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Urban and offshore subterranean comprehensive pipelines are currently utilized frequently as infrastructure for fitting different engineering pipelines used for electricity, signal transmission, natural gas, petroleum, heating, water supply, and drainage systems. This study utilizes the finite element limit analysis (FELA) and artificial neural network (ANN) to evaluate the pull-out capacity factor of the buried rectangular box carrying the pipelines with internal inclined force in cohesive soil. In FELA, rigorous upper bound and lower bound solutions are performed to achieve the exact result. In this study, a dimensionless parametric analysis is carried out by considering the effect of five parameters viz. buried depth ratio, width-depth ratio, overburden factor, internal inclination angles, and interface factor on the pull-out capacity factor of a buried rectangular box, which can be called as a rectangular pipeline. Two significant samples of the investigated parameters are selected to evaluate the soil failure pattern (failure envelope) using the shear dissipation of soil failure for the buried rectangular pipeline subjected to inclined loading. Using the FELA results, the predictive equations are proposed using ANN, and then sensitivity analysis is performed to examine the sensitivity of each investigated essential parameter on the stability of the underground rectangular pipeline. The predictive ANN model for the buried rectangular pipe subjected to inclined loading is presented as design charts for practice and further investigation. [ABSTRACT FROM AUTHOR]

In advancing “smart city” initiatives, multi‐functional sensing devices are crucial for the structural health monitoring (SHM) of key infrastructures. This study presents a self‐sensing sealing electronic gasket (e‐gasket) featuring multi‐modal interdigitated‐electrode‐based sensors for underground pipeline damage assessments, via simultaneously detected distribution information of contact pressure and relative humidity (RH). Detecting performance is enhanced through functional surface coatings and optimized pore size of the porous foam layer. An equivalent decoupling model for precise detection is established by analyzing the electrical responses of capacitance and impedance, and a rough estimation method relying on relative response is investigated to reduce the energy consumption and enhance monitoring efficiency. It demonstrates excellent multi‐modal sensing capabilities, repeatability, and stability over the long term. Experimental results verify the effectiveness in condition detection, fault classification, damage severity assessment, and early warning functions of the e‐gasket, enabling comprehensive SHM. [ABSTRACT FROM AUTHOR]

The mathematical modeling of the dynamics of a two-layer shallow pipeline under the influence of transport load (the load created by an object moving along the pipeline) has been successfully resolved. The pipeline is represented as an extended circular cylindrical two-layer shell with a thin inner (bearing) layer and a thick outer (enclosing) layer situated in an elastic half-space. Dynamic equations of elasticity theory using Lamé potentials are utilized to describe the motion of the half-space and the enclosing layer of the shell. The vibrations of the bearing layer of the shell are described by the classical equations of the theory of shells. Numerical experiments have considered the case of a moving axisymmetric cylindrical normal load applied to a pipeline (without an enclosing layer and with an enclosing layer of varying thickness and material stiffness). It was demonstrated that if the material of the enclosing layer of the pipeline is more rigid than that of the rock mass, the dynamic effect of the moving load on the rock mass is reduced. [ABSTRACT FROM AUTHOR]

To address low detection accuracy and speed due to the multisolvability of the ground‐penetrating radar signal, we proposed a novel centralized feature pyramid‐YOLOv6l–based model to enhance detection precision and speed in road damage and pipeline detection. The centralized feature pyramid was used to obtain rich intra‐layer features and improve the network performance. Our proposed model achieves higher accuracy compared with the existing detection models. We also built two new evaluating indexes, relative average precision and relative mean average precision, to fully evaluate the detection accuracy. To verify the applicability of our model, we conducted a road field detection experiment on a ground‐penetrating radar dataset we collected and found that the proposed model had good performance in increasing detection precision, achieving the highest mean average precision compared with YOLOv7, YOLOv5 and YOLOx models, with relative mean average precision and frame rate per second at 16.38% and 30.5%, respectively. The detection information for the road damage and pipeline were used to conduct three‐dimensional imaging. Our model is suitable for object detection in ground‐penetrating radar images, thereby providing technical support for road damage and underground pipeline detection. [ABSTRACT FROM AUTHOR]

Preserving the structural integrity of critical infrastructure systems necessitates a heightened focus on fortifying the protection of underground pipelines. To this end, this paper presents an innovative approach, namely the Multi-Sample Joint Localization Method (MSJLM) utilizing Cross-Correlation Convolutional Neural Networks (CC-CNN), aimed at precisely localizing intrusion sources in the vicinity of underground pipelines. Traditional techniques for detecting and pinpointing pipeline intrusions primarily rely on a single sensor monitoring point, which is susceptible to inherent errors and constraints. In contrast, the MSJLM proposed in this study leverages data from multiple samples, integrating diverse data sources through correlation analyses to elevate precision and reliability. The utilization of the CC-CNN framework for processing aggregated data has proven highly successful in extracting spatial features and identifying patterns. Furthermore, the effectiveness of this method is corroborated through validation via a pile-driving model test. [ABSTRACT FROM AUTHOR]

Detection of underground natural gas pipeline micro-leakage based on unmanned aerial vehicle (UAV) hyperspectral remote sensing and GIS. Hyperspectral images can indirectly detect underground natural gas pipeline micro-leakage through spectral and spatial variation characteristics of surface vegetation. However, most of existing studies were based on ground-mounted platforms, which could only perform small-range single-point detection and might occur misidentifications. UAV hyperspectral remote sensing can allow wide-range detection of surface vegetation. Moreover, underground pipeline distribution GIS data can provide prior knowledge about leakage points to exclude misidentifications. Therefore, a natural gas pipeline micro-leakage experiment was set up. UAV hyperspectral images of grasslands and pipeline distribution vector data were obtained, which led to a proposed new wide-range multi-points detection methodology of underground natural gas micro-leakage. Firstly, the vegetation identification index (WVI) $\left({{R_{470}} + {R_{674}}} \right)/\left({{R_{555}} + {R_{750}}} \right)$R470+R674/R555+R750 was designed based on WOA–VMD (whale optimization algorithm – variational modal decomposition) to segment and extract the vegetation stress zones. Then, UAV- and GIS-based natural gas micro-leakage vegetation stress identification model was constructed to obtain the leak points of natural gas micro-leakage. Finally, the recognition ability was evaluated by comparing with three stress vegetation identification indices proposed in previous studies. The result showed that there was no missing or false detection in identification results; the identification and positioning effect was better than other indices, which could meet the practical application requirements. [ABSTRACT FROM AUTHOR]

