. In short, the integration of ground penetrating radar method, high-density resistivity method and spontaneous potential method can effectively detect the structural characteristics of epikarst zone, address the multi-solution problem, and hence an effective means to interpret the thickness of epikarst zone and to detect the spatial distribution of strong runoff belt. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the background of ground penetrating radar (GPR) image contains a lot of noise, which leads to the difficulty of effective signal extraction and recognition, a GPR denoising method based on improved Markov random field combined with Otsu algorithm is proposed. Firstly, the Otsu algorithm was used to binarize the GPR image data, and the foreground and background images were divided. Then, the improved Markov random field combined with iterated conditional mode algorithm (ICM) was used to denoise the image, and the binary image containing only the effective signal was obtained. The binary image was combined with the noisy image, and the median filtering method was used to reduce the noise, finally the optimized GPR image was obtained. According to the experimental results, this method has a good effect on the ground penetrating radar data noise reduction and effective signal extraction. Compared with other traditional and original Markov random field denoising methods, it performs best in various GPR evaluation methods. Specifically, it has the highest fitting degree in the signal single-channel waveform contrast, the peak signal-tonoise ratio reaches 52. 528 1 dB, and the structural similarity is 0. 998 1. Meanwhile, the image waveform recognition become clearer by using the filter image which combined the binary image. Therefore, this method has a certain practical value in the use of GPR detection and flaw detection engineering projects. [ABSTRACT FROM AUTHOR]

In China, approximately 346.3 x 104 km² of the karst rocks are distributed, accounting for about one-third of the country's land area. Karst groundwater channels are common geological phenomena in concealed karst areas. Various karst caves and underground channels widely developed cause the complex groundwater system dominated by pipe flow, which promotes the transport of groundwater, soil, and rocks, resulting in complex geological issues for urban underground space development and utilization in karst areas. In these areas, ground collapse disasters occur from time to time. In geothermal areas, karst groundwater channels are often accompanied by frequent heat exchange, directly affecting the quality of geothermal development. Therefore, conducting exploration of karst underground channels is of great significance for the development of urban underground space and the prevention of geological disasters in karst areas. Due to the high degree of spatial variability of karst channels, it is a challenge for conventional two-dimensional detection methods to complete the geophysical imaging, which in turn results in the difficulty of conventional karst detection. Geophysical exploration is widely used due to its wide applicability, large detection depth, and accuracy. However, different geophysical methods have different advantages in terms of detection depth, resolution and practicality. The Ground Penetrating Radar has the characteristics of high efficiency and high resolution, but it is mainly applied to the exposed and shallow-covered karst due to factors such as limited penetration depth, irregular terrain, and clay content. Electromagnetic and seismic exploration can generate better results in the exploration of buried karst. In addition, microgravity exploration can be used to detect shallow karst caves and fill-type karst caves. Electrical resistivity tomography (ERT) is the most commonly used geophysical method for karst exploration, and has been applied to various karst geological environments, such as cave exploration, the exploration of water-filled karst groundwater channel, the detection of urban underground cavity, and engineering surveys. In this study, 3D ERT was used for fine detection of concealed karst underground channels in the urban area. Combining with geophysical numerical simulation and application examples, the effectiveness of 3D on karst underground channels with different filling types was analyzed. The research results show that 3D ERT has a significant improvement in data volume and resolution compared to 2D ERT. 3D ERT can more intuitively characterize the three-dimensional electrical structure characteristics of the target body and has advantages in imaging karst groundwater channels. Through the three-dimensional electrical imaging of the karst groundwater channel in Yuanquan village, Wuhan City, the groundwater migration characteristics of the low-temperature hot spring are revealed. The analyses of geophysical prospecting and drilling show that two low-temperature hydrothermal vent groups in this area are directly connected by karst underground channels and connected with north-west fault structures, reflecting a hydrodynamic process. In this process, deep hot water firstly circulates along the fault fracture zone to shallow karst channels, and after its horizontal migration at a certain distance, deep hot water exposes at the surface in the form of spring near the fracture zone, and the contact zone of carbonate rock and schist. In this study, the three-dimensional electrical structure imaging of karst groundwater channel near the hot spring point has been jointly realized by geophysical exploration and drilling, and the trends of fractured fault zone and karst channel have been displayed. Study results show that the low-temperature hydrothermal spring is connected to the karst groundwater system through deep faults. In view of this, it is proposed to carry out systematic geothermal explorationin the area to find out the hydrogeological conditions of hydrothermal spring, the groundwater circulation and heat interaction processes. In addition, the study results may provide support for the temperature increase of the hydrothermal spring and for the development of urban geothermal energy. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the management process of mining geological environment, it is found that some mining enterprises had obvious over-exploration activities, which were usually concealed later by backfilling mining pits with mixed soil and rocks. In order to investigate the illegal liability, the administration needs to scope the actual mining area and excessive amount of over mining. Since most part of the mine pit is covered by backfilled soil and rocks, it cannot be directly measured, needing engineering exploration to reveal the interface between backfilled soil and rocks and bedrock. Studies show that the high-density resistivity and ground penetrating radar adopted as geophysical means in the preliminary exploration on the backfilled limestone pit can infer the interface between the backfilled body and the bottom bedrock, and the pit boundary in the shallow coverage area, which can provide guidance for the layout and depth design of drilling hole. The comprehensive analysis of geophysical prospecting and drilling results can determine the interface between the backfilled and the bedrock, with the comparison to licensed mining scope calculating the over-mining amount. Drilling work verify that the geophysical inference results are relatively accurate, and the collaboration of the two approaches can significantly improve work efficiency and reduce exploration costs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ground Improvement is the property of Journal of Ground Improvement Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to eliminate underground blind areas in transmission line corridor operation and maintenance, timely discover hidden structural diseases inside the tower foundations and the surrounding underground environment, thus avoiding safety accidents such as ground collapse within the corridor,based on the efficient and nondestructive ground penetrating radar means, a transmission line corridor hidden disease identification model based on improved Faster R-CNN is proposed, and a method of expanding underground hidden disease detection data using generative adversarial network is proposed to reduce the difficulty of constructing datasets for the problem of insufficient sample size of existing ground-penetrating radar datasets.The experimental results show that the detection accuracy of the proposed model reaches 92.34%, which can effectively identify the hidden diseases in transmission line corridors in complex backgrounds. The research results can provide engineering application theoretical basis for the underground hidden danger detection of transmission line corridors in the future. [ABSTRACT FROM AUTHOR]