High-accuracy deformation monitoring is crucial for investigating landslide–pipeline interaction problems, in which the fiber optic nerve system (FONS) holds enormous potential. This paper presents a theoretical framework for interpreting landslide–pipeline interactions using the FONS and proposes a novel method for calculating characteristic parameters of pipe–soil interfaces based on distributed strain measurements. The feasibility of this method is validated through a full-scale model test, and its application for studying pipeline behaviors is demonstrated in the Xinpu landslide, situated in the Three Gorges Reservoir region, China. The field monitoring results reveal that short-duration, high-intensity rainfall events triggered immediate acceleration of landslide movements, leading to pipeline elongation and flexure. Strain measurements of the underground pipeline allow for the identification of the local slipping interface of the landslide. Furthermore, the relationships between reservoir water level (RWL) fluctuations, rainfall events, landslide deformation, and the structural response of the pipe are analyzed. The findings suggest that the deformation of the landslide in the leading and middle parts exhibits high correlations with the combined effect of rainfall and RWL drawdown. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate the presence of benzene in the ground and drinking water in the eastern Niger Delta, where multiple oil and gas production facilities are present. Samples from drinking water wells were collected for measurements of benzene, toluene, ethylbenzene, and xylenes (BTEX). Additionally, the dissolved organic carbon (DOC) concentration was determined for the first time to establish the groundwater's total hydrocarbon and non-hydrocarbon load. The groundwater BTEX and benzene levels were up to 3904 µg/L and 3500 µg/L, respectively. DOC concentrations were up to 49 mg/L. The highest benzene concentrations were detected in wells near an underground petroleum pipeline. However, the concentrations decreased with distance from the pipeline to levels less than 0.1 µg/L. Despite benzene contamination, the aquifer has shown promising aerobic attenuation potential, having up to a 7.5 (95%) mg/L DO level and 2.11 mg/L BTEX biodegradation capacity for DO. However, the high groundwater temperature of up to 32.5 °C may weaken attenuation. The benzene and BTEX point attenuation rates ranged from 0.128 to 0.693 day−1 and 0.086 to 0.556 day−1, respectively. Hence, by natural attenuation alone, up to 66.5 and 85 years would be required to reach Nigeria's groundwater benzene and BTEX remediation goals, respectively. [ABSTRACT FROM AUTHOR]

Coal seam mining causes fracture and movement of overlying strata in goaf, and endangers the safety of surface structures and underground pipelines. Based on the engineering geological conditions of 22,122 working face in Cuncaota No.2 Coal Mine of China Shenhua Shendong Coal Group Co., Ltd. a similar material model test of mining overburden rock was carried out. The subsidence of overburden rock was obtained through the full-section strain data of distributed optical fiber technology, and the characteristics of mining surface subsidence were studied. The Weibull model was used to adjust the mathematical form of the first half of the surface subsidence curve via the MMF function. On this basis, the prediction model of coal seam mining surface subsidence was established, and the parameters of the prediction model of surface subsidence were determined. The test results show that with the advancement of coal seam mining, the fit goodness of the surface subsidence prediction curve based on the MMF optimization model reaches 0.987. Compared with the measured values, the relative error of the surface subsidence prediction model is reduced to less than 10%. The model displays good prediction accuracy. The time required for settlement stability in the prediction model is positively correlated with parameter a and negatively correlated with parameter b. The research results can be further extended to the prediction of overburden "three zones" subsidence, and provide a scientific basis for the evaluation of surface subsidence compression potential in coal mine goaf. [ABSTRACT FROM AUTHOR]

This investigation explores the erosion dynamics in sandy soils triggered by underground pipeline fractures, applying transparent soil technology for visualization. Through this approach, the erosion process within the transparent soil model was meticulously recorded using photography, enabling the quantitative analysis of collapse pit dimensions over time. Results reveal that soil erosion primarily manifests directly above the pipeline fracture, varying significantly with hydraulic conditions. In scenarios devoid of water flow within the pipeline, an increase in collapse pit depth is halted, attributed to the accumulation and blockage of soil particles at the fracture point. Contrastingly, under half-pipe and full-pipe flow conditions, the depth of the collapse pit swiftly reaches the fracture site. The flow of water notably escalates the expansion rate of the erosion pit, especially above the rupture, leading to continuous enlargement of the central area and subsequent secondary and tertiary collapses at the pit's apex. The study further identifies the impact of water flow on soil scouring near the pipeline rupture, with pronounced effects in full-pipe flow, predominantly ahead of the rupture point, and less significant impacts observed in half-pipe flow scenarios. Differential image analysis facilitated the categorization of soil into distinct zones: collapsed, loosened, stable, and eroded, with a direct correlation observed between the extent of the loosened zone and the velocity of water flow. [ABSTRACT FROM AUTHOR]

The paper analyzes the problem of protection of underground metal pipelines using active cathodic protection. Shortcomings and emergency situations of active defense complexes are given. Analytical dependences of determining the levels of the protective potential in the conditions of a heterogeneous environment, various variations of the topology of laying the pipeline system are generally presented. The results of comprehensive monitoring of the operation modes of electrotechnical complexes of electrochemical protection allowed to develop a universal methodology for creating energy-efficient and reliable systems of cathodic protection of pipelines. [ABSTRACT FROM AUTHOR]

The inertial measurement method of pipelines utilizes a Micro-Electro-Mechanical Systems Inertial Measurement Unit (MIMU) to get the three-dimensional trajectory of underground pipelines. The initial attitude is significant for the inertial measurement method of pipelines. The traditional method to obtain the initial attitude uses three-axis magnetometers to measure the Earth's magnetic field. However, the magnetic field in urban underground pipelines is intricate, which leads to the initial attitude being inaccurate. To overcome this challenge, a novel multi-position initial alignment method based on data backtracking for a single-axis FOG and a three-axis Micro-Electro-Mechanical Inertial Measurement Unit (MIMU) is proposed. Firstly, the configuration of the sensors is determined. Secondly, according to the three-point support structure of the pipeline measuring instrument, a three-position alignment scheme is designed. Additionally, an initial alignment algorithm using the data backtracking method is developed. In this algorithm, a rough initial alignment is conducted by the data from single-axis FOG, and a fine initial alignment is conducted by the data from FOG/MIMU. Finally, an experiment was conducted to validate this method. The experiment results indicate that the pitch and roll angle errors are less than 0.05°, and the azimuth angle errors are less than 0.2°. This improved the precision of the 3-D trajectory of underground pipelines. [ABSTRACT FROM AUTHOR]

The transportation of coal-based solid waste filling slurry (CSWFS) through pipelines for underground goaf injection is essential for enhancing mine safety and promoting green, low-carbon coal mining. To address the issue of pipeline blockage caused by the suspension sensitivity of CSWFS during long-distance transportation, this study proposes the addition of the suspending agent hydroxypropyl methyl cellulose (HPMC) to transform the filling slurry into a stable suspending slurry. The mechanism by which the suspending agent modifies the rheological property of CSWFS was elucidated and verified. Firstly, an evaluation index system for the suspending state of CSWFS based on the "experimental test and theoretical calculation" was established. The values for layering degree, bleeding rate time-loss, and the corresponding average time-loss rate over 0 to 120 min of A1–A5 CSWFS were recorded as 24 mm–2 mm, 3.0–0.2%, 252.4–54.2%, and 149.6–14.6%, respectively. The concentration gradient evaluation result, C/CA = 0.91 (≥0.8), confirmed that the suspending agent maintained a stable suspending state over time for CSWFS. Secondly, it was demonstrated that the suspending agent HPMC modified the rheological property of A1–A5 CSWFS by increasing its plastic viscosity, which strengthened the viscous resistance to particle settling, thereby transforming a semi-stable slurry into a stable one. Additionally, the formation of a spatial suspending network by the suspending agent ensures that no pipeline blockage accidents occured in practical engineering applications. Furthermore, the XRD and SEM tests were utilized to verify the microstructure of the top (T) and bottom (B) samples in A4 block. It was concluded that the type of hydration products, occurrence forms, lapping compactness, and microstructural development were consistent, ultimately forming a high-strength, dense, hardened filling block. Finally, numerical simulation confirmed that the addition of suspending agent in A4 slurry formed a comprehensive spatial suspending network and a well-structured, unified system. This is one effective approach which could contribute to addressing the technical issue of pipeline blockage during long-distance pipeline transportation. [ABSTRACT FROM AUTHOR]

In order to reduce heat loss and diffusion of underground heating pipelines, this research incorporated phase change material (PCM) into the controlled low-strength material (CLSM) to prepare a pipeline backfill material with temperature control performance. In response to the problem that PCM leaks easily, a new type of paraffin–rice husk ash composite PCM (PR-PCM) was obtained by adsorbing melted paraffin into rice husk ash. Through mixing PR-PCM with dredged sediment (DS) and ordinary Portland cement (OPC), a controlled low-strength material (CLSM) with temperature control performance was prepared. The flowability, mechanical properties, microscopic characteristics, thermal characteristics, and durability of CLSM were analyzed through flowability, unconfined compressive strength (UCS), X-ray diffraction (XRD), scanning electronic microscopy (SEM), differential scanning calorimetry (DSC), and phase change cycle tests. The results show that when water consumption is constant, as the PR-PCM content increases, the flowability of CLSM increases, and the strength decreases. The CLSM has an obvious paraffin diffraction peak in the XRD pattern, and its microstructure is dense with few pores. The melting point of CLSM is 50.65 °C and the latent heat is 4.10 J/g. Compared with CLSM without PR-PCM, the maximum temperature difference during the heating process can reach 3.40 °C, and the heat storage performance is improved by 4.1%. The strength of CLSM increases and the melting point decreases after phase change cycles. CLSM containing PR-PCM has the characteristics of phase change temperature control, which plays a positive role in reducing heat loss by heating pipelines and temperature change in backfill areas. [ABSTRACT FROM AUTHOR]

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Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infrastructure systems and networks capable of withstanding blast loading. Initially centered on high-profile facilities such as embassies and petrochemical plants, this concern now extends to a wider array of infrastructures and facilities. Engineers and scholars increasingly prioritize structural safety against explosions, particularly to prevent disproportionate collapse and damage to nearby structures. Urbanization has further amplified the reliance on oil and gas pipelines, making them vital for urban life and prime targets for terrorist activities. Consequently, there is a growing imperative for computational engineering solutions to tackle blast loading on pipelines and mitigate associated risks to avert disasters. In this study, an empty pipe model was successfully validated under contact blast conditions using Abaqus software, a powerful tool in mechanical engineering for simulating blast effects on buried pipelines. Employing a Eulerian-Lagrangian computational fluid dynamics approach, the investigation extended to above-surface and below-surface blasts at standoff distances of 25 and 50 mm. Material descriptions in the numerical model relied on Abaqus' default mechanical models. Comparative analysis revealed varying pipe performance, with deformation decreasing as explosion-to-pipe distance increased. The explosion's location relative to the pipe surface notably influenced deformation levels, a key finding highlighted in the study. Moreover, quantitative findings indicated varying ratios of plastic dissipation energy (PDE) for different blast scenarios compared to the contact blast (P0). Specifically, P1 (25 mm subsurface blast) and P2 (50 mm subsurface blast) showed approximately 24.07% and 14.77% of P0's PDE, respectively, while P3 (25 mm above-surface blast) and P4 (50 mm above-surface blast) exhibited lower PDE values, accounting for about 18.08% and 9.67% of P0's PDE, respectively. Utilising energy-absorbing materials such as thin coatings of ultra-high-strength concrete, metallic foams, carbon fiber-reinforced polymer wraps, and others on the pipeline to effectively mitigate blast damage is recommended. This research contributes to the advancement of mechanical engineering by providing insights and solutions crucial for enhancing the resilience and safety of underground pipelines in the face of blast events. [ABSTRACT FROM AUTHOR]

The urban lifeline safety project is a major national livelihood project, which ensures the safe operation of urban gas, water, electricity and other systems. Nowadays, the project is confronted with three types of difficulties: Difficulties in mechanism discovery and experimental reproduction; difficulties in risk detection and early identification, and difficulties in accurate early warning and collaborative prevention and control. In order to reveal the mechanism and reproduce the experiments, a full-size urban lifeline multihazard large-scale scientific device is firstly developed in the world, a series of dis-aster modes with 5 categories and 169 kinds of disasters coupled are established, based on which a comprehensive risk dynamic assessment method coupled with underground pipelines and above-ground disaster-bearing body is presented. To improve the risk detection and early identification, highly sensitive gas sensing laser chip as well as detector with active grating and wavelength-biased are invented. We develop an intelligent ball for leakage located in water supply pipe network based on the inertial guidance, force balance, acoustic spectrum and Bei Dou. Bridge overall modal (fingerprint) monitoring technology is break-through. In order to solve the problem of accurate early warning and collaborative prevention and control, an urban lifeline safety risk physical heuristic artificial intelligence early warning technology is presented, based on which a monitoring and early warning system is developed with collaborative sensing, fusion monitoring, targeting early warning, linkage response and other functions. The related studies result in the development of the safety and emergency response industry, followed by the pioneering and substantial contributions to the prevention and control of urban lifeline risks [ABSTRACT FROM AUTHOR]