For the problem of strong clutter when using ground penetrating radar (GPR) for landmine detection, a low rank and sparse decomposition (LRSD) based method is proposed. The proposed method introduces weighted nuclear norm (WNN) into robust principle component analysis (RPCA) and combines randomized singular value decomposition (RSVD) with the alternating direction method of multipliers (ADMM) to solve the optimization function, which suppresses the clutter by treating the target image as sparse component and the clutter image as low rank component and enhance the accuracy and efficiency of the proposed algorithm. The experimental results show that the proposed method can significantly improve the signal-to-clutter ratio (SCR) of the imaging results and the computation efficiency is over five times than that of the RPCA, which demonstrates the efficiency in clutter mitigation. [ABSTRACT FROM AUTHOR]

Building sites are created by leveling hills and creating land in the hilly mountainous areas of collapsible loess. The deformation characteristics of the high slopes of excavation and filling and the internal properties of the soil at the exposed position of the boundary line are the key aspect of slope stability evaluation. To investigate the stability of the collapsible loess high slope for the Tongxin Miaoling transformer station from the important hub of the West-East power transmission project, this study conducted field detection tests using professional ground-penetrating radar (GPR) of model pulseEKKO PRO, Survey lines with lengths of 416 m and 372 m were laid at the top of the slope in the excavation area and the fill area. Meanwhile, survey lines of 15 m and 20 m in length were laid on both sides of the excavation and filling boundary. GPR is used to carry out detection work on all survey lines at 0.5 m intervals. The results show that the wave spectrum characteristics image of the high excavation slope is consistent with the soil distribution at the same location in the geological survey results. Meanwhile, its reflected wave is messier, which indicates that there are unloading cracks and sporadic fracture zones inside the slope. There is no abnormal reflective wave surface such as cracks and local subsidence on the high fill slope, and its filling soil is uniform. The original soil in the high fill slope area is self-weight collapsing loess, thus the soil of the high fill slope has potential risks. The boundary area of excavation and filling has a more obvious boundary line of excavation and filling, which has a slow slope and uniform transition. The detection waveform on the side of the boundary line is complex, with many types of lithology, and high soil compactness, while the right side has regular waveforms, single soil properties, low soil compactness, and differences in soil properties between excavation and filling.easily lead to unenen settlement. These results could provide a reference for the design and construction of the high side slope of the cutting hills to the backfill ditch project.