[Objective] In order to study the displacement variation law of adjacent underground pipelines during the excavation of deep foundation pits. [Method] Based on a deep foundation pit project of Nanchang No.4 line, FLAC 3D software is used to simulate the whole process of dynamic construction of foundation pit, and the influence of different pipe materials, pipe diameter, buried depth and buried distance of internal support on pipeline displacement is analyzed. And the field deformation monitoring data are used for comparison and verification. [Result] The results show that the internal support plays a good role in limiting the displacement of the adjacent pipeline during the construction of the foundation pit. In the process of foundation pit excavation, the change of pipe material and pipe diameter mainly affects the settlement of pipeline. [Conclusion] The stiffness of different types of pipes is different. The greater the stiffness, the stronger the pipeline's ability to resist soil de formation. The settlement variation of the pipeline is negatively correlated with the variation of the pipe diameter. The buried depth of the pipeline has a significant effect on the horizontal displacement of the pipeline. The horizontal displacement of the pipeline increases first and then decreases with the increase of the buried depth, and reaches the maximum when the buried depth of the pipeline is close to 1/2 of the design depth of the foundation pit. Under the principle of following a single variable, there are differences in the influence range of displacement of pipelines with different buried distances. Compared with pipeline settlement, foundation pit excavation has a greater influence range on the horizontal displacement of adjacent pipelines. [ABSTRACT FROM AUTHOR]

The logistics transportation system is critical to the United States economy. Underground Logistics Transportation (ULT) is a class of automated transportation systems in which vehicles carry freight through pipelines and tunnels between terminals. Being able to use a part of the underground space of existing highways will greatly facilitate the construction of such pipelines and tunnels and reduce their construction costs. Underground Logistics Transportation (ULT) could be the answer to make freight transport more sustainable and competitive. Texas highways and railroads are expected to increase by nearly 207% from 2003 to 2030. Truck tonnage will grow by 251%, while rail tonnage is forecasted to increase 118%. The number of trucks carrying NAFTA goods will increase by 263%, and the number of rail units will grow by 195%. This will have a profound impact on the highway and rail systems. The objective of this paper is to present requirements and operational components for three types of ULT lines: standard shipping containers, a standard crate size, and a standard pallet size. This study examines the use of ULT as a mode of underground transportation with the help of three case studies. This research shows that ULT is financially viable, feasible, greener, cost effective, and can become an important part of intermodal freight mobility. [ABSTRACT FROM AUTHOR]

In the rapid development of urban construction, underground pipelines play a crucial role. However, the current underground pipelines have poor association with relevant management departments, and there are deficiencies in data completeness, accuracy, and information content. Managing and sharing information resources is relatively difficult, transforming the constructed 3D underground pipeline geographic information systems into an 'Information silo'. This results in redundant construction and resource wastage of underground utilities. The complex distribution characteristics of underground utilities make rapid batch modeling and post-model maintenance challenging. Therefore, researching a 3D spatial data fusion model for urban underground utilities becomes particularly important. Given the above problem, this paper proposes a spatial data fusion model for underground pipeline scene modeling. It elaborates on the geometric, semantic, and temporal characteristics of underground pipelines, encapsulating these features. With underground pipeline objects as the core and pipeline characteristics as the foundation, a spatial data fusion model integrating multiple characteristics of underground pipelines has been constructed. Through software development, the data model designed in this paper facilitates rapid construction of underground pipeline scenes. This further enhances the consistency and integrity of underground pipeline data, enabling shared resources and comprehensive supervision of facility operations on a daily basis. [ABSTRACT FROM AUTHOR]

The corrosion mechanism of L245NS steel and L360QS steel of gas injection/withdrawal pipeline of underground gas storage in different acidic gas environments was studied by means of SEM, EDS, XRD, XPS, and GC-MS. The results show that Fe2O3, Fe3O4, and CaCO3 with poor protection were formed on the surface of L245NS steel, which provided a channel for the corrosive medium to contact the surface of the metal matrix and accelerated the corrosion rate of the pipeline. Meanwhile, CI− had a small radius and strong penetrability, which was easy to pass through the product film to reach the surface of the metal matrix to participate in the reaction, resulting in corrosion defect pits. The inner wall of L360QS steel was attached with gum, forming a dense protective film on the inner surface of the pipeline, and it was difficult for corrosive substances to enter the metal matrix, which played a role in inhibiting the corrosion of the pipeline. [ABSTRACT FROM AUTHOR]

In this subsection, a simulation model of underground pipeline leaks was created. Modeling the flow fields of overhead pipelines and underground pipelines with different soil porosity was conducted. The influence of the underground environment and soil porosity on the pipeline leakage field was analyzed. The influence of changes in the underground environment and soil porosity on the loss of kinetic energy at gas leakage was defined. Thus, the law of change in the characteristics of the sound signal of a leak on the pipe wall was obtained. Based on the results of study, it was determined the area of damage to a gas pipeline which is depended on proportionality of the diameter of the gas jet. As the gas is released from a crack in the gas pipeline and with different porosity of the pipe material, the gas diffusion occurred. As a result, the explosion zone increased which ultimately the release of gases into the environment under the influence of pressure increased. [ABSTRACT FROM AUTHOR]

The evolution and mechanism of ground collapse caused by underground water pipeline leakage have become increasingly significant as more urban areas experience collapses. Based on the principle of similarity, and considering the engineering context of road collapses in Anqing City, Anhui Province, this study designed a 3 m × 2 m × 2 m rupture-collapse model test device. Digital Image Correlation (DIC) technology was employed to investigate the erosion process and collapse mechanisms caused by underground pipeline leakage. The results indicate that groundwater seepage provides the driving force for collapses, combined with the migration space provided by defects, collectively triggering the collapses. When groundwater seepage is minimal, the cohesive forces between soil particles maintain soil stability. As groundwater seepage increases, the soil particle framework is eroded, leading to soil structure destabilization and collapse initiation. The depth of collapse significantly influences stress evolution: stress evolution intensity beneath and above the collapse pit is positively correlated with the distance from the collapse pit bottom, but negatively correlated with the distance from the defect. The research provides insights for the early warning and management of ground collapse. [ABSTRACT FROM AUTHOR]

The correct prediction of heating network pipeline failure rates can increase the reliability of the heat supply to consumers in the cold season. However, due to the large number of factors affecting the corrosion of underground steel pipelines, it is difficult to achieve high prediction accuracy. The purpose of this study is to identify connections between the failure rate of heating network pipelines and factors not taken into account in traditional methods, such as residual pipeline wall thickness, soil corrosion activity, previous incidents on the pipeline section, flooding (traces of flooding) of the channel, and intersections with communications. To achieve this goal, the following machine learning algorithms were used: random forest, gradient boosting, support vector machines, and artificial neural networks (multilayer perceptron). The data were collected on incidents related to the breakdown of heating network pipelines in the cities of Kazan and Ulyanovsk. Based on these data, four intelligent models have been developed. The accuracy of the models was compared. The best result was obtained for the gradient boosting regression tree, as follows: MSE = 0.00719, MAE = 0.0682, and MAPE = 0.06069. The feature «Previous incidents on the pipeline section» was excluded from the training set as the least significant. [ABSTRACT FROM AUTHOR]

The purpose of this study is to put forward a feature extraction and pattern recognition method for the flow noise signal of natural gas pipelines in view of the complex situation brought by the rapid development and expansion of urban natural gas infrastructure in China, especially in the case that there are active and abandoned pipelines, metal and nonmetal pipelines, and natural gas, water and power pipelines coexist in the underground of the city. Because the underground situation is unknown, gas leakage incidents caused by natural gas pipeline rupture occur from time to time, posing a threat to personal safety. Therefore, the motivation of this study is to provide a feasible method to accelerate the aging, renewal and transformation of urban natural gas pipelines to ensure the safe operation of urban natural gas pipeline network and promote the high-quality development of urban economy. Through the combination of experimental test and numerical simulation, this study establishes a database of urban natural gas pipeline flow noise signals, and uses principal component analysis (PCA) to extract the characteristics of flow noise signals, and develops a mathematical model for feature extraction. Then, a classification and recognition model based on backpropagation neural network (BPNN) is constructed, which realizes the detection and recognition of convective noise signals. The research results show that the theoretical method based on acoustic feature analysis provides guidance for the orderly and safe construction of urban natural gas pipeline network and ensures its safe operation. The research conclusion shows that through the simulation analysis of 75 groups of gas pipeline flow noise under different working conditions. Combined with the experimental verification of ground flow noise signals, the feature extraction and pattern recognition method proposed in this study has a recognition accuracy of up to 97% under strong noise background, which confirms the accuracy of numerical simulation and provides theoretical basis and technical support for the detection and recognition of urban gas pipeline flow noise. [ABSTRACT FROM AUTHOR]

The location monitoring of underground pipelines is of utmost significance as it helps the effective management and maintenance of the pipelines, and facilitates the planning of nearby projects, preventing damage to the pipelines. However, currently there is a serious lack of data on the locations of underground pipelines. This paper proposes an image-based approach for monitoring the locations of underground pipelines by combing deep learning and visual-based reconstruction. The proposed approach can build the monitoring model for underground pipelines and characterize their locations through their centroid curve. Its advantages are: (1) simplicity: it only requires time-sequential images of the inner walls of underground pipelines; (2) clarity: the location model and the location curve of underground pipelines can be provided quickly; (3) robustness: it can cope with some existing problems in underground pipelines, such as light variations and small viewing angles. A lightweight approach for monitoring the locations of underground pipelines is achieved. The proposed approach’s effectiveness has been validated through laboratory simulation experiments, demonstrating accuracy at the millimeter level.

As a popular nondestructive technique, ground penetrating radar (GPR) is extensively utilized for detecting underground pipelines. In this paper, an efficient and automatic scheme is presented for the detection and classification of underground pipelines by combining electromagnetic modeling and machine learning techniques. By virtue of open-source gprMax software, the B-scan signatures of underground pipelines are simulated and analyzed in detail, with four types of underground pipelines taken into account, i.e., iron pipelines, concrete pipelines, copper pipelines, and PVC pipelines. On the basis of electromagnetic modeling, B-scan profiles of underground pipelines are preprocessed by using the average method and time gain compensation method to obtain a dataset for training neural network of YOLOv8 model. The simulations indicate that our scheme combining simulated B-scan profiles and YOLOv8 model is able to detect and classify underground pipelines with high accuracy, and the category and material of underground pipelines can be determined with a high confidence level. Specifically, the detection time of a single B-scan image for underground pipelines is about 0.02 s, and the average detection accuracy can reach 0.995, which is potentially valuable for the automatic detection and classification of underground pipelines in GPR applications. [ABSTRACT FROM AUTHOR]

As the strategy for building China's strength in transportation continues to advance, people's demand for the quality of travel is increasing. Rail transit has become the lifeline for high-quality development in urbanization. Especially for intercity railways, suburban railways, and metros, which are mainly built through urban areas and are mostly laid underground, resulting in numerous urban tunnels. Due to the complex urban environment, tunnels inevitably pass above, below, or alongside existing buildings and structures such as railways, metros, highways, main urban roads, and high-rise buildings (hereinafter referred to as close-spaced engineering). How to ensure the normal operation and safety of close-spaced engineering during tunnel construction, as well as how to reasonably determine the deformation control standards for close-spaced engineering, are the focus, difficulty, and control points of urban tunnel construction. This article categorizes by adjacent railway, highway, urban rail transit, and underground pipelines, systematically sorts out the standards of related industries, and proposes protection ranges and requirements for tunnels in different environments, deformation control standards for close-spaced engineering construction. Based on the control standards and engineering experience, a set of design and construction control measures for close-spaced engineering are proposed: During the survey phase, it is necessary to ascertain the surrounding environment and geological conditions. During the design phase, on the basis of reasonably designing the route scheme and keeping enough safe clearance, adopt reasonable construction methods and reliable supporting structures, and set up effective isolation, protection, and reinforcement measures. During the construction phase, strengthen tunnel geological prediction and monitoring, and establish perfect contingency plans. [ABSTRACT FROM AUTHOR]

This paper is devoted to the issue of efficiency of application of fibre optic leak detection systems for identification of small leaks on trunk pipelines. The main methods of leak detection currently in use have been considered, and parametric and fibre optic LDS have been selected for comparative analysis. In the course of the research a model of product leakage from an underground oil pipeline equipped with a fibre-optic LDS was built in the COMSOL Multiphysics software package. The result of the simulation was the estimated time of leak identification by the fibre-optic system, which turned out to be much shorter than that of the parametric LDS. Compensable environmental damage for each type of system was then calculated, confirming the effectiveness of fibre optic LDS for detecting small leaks on trunk pipelines due to the significant reduction in compensable damage. [ABSTRACT FROM AUTHOR]