Ground-penetrating radar (GPR) is a non-destructive testing method used for identifying internal anomalies in roads. GPR often generates a massive amount of scan data during operation, which requires high technical skills and a heavy workload for interpretation and is typically completed manually. Moreover, the complexity of road structures and the diversity of anomalies increase the difficulty of image anomaly detection. In recent years, the rapid development of artificial intelligence (AI) technology has provided feasible technical solutions for automatic interpretation of GPR B-scan images based on AI. Common deep learning algorithms for object detection include RCNN(region-convolutional neural network) and YOLO( you only look once). While YOLOv3 has achieved some success in object detection, the YOLOv4 algorithm based on its improvements can further enhance detection capabilities. The impact of the improvement in YOLOv4 on the object detection and the ability of YOLOv4 improving the efficiency of detecting abnormal object in the GPR image was investigated. The results show that YOLOv4 with the network framework and algorithm improvements is more suitable for automatic detection of anomalies in GPR images. The trained YOLOv4 network meets the requirements of intelligent detection of abnormal object in GPR images and possesses the high practical value. [ABSTRACT FROM AUTHOR]

Wuhu Straddle-type Monorail Line 1 and Line 2 run through the main urban area of Wuhu along the north-south and east-west directions respectively, and the urban investigation environment and geotechnical conditions are complicated. In Wuhu viaduct station, the single-column large cantilever structure concept of "bridge construction in one" is used, and the continuous steel track beam bridge is used in the section, which has its special structural form. As a special standard of rail transit, straddle monorail has no specific description and technical requirements in the current survey standards, which requires higher requirements for the survey work. To solve the karst problem, the karst exploration methods were combined with ground electric method, geological radar (single hole radar, cross hole radar CT) and drilling. To solve the problem of soft soil, the methods of in situ test and laboratory test, such as lateral expansion of flat shovel, cross plate shear and static penetration were used. To solve the hydrogeological problems, the methods of hydrology investigation with "one drawing and three observations" hydrology experiment, long-term hydrology observation and laboratory experiment were adopted. The research shows that the comprehensive survey technology can fully identify the karst distribution and development characteristics, soft soil characteristics and mechanical property differences, accurately determine the hydrogeological parameters, and rationally optimize the anti-floating design. [ABSTRACT FROM AUTHOR]