During the process of urban development, there is large-scale laying of underground pipeline networks and coordinated operation of both new and old networks. The underground concrete drainage pipes have become a focus of operation and maintenance due to their strong concealment and serious corrosion. The current manual inspections for subterranean concrete drainage pipelines involve high workloads and risks, which makes meeting the diagnostic needs of intricate urban pipeline networks challenging. Through advanced information technology, it has reached a consensus to intelligently perceive, accurately identify, and precise prediction of the condition of urban subterranean drainage networks. The development process of detection and evaluation methods for underground concrete drainage pipe networks is the focus of this study. The study discusses common algorithms for classifying, locating, and quantifying pipeline defects by combining the principles of deep learning with typical application examples. The intelligent progression of information collection methods, image processing techniques, damage prediction models, and pipeline diagnostic systems is systematically elaborated upon. Lastly, prospects for future research of intelligent pipeline diagnosis are provided. [ABSTRACT FROM AUTHOR]

With economic development and the burgeoning need for energy, numerous underground gas pipelines have been deployed for operation. Buried gas pipelines often suffer failures as a result of adverse factors, including corrosion, uneven subsidence, and damage caused by third parties. To investigate and predict the diffusion behavior following a natural gas pipeline leakage, Fluent software is utilized to develop a numerical model for the leakage and diffusion of high-pressure natural gas within a confined space. This model incorporates the Soave–Redlich–Kwong equation of state, which is widely recognized for its exceptional precision in characterizing the behavior of natural gas under high-pressure conditions. The study focuses on the analysis of leakage and diffusion behavior as well as the examination of how pipeline operating pressure and leakage diameter have an impact on the dispersion of leaked gas. Further, the prediction model for the diffusion distance of the hazardous area is developed, employing the least-square method and finite element calculations. The results show that, during the leakage process, a vortex and velocity region emerge, extending along the confined space. The farther away from the leakage hole above the pipeline, the higher the overall concentration of the gas. Moreover, the horizontal diffusion distance of gas at the bottom of the pipeline is considerably smaller than that above it. However, gas tends to readily accumulate in a high concentration area at the bottom of the pipeline. Elevating the leakage diameter and the operation pressure leads to a significant rise in gas concentration and the horizontal diffusion of the hazardous area. It is worth noting that the leakage diameter has a more pronounced effect on gas diffusion than does the pressure. The prediction model proposed in this study effectively anticipates the horizontal diffusion of the hazardous area within confined spaces. [ABSTRACT FROM AUTHOR]

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Stones are one of the primary objects that impede the normal activity of underground pipelines. As human intervention is difficult inside a narrow underground pipe, a robot with a machine vision system is required. In order to remove the stones during regular robotic inspections, precise stone detection, segmentation, and measurement of their distance from the robot are needed. We applied Mask R-CNN to perform an instant segmentation of stones. The distance between the robot and the segmented stones was calculated using spatial information obtained from a lidar camera. Artificial light was used for both image acquisition and testing, as natural light is not available inside the underground pipe. ResNet101 was chosen as the foundation of the Mask R-CNN, and transfer learning was utilized to shorten the training time. The experimental results of our model showed that the average detection precision rate reached 92.0; the recall rate was 90.0%; and the F1 score rate reached 91.0%. The distance values were calculated efficiently with an error margin of 11.36 mm. Moreover, the Mask R-CNN-based stone detection model can detect asymmetrically shaped stones in complex background and lighting conditions. [ABSTRACT FROM AUTHOR]

The spray system mechanism during a gas explosion in an underground square pipeline is complex. In this paper, the underground square of Fuxin City is selected as the research object. FLACS numerical simulation software is used to analyze the spatial and temporal distribution characteristics of a gas explosion in an underground square pipeline with an unopened spray system using combustion and combustion rate models. Different spray pressures were compared and analyzed to determine the optimal spray control pressure, and the spray system mechanism was clarified. The results revealed that the gas explosion overpressure is divided into the overpressure gentle, overpressure rising, and overpressure decay stages, corresponding to a trend of rapid growth and slow decline. The influence of spray pressure on the gas explosion exhibits a promotion–inhibition–promotion trend, corresponding to 0–0.2 MPa, 0.2–0.6 MPa, and 0.6–1.6 Mpa, respectively. The peak overpressure and overpressure propagation rates are the lowest at 0.6 MPa, and the explosion suppression effect is the most pronounced. The spray system mechanism varies with the explosion overpressure stages. Generally, the time to peak value, that is, the peak time, the overall duration of the explosion, and the duration of the explosion stage decrease, whereas the peak explosion overpressure decreases. [ABSTRACT FROM AUTHOR]

The object of the study is the development of a device capable of accurately and reliably measuring heat flux density in various environments. The development of a heat flux density meter designed for non-destructive analysis of thermal processes in various fields of application is presented. The developed device is intended for evaluating the thermal insulation condition of underground pipelines. The functionality of the heat flow device relies on comparing standard temperature values with experimental ones measured on the soil surface. To ensure accurate and reliable measurement of heat flux density, the basis is a thermoelectric battery converter, which uses the auxiliary wall method. The heat flow density measuring device is constructed in the shape of a restricted cylinder, with one base serving as the working surface, while the second base establishes thermal contact with the body at ambient temperature. Embedded heaters enable the generation of heat flow through the thermoelectric sensor in directions perpendicular to its base. For calibrating the heat flux device, experiments were conducted using a standard copper-constantan calibration table. Temperature increments were determined from thermo electromotive force, and tests were performed on an existing heating network. The conducted measurements validate the fundamental feasibility of employing the proposed device for implementing the nondestructive thermal testing method on underground heating mains. The results of the experiment can be used not only for research, but also for monitoring and regulating processes in various fields of science and technology. The developed heat flux meter promises a significant contribution to the development of modern methods for analyzing thermal processes. The dimensions of the thermoelectric battery converter are also determined and the coefficient (kq) should be in the range from 4.0 to 12.0 W/(m²⋅mV), and the electrical resistance should be in the range of 12–20 kOhm. [ABSTRACT FROM AUTHOR]

The deep surrounding rock is usually in the true triaxial stress state, and previous constitutive models based on the understanding of uniaxial and conventional triaxial test results have difficulty characterizing the degradation and fracture process of rock ductile--brittle failure under true triaxial stress state. Therefore, this study conducted a series of true triaxial tests to obtain the understanding of the ductile--brittle behaviour of rock, and then combined the test results and the Mogi--Coulomb strength criterion, and proposed calculation methods for the elastic modulus E, cohesion c and internal friction angle u and the evolution functions of E, c and ф of rock under true triaxial stresses. With the decreasing of the minimum principal stress σ3 or increasing of the intermediate principal stress σ2, the marble post-peak stress drop rate gradually increases, the ductility gradually weakens, and the brittleness significantly strengthens. The calculation method and evolution function of rock E, c and ф under true triaxial stress were proposed. E decreased at first and then tended to remain stable with the increasing of equivalent plastic strain increment dep. c and u slowly increased at first and then rapidly decreased. With a method of parameter degradation rate to realize post-peak stress drop rate to reflect the ductile--brittle characteristics, a new three-dimensional ductile--brittle deterioration mechanical model (3DBDM) was established. The proposed model can accurately characterize the influence of rσ and rσ on mechanical parameters, the ductile--brittle behaviour of rock under true triaxial stresses, and the asymmetric failure characteristics of surrounding rock after excavation of deep underground engineering. The proposed model can be reduced to elastic--perfectly plastic, elastic--brittle, cohesion weakening friction strengthening (CWFS), Mohr--Coulomb, and Drucker--Prager models. [ABSTRACT FROM AUTHOR]

Urban underground pipeline networks are a key component of urban infrastructure, and a large number of older urban areas lack information about their underground pipelines. In addition, survey methods for underground pipelines are often time-consuming and labor-intensive. While the manhole cover serves as the hub connecting the underground pipe network with the ground, the generation of underground pipe network can be realized by obtaining the location and category information of the manhole cover. Therefore, this paper proposed a manhole cover detection method based on UAV aerial photography to obtain ground images, using image super-resolution reconstruction and image positioning and classification. Firstly, the urban image was obtained by UAV aerial photography, and then the YOLOv8 object detection technology was used to accurately locate the manhole cover. Next, the SRGAN network was used to perform super-resolution processing on the manhole cover text to improve the clarity of the recognition image. Finally, the clear manhole cover text image was input into the VGG16_BN network to realize the manhole cover classification. The experimental results showed that the manhole cover classification accuracy of this paper's method reached 97.62%, which verified its effectiveness in manhole cover detection. The method significantly reduces the time and labor cost and provides a new method for manhole cover information acquisition. [ABSTRACT FROM AUTHOR]

Remote sensing detection of natural gas leaks remains challenging when using ground vegetation stress to detect underground pipeline leaks. Other natural stressors may co-present and complicate gas leak detection. This study explores the feasibility of identifying and distinguishing gas-induced stress from other natural stresses by analyzing the hyperspectral reflectance of vegetation. The effectiveness of this discrimination is assessed across three distinct spectral ranges (VNIR, SWIR, and Full spectra). Greenhouse experiments subjected three plant species to controlled environmental stressors, including gas leakage, salinity impact, heavy-metal contamination, and drought exposure. Spectral curves obtained from the experiments underwent preprocessing techniques such as standard normal variate, first-order derivative, and second-order derivative. Principal component analysis was then employed to reduce dimensionality in the spectral feature space, facilitating input for linear/quadratic discriminant analysis (LDA/QDA) to identify and discriminate gas leaks. Results demonstrate an average accuracy of 80% in identifying gas-stressed plants from unstressed ones using LDA. Gas leakage can be discriminated from scenarios involving a single distracting stressor with an accuracy ranging from 76.4% to 84.6%, with drought treatment proving the most successful. Notably, first-order derivative processing of VNIR spectra yields the highest accuracy in gas leakage detection. [ABSTRACT FROM AUTHOR]

A permanent magnet linear synchronous motor (PMLSM) with discontinuous driving coils potentially applied in the underground pipeline freight delivery system is introduced in this article. Firstly, the detailed structure of the PMLSM with discontinuous driving coils is designed and presented, and the dynamic models of the PMLSM during three different processes are developed. In addition, based on the proportional-integral (PI) and the adaptive disturbance observer (DOB), a multi-loop control strategy is designed for the PMLSM with discontinuous driving coils. The critical performances of PMLSM, such as the speed precision and anti-disturbance ability, are testified in the experiment, and the results validate that the multi-loop control model with adaptive DOB used in the PMLSM with discontinuous driving coils has better speed precision than the PI+PI model by suppressing the detent force. • The thrust-force varies with the motion process of the PMLSM with discontinuous driving coils. • The DOB model estimates the thrust-force variation of the PMLSM with discontinuous driving coils. • A multi-loop control based on PI and DOB improves the speed precision of the PMLSM with discontinuous driving coils. [ABSTRACT FROM AUTHOR]

In the work, the modeling of the distribution of the protective potential of electrochemical protection stations is performed by revealed functional dependencies. The initial conditions are adopted for a typical assortment of rolled metal used for underground gas supply. At the initial stage of modeling, the stochastic nature of the change in soil parameters is not taken into account. The distribution of the protective potential of the underground pipeline as a function of two variables (time and distance) showed the mutual influence of neighboring stations on the formation of protective zone. New dependences of the operating parameters of the electrotechnical complex of electrochemical protection on the set of variables characterizing the power source, the physical dimensions of pipeline and the alternative arrangement of active cathodic protection stations (CPS) were obtained. Experimental studies of the modes of electrochemical protection stations at the objects of the gas transportation system of Ukraine confirmed the adequacy of the proposed analytical models. References 16, Figures 3. [ABSTRACT FROM AUTHOR]

Uneven settlement phenomenon is very easy to occur in the sandy pulverized ground stratum, the underground pipe corridor longitudinal and transverse stiffness difference is obvious, so that it is easy to crack and deformation due to uneven settlement in this type of stratum. This paper carries out research on uneven settlement and cracking and deformation of Qihe tube corridor, analyzes the reasons leading to uneven settlement and the factors affecting the deformation and cracking of the tube corridor, and provides guidance for foundation treatment and tube corridor repair and mixing and reinforcement. It was found that the concrete structure of the corridor itself had exposed reinforcement, pockmarks and holes, and that cracks on the structure of the corridor sprouted and expanded from these defects. Defects and damages on the concrete structure of the pipeline corridor are contributing factors to the deformation and cracking of the members, and the uneven settlement of the foundation is the main initiating factor for the cracking and deformation. The analysis of the numerical simulation results of similar underground pipeline corridors is carried out, and it is found that the simulation results are consistent with the deformation characteristics of the Qihe pipeline corridor, which further supports the conclusions of this paper. The main stratigraphic factors contributing to the inhomogeneous settlement were found to be the water-rich and loose bodies in the lower part of the strata, as revealed by the physical means and the experimental verification boreholes. Localized hydraulic effects such as pumping further accelerate the uneven settlement of the foundation. [ABSTRACT FROM AUTHOR]