In order to investigate the development scale and spatial morphology characteristics of karst in the sea area, ensure that shield tunneling can smoothly pass through the underwater karst area, and effectively reduce safety hazards during the construction process of underwater tunnels. In this paper, relying on the karst survey project in a certain section of Dalian Metro Line 5, the development of karst in the site area was first divided by the seismic reflection method and the transient electromagnetic method in the sea area, and then the cross hole elastic wave CT method was used to find out the characteristics and scale of single karst development, ultimately achieving the goal of high-precision detection of the scale of karst development, spatial morphological characteristics, etc. within the influence area of the submarine tunnel. The survey results indicate that: (1) The traditional water surface geophysical exploration method can divide karst development zones from a macroscopic perspective, using water seismic reflection method to divide 2 karst development zones, transient electromagnetic method to divide 36 karst development zones, and dividing the entire survey interval into 3 sections: karst micro development, karst medium development, and karst strong development; (2) Due to the constraints of seawater conductivity, traditional geophysical methods such as surface and inter hole electrical methods are not suitable for karst exploration in sea areas; (3) The cross hole elastic wave CT method can accurately detect the spatial morphology of individual karst in local areas, accurately scan the development of karst between two holes, and clearly reflect the relationship between karst caves and tunnel bodies on a two-dimensional profile. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Non-destructive testing of tree roots has the vast application potential to the root system evaluation of fruit and ancient trees for the better management of plant health. Among them, ground-penetrating radar (GPR) can be expected to nondestructively detect the tree roots, due to the portable and low-cost. However, the interpretation of GPR data is dependent mainly on the manual analysis, leading to the reduced automation and accuracy. Moreover, the clutters and noise that caused by soil heterogeneity can severely affect the accuracy of root detection and identification. In this study, a detection method was proposed for the clutter suppression and root parameter prediction of ground penetrating radar. The data collection was divided into two parts: the dataset and field test. The datasets consisted of simulated and synthesized real data. The roots with the radius ranging from 5 to 30 mm were randomly distributed within 300 mm underground. The field experiment was conducted in three sand pits. The soil heterogeneity was simulated to create the different moisture levels, when adding water into different parts in two of the dry sand pits. The rest sandpit was a condition of higher water content after heavy rainfall. At the same time, the roots were excavated to verify the model under real soil conditions. Four test pits contained the roots of different tree species, the different soil environments, as well as the different radii and depths. The attention mechanism was integrated into the U-net model, in order to enhance the capability in the clutter suppression and root target reflection restoration. A clutter suppression network was constructed to test the effectiveness of the model. The encoding-decoding structure of U-net was separated the target root hyperbolic reflection from the overall background. The attention mechanism enabled the network to better adaptively focus on the hyperbolic reflection of the target root system without identifying the clutter as the target reflection. The clutter suppression was realized for the original B-scan image to remove the adverse effects, due to the soil heterogeneity and radar antenna coupling. Furthermore, the network of root parameter prediction was constructed using residual blocks and inception. The multi-scale receptive field of inception was used to extract the global and local features, and simultaneously to predict the root radius and depth. The predicted results were obtained by parallel inputting the clutter suppressed image and the original B-scan image into the network. The effectiveness of the model was evaluated using datasets and field experiments. The test results of clutter suppression were evaluated using peak signal to noise ratio (PSNR) and structural similarity (SSIM), which were 39.42 dB and 0.991, respectively, better than before. The test results on datasets showed the mean absolute error (MAE) of 1.7 mm, and the coefficient of determination R² value of 0.914 for the root radius prediction, while the mean absolute error (MAE) of 6.3 mm and the R² value of 0.989 for the root depth prediction. The clutter suppression was also achieved in the better performance than the rest on the field data. The maximum prediction errors for the root radius and depth were 1.85, and 13.6 mm, respectively, where the total average relative error was 6.55%. Influencing factors were determined for the prediction effectiveness of ground-penetrating radar. The future research directions were pointed out as well. The findings can be applied to the actual prediction of root depth and radius of tree roots, particularly for the health administration of fruit trees and the protection of ancient trees.protection of ancient trees.protection of ancient trees. [ABSTRACT FROM AUTHOR]