The accuracy of the current buried pipeline management geographic information system (GIS) is not adequate to serve as base information for road digging control and permit in Taiwan. The existing positioning system for buried pipelines does not offer satisfactorily accurate surveying results for all the scenarios because the positioning accurateness decreases with an increase in the pipeline depth. The costly excavation and direct survey of the exposed pipeline method can provide precise measurement at the designed arbitrary interval and then the discrete point is interpolated into the continuous track. The required traffic controls and excavation permits for roads are the most critical drawback of this technology. The method of in-pipe inertial navigation system (INS) can record the complete, continuous pipe tracks, but such measurement drifts with an increase in the survey length. We proposed a pipeline positioning system by radiating an extremely low-frequency (ELF) magnetic field from the electrical coil placed on the ground to constrain the locating measurement of in-pipe INS. The proposed system could easily expand the diameters or increasing turns of a ground-based coil device to enhance the magnetic field intensity for accurately positioning the deeper buried pipes. The field tests were performed using a ductile cast iron pipe (DIP), and the corresponding results revealed that for the overburden depth of 3.4–4.2 m, the average positioning errors were 0.12 and 1.6 m in the horizontal and vertical directions, respectively. This approach is only plausible for an empty pipeline, and access to both ends of the pipe is required. A four-person crew handled the proposed system to locate the track of a 5-km-long buried pipeline in an 8-h-long working day when the pipeline was unfilled. Any pipeline with diameter larger than 10 cm (4 in.) could apply this system to locate the continuous track with the requirement of accessibility at both ends of the empty pipe. With 1.45-m coil, the maximum detectable buried depth is 15 m, and locating error is less than 20 cm at both directions for the cases with buried depth less than 5 m. Two people need to move and operate the magnetic coil at the ground and another two people must hoist the in-pipe unit at each end of the pipe simultaneously. With this arrangement, the continuous track of buried empty pipe could surveyed for 5 km in length within an 8-h working day. [ABSTRACT FROM AUTHOR]

Excessive lateral movements of buried pipes in geohazard-prone areas frequently jeopardize the structural integrity and serviceability of pipelines, as well as the safety of the surrounding geoenvironments. Based on the material point method (MPM), this paper investigates the pipe–soil interactions under lateral pipe movements, with a focus on the failure mechanisms of the surrounding soil during postfailure stages. The accuracy of the numerical model is validated by comparison with the results of large-scale model tests in the literature. There is a strong correlation between the experimental and numerical results in terms of force–displacement relationships and soil failure patterns. The impacts of burial depths, pipe diameters, and soil densities on the failure mechanism are analyzed in detail. The results showed that general shear failure tends to occur in shallow pipe conditions, resulting in significant ground heave. As the pipe burial depth increases, the peak soil resistance increases accordingly, and a transition from general shear failure to a localized flow-around mechanism gradually evolves. Furthermore, the softening effect after the peak resistance is reduced under the smaller pipe diameter and greater buried depth conditions. Comparisons of failure patterns illustrate that the embedment ratio is the main determinant of pipe–soil interaction modes as compared with the soil density. Transition failure often occurs when the embedment ratio ranges from 4.5 to 9.5, with slight influences from pipe diameters and soil properties. Finally, the prediction of the soil peak lateral resistance is explored to assist in underground pipeline design. [ABSTRACT FROM AUTHOR]

Featured Application: The findings of this study can be applied in engineering practice for the protection of buried pipelines and other underground life lines crossing under or near continuously expanding high-speed railway lines. High-speed railway (HSR) lines commonly operate over hundreds of kilometers, crossing several other large-scale infrastructures, such as highways, tunnels, bridges, and pipelines. This fact makes adjacent infrastructure more vulnerable to high-speed train (HST)-induced vibrations; thus, their potential distress should be carefully examined. The current study aims to assess the level of traffic-induced vibrations on the surface of buried pipelines vertically crossing under an HSR line. Firstly, the necessity to reduce high vibration levels is highlighted, utilizing a three-dimensional (3D) finite element model in conjunction with the moving load approach. Subsequently, an efficient mitigation measure is proposed to minimize these vibrations. For this purpose, a low-weight, high-performance geosynthetic fill material, i.e., expanded polystyrene (EPS) geofoam blocks, has been implemented between the HSR line and the buried pipeline to minimize the impact of vibrations. In this manner, HST-induced vibrations are reflected on EPS blocks, preventing them from reaching the pipeline surface. Based on this detailed parametric study, useful conclusions are drawn regarding the mechanical properties and geometry of the EPS protection layer. [ABSTRACT FROM AUTHOR]

The pipeline ground-penetrating radar stands as an indispensable detection device for ensuring underground space security. A wheeled pipeline robot is deployed to traverse the interior of urban underground drainage pipelines along their central axis. It is subject to influences such as resistance, speed, and human factors, leading to deviations in its posture. A guiding wheel is employed to rectify its roll angle and ensure the precise spatial positioning of defects both inside and outside the pipeline, as detected by the radar antenna. By analyzing its deflection factors and correction trajectories, the intelligent correction control of the pipeline ground-penetrating radar falls into the realm of nonlinear multi-constraint optimization. Consequently, a time-series-based correction angle prediction algorithm is proposed. The application of the long short-term memory (LSTM) deep learning model facilitates the prediction of correction angles and torque for the guiding wheel. This study compares the performance of LSTM with an autoregressive integrated moving average model under identical dataset conditions. The subsequent findings reveal a reduction of 4.11° and 8.25 N·m in mean absolute error, and a decrease of 10.66% and 7.27% in mean squared error for the predicted correction angles and torques, respectively. These outcomes are achieved utilizing the three-channel drainage pipeline ground-penetrating radar device with top antenna operating at 1.2 GHz and left/right antennas at 750 MHz. The LSTM prediction model intelligently corrects its posture. Experimental results demonstrate an average correction speed of 5 s and an average angular error of ±1°. It is verified that the model can correct its attitude in real-time with small errors, thereby enhancing the accuracy of ground-penetrating radar antennas in locating pipeline defects. [ABSTRACT FROM AUTHOR]