At present, the application of bottom-dipping radar is more and more extensive, but the information interpretation of bottom-dipping radar profile is lack of systematic standard. The image characteristics of forward modeling of six typical underground target models: horizontal layered target, circular target, rectangular target, underground pipeline, local aquifer, and petroleum pollutants were discussed. The two-dimensional finite-difference time-domain method was used to construct the forward modeling model of six typical underground targets in the contaminated site, and the radar profile of the typical underground targets was obtained. The image recognition characteristics of each typical target in the forward simulation profile were further summarized, and the formation mechanism of clutter such as multiple waves and diffraction waves in the radar detection process was analyzed. Finally, the accuracy of ground penetrating radar graphic feature analysis was verified by drilling data of petroleum hydrocarbon polluted site. The research results provide a theoretical basis for the interpretation of reflected signals of ground penetrating radar and the identification of underground targets in practical work. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shenzhen University Science & Engineering is the property of Editorial Department of Journal of Shenzhen University Science & Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Directional borehole radar is a new type of ground penetrating radar applied to boreholes, which has the ability to identify the azimuth of target bodies around boreholes, and can realize three-dimensional fine detection of abnormal bodies. Quadruple array receiving radar is a form of directional radar, which uses the weak difference of signals received by four closely spaced receiving antennas to judge the direction of incident wave, and then infers the position of abnormal body' s reflection interface. On the basis of previous studies, a new data processing method was proposed for quadruple array receiving radar. This method was based on estimation spectrum rational invariance technique (ESPRIT) algorithm, which can quickly and accurately process and analyze array receiving antenna data, judge the azimuth of abnormal bodies, and therefore solve the key and difficult problem in the application of the quadruple array receiving radar. Compared with existing azimuth recognition algorithms, the proposed new data processing method does not have the problem of 180° azimuth confusion, and has obvious advantages in computing speed. Based on GprMax synthetic data, the feasibility of the proposed method was verified. [ABSTRACT FROM AUTHOR]

Copyright of Water Conservancy Science & Techonlogy & Economy is the property of Water Conservancy Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ground-penetrating radar will be disturbed by various noise signals in the actual use process, and to solve this problem, a ground-penetrating radar denoising was proposed based on wavelet adaptive thresholding method. Conventional wavelet thresholding algorithms for ground-penetrating radar B-scan images may cause image distortion due to the difference in wavelet coefficients before and after processing. In order to make the target signal clearer and eliminate interference such as noise, wavelet thresholds were improved by the way of selecting wavelet thresholds and the threshold function, and the thresholds were identified with the length of subbands of different layers of wavelet transform to achieve adaptive and accurate quantization of thresholds. The experimental results show that the method is applicable to ground-penetrating radar signal processing and improves the good continuity and stability of the threshold function compared with the ordinary wavelet thresholding algorithm, further improves the direct wave removal and noise reduction effects, and better preserves the details of the target image. Comparing the results with other methods shows that the algorithm proposed in this paper improves the peak signal-to-noise ratio and reduces the image entropy. The research results show that the method has a certain application value in the practical use case of ground-penetrating radar. [ABSTRACT FROM AUTHOR]

Building sites are created by leveling hills and creating land in the hilly mountainous areas of collapsible loess. The deformation characteristics of the high slopes of excavation and filling and the internal properties of the soil at the exposed position of the boundary line are the key aspect of slope stability evaluation. To investigate the stability of the collapsible loess high slope for the Tongxin Miaoling transformer station from the important hub of the West-East power transmission project, this study conducted field detection tests using professional ground-penetrating radar (GPR) of model pulse EKKO PRO, Survey lines with lengths of 416 m and 372 m were laid at the top of the slope in the excavation area and the fill area. Meanwhile, survey lines of 15 m and 20 m in length were laid on both sides of the excavation and filling boundary. GPR is used to carry out detection work on all survey lines at 0.5 m intervals. The results show that the wave spectrum characteristics image of the high excavation slope is consistent with the soil distribution at the same location in the geological survey results. Meanwhile, its reflected wave is messier, which indicates that there are unloading cracks and sporadic fracture zones inside the slope. There is no abnormal reflective wave surface such as cracks and local subsidence on the high fill slope, and its filling soil is uniform. The original soil in the high fill slope area is self-weight collapsing loess, thus the soil of the high fill slope has potential risks. The boundary area of excavation and filling has a more obvious boundary line of excavation and filling, which has a slow slope and uniform transition. The detection waveform on the side of the boundary line is complex, with many types of lithology, and high soil compactness, while the right side has regular waveforms, single soil properties, low soil compactness, and differences in soil properties between excavation and filling.easily lead to unenen settlement. These results could provide a reference for the design and construction of the high side slope of the cutting hills to the backfill ditch project. [ABSTRACT FROM AUTHOR]

Copyright of Water Conservancy Science & Techonlogy & Economy is the property of Water Conservancy Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Zhengzhou University (Natural Science Edition) is the property of Journal of Zhengzhou University (Natural Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Taking the rock slope of the subway deep foundation pit as the research object, elastic wave CT is used to preliminarily judge the type and spatial distribution of rock mass diseases in foundation pit, which is then verified by geological radar. Furtherly the a watershed algorithm is adopted to analyze the wave velocity distribution obtained by elastic wave CT in order to extract the detailed sound velocity change at the rock cave and delineate its range. On this basis, based on the coordinate information of elastic wave CT three-dimensional spatial wave velocity database, combined with the spatial coordinate information obtained by watershed algorithm, the modeling database is constructed, after imported into GOCAD software, the three-dimensional geological visualization model is established after processing and analysis. The rock mass disease model established in this paper is highly consistent with geological drilling, peephole imaging and field observation. The proposed rock disease identification method and modeling technology can not only provide an important reference for rock mass support but also provide a basis for water disaster prevention of urban underground engineering.

Ground-penetrating radar (GPR) is one of the emerging technologies for soil moisture measurement. However, the measurement accuracy is difficult to determine due to some influence factors including radar wave frequency, soil texture type, etc. The GPR equipment with 1000 MHz center frequency and the measurement method of common midpoint (CMP) were adopted in the research to collect radar wave raw data in the selected field area under arid soil and moist soil conditions. The transmitter and receiver antennas of the GPR equipment were moved 0.01 m respectively in opposite directions on each radar wave raw data collection. Therefore, a CMP radar image consisted of 100 pieces of radar wave raw data by increasing the antenna distance from 0 m to 2 m. Each radar wave raw data indicated that the radar waves were reflected in the reflective layer with different dielectric constant under the same antenna distance. And the reflected and refracted radar waves were acquired by the receiving antenna at different two-way travel time respectively, and recorded in the computer. The collection of CMP soundings aimed to determine the inversion accuracy, optimum inversion depth, effective inversion depth and optimal inversion model of soil moisture content at different depth ranges and adjacent reflective layers by GPR at field scale. The reflected and refracted radar wave data were extracted from the raw data. The velocities of the surface waves and reflected waves were obtained respectively from the line slope of the surface wave data and the hyperbolic curves fitting of the reflected wave data. In addition, the relative dielectric constant of the soil at specified depth were deduced according to the soil dielectric constant and its reflected wave velocity. Moreover, 4 different models including Topp, Roth, Herkelrath and Ferre were used to figure out the soil volumetric water content inversion. Meanwhile, the measured data of soil volumetric moisture content obtained by oven drying method were used to verify the accuracy of the inversion results. The results showed that the effective inversion depth of 1000 MHz GPR ranged from 0 to 50 cm. The best inversion depth was 50 cm in arid soil and 40 cm in moist soil. The Roth model had the best correlation and stability with the highest R2 was 0.750, the Root Mean Square Error (RMSE) was 0.0114 m3/m3 and the lowest Relative Error (RE) was 3.0%. The GPR could possess the capacity of quick, precise and non-destructive measurement of specified depth soil moisture in field scale. The inversion model of soil moisture content needs to be calibrated according to different soil conditions.

Copyright of Hydrogeology & Engineering Geology / Shuiwendizhi Gongchengdizhi is the property of Hydrogeology & Engineering Geology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

During the torrential rainstorm of July 20, 2021 in Zhengzhou, some dangerous situations such as water seepage and pit collapse occurred in the downstream slope of the main dam of Changzhuang Reservoir. In order to detect whether there is seepage potential in the dam body and find out the quality of the main dam, the comprehensive geophysical prospecting method combining with ground penetrating radar and high-density electrical method was used to detect and analyze the dam. According to the characteristics of the project and the location of the accident, ground penetrating radar was used on the upstream and downstream dam slopes and the dam crest, and the high density electrical method was used on the downstream dam slopes. The results show that the soil mass of the dam is generally uniform and dense within the detection range, and there is no obvious cavity defect or leakage channel. However, the shallow soil mass of downstream slope is relatively less dense, which may be an important factor for inducing dangerous situations such as seepage and pit collapse during the rainstorm. [ABSTRACT FROM AUTHOR]