Underground Leakage Research Articles

Leak detection and localization in underground water supply system using thermal imaging and geophone signals through machine learning

The underground water pipeline system is a crucial infrastructure that largely remains out of sight. However, it is the source of a clean and uninterrupted flow of water for our everyday lives. Various factors, including corrosion, material degradation, ground movement, and improper maintenance, cause pipe leaks, a silent crisis that causes an estimated 39 billion dollars of loss every year. Prompt leakage detection and localization can help reduce the loss. This research investigates the potential of two machine learning models as supporting tools for surveying extensive areas to identify and pinpoint the location of underground leaks. The presented combined approach ensures the speed and accuracy of the leakage survey. The first machine learning model is a hybrid ML model that employs thermal imaging to identify subterranean water leakage. It relies on detecting thermal anomalies and distinctive signatures associated with water leakage to identify and locate underground water leakage. The developed model can detect up to 750 mm underground leakage with 95.20 % accuracy. The second model uses binaural audio from geophones to localize the leakage position. The model utilizes interaural time difference and interaural phase difference for localization purposes, and the 1D-CNN network delivers an angle in twenty-degree increments with an accuracy of 88.19 %. Large-scale implementation of the proposed model could be a powerful catalyst to reduce water loss in the water supply system.

Flow and Transport of Methane from Leaking Underground Pipelines: Effects of Soil Surface Conditions and Implications for Natural Gas Leak Classification

Flow and Transport of Methane from Leaking Underground Pipelines: Effects of Soil Surface Conditions and Implications for Natural Gas Leak Classification

A New Attempt to Estimate Underground Soil Leakage through High-Density, Fixed-Point Monitoring in a Typical Karst Rocky Desertification Region

Understanding soil loss pathways in karst regions is crucial for erosion control. Combining high-density measurements of grid points with runoff plot monitoring, we attempt to use a new indirect method to study the characteristics of soil loss in karst rocky desertification areas of Salaxi Town, Guizhou province. One cycle year monitoring data of 12640 grid points were applied in the soil loss analysis. This study identifies underground leakage as the primary pathway of soil loss, with an mean soil leakage of 21.51 kg in potential areas, accounting for 83.12%, and an average leakage of 22.69 kg in in mild karst rocky desertification areas accounting for 81.48%. Mixed vegetation types (forest, shrub, and grass) were better at preventing surface soil loss but increased underground leakage compared to single vegetation types. The rainy season significantly influences soil erosion, accounting for 67.88% of total loss, with slight variations among different karst rocky desertification grades and vegetation types. Mean underground leakage rates during the rainy and dry seasons are 63.34% and 36.66%, respectively. Although this method still has certain limitations, it plays a positive role in revealing the mechanism of soil erosion processes in karst regions.

The Study on the Ecological Governance Method and Green Enclave Economy Operating in Rocky Desertification Region of Northwest Guangxi

The karst landscapes of Northwest Guangxi are characterized by three-dimensional ecological syndromes of desertification: vertical underground leakage, horizontal surface loss, and evaporation of light and heat from the sky, making them a veritable kingdom of "karst + desertification". The study of ecological management methods and green enclave economy operation in the rocky desertification area of Northwest Guangxi will help to form a causal chain between rocky desertification and poverty in the rocky desertification area, so as to realize the successful synergistic evolution of GDP and GEP. This paper adopts the ecological value-oriented green photovoltaic and ecological agroforestry, culture and tourism and other diversified industrial integration and comprehensive governance methods in the rocky desertification area of Northwest Guangxi, and the 1+1>2 new wooden barrel corresponding to the consortium and outsourcing operation mode of the virtual enterprise development of the green enclave economy. Eventually, it has achieved the outstanding achievements that the average annual reduction rate of rocky desertification, the greening coverage rate of villages, the forest coverage rate, the growth rate of per capita disposable income, and other indicators of double carbon and enrichment of "rocky nooks and crannies" have ranked in the forefront of Guangxi and the whole country, and it is a successful sample of rocky desertification area to interrupt the chain of causality between rocky desertification and poverty, and to realize synergistic evolution of GDP and GEP.

Modeling and investigation of the hydrological situation

Thousands of earthen dams have been built in Russia to create accumulating reservoirs, protect low-lying areas from floods, hydropower and others. Sometimes, due to the presence of underground leaks, erosion of the dam occurs and a breakthrough with catastrophic consequences. Therefore, the task of timely identification of places of underground leaks of earthen dams is urgent. Objective – to show the results of a flight experiment and the practical use of a microwave radiometer mounted on an unmanned aerial vehicle (UAV) in order to monitor the condition of an earthen dam in the Voronezh region and the possibility of searching for places of underground leaks. The paper presents the results of an experimental study of the condition of earthen dams. Also, the analysis of the obtained soil moisture maps allows you to determine the locations of possible underground leaks. The results of a flight experiment using a bipolarization microwave radiometer placed on board an unmanned aerial vehicle for remote determination of a portrait of soil moisture can be used to search for places of possible underground leaks. Also, this method of remote measurement of soil moisture can be used for the needs of agriculture, in particular for precision farming systems. In addition, the paper assesses the prospects of using microwave radiometric moisture meters for operational examination of the state of extended hydrological objects.

Hydrochemical examination of underground leakage water spread from open landfill in aksaray city in turkey and determination of its location. Case study

Hydrochemical examination of underground leakage water spread from open landfill in aksaray city in turkey and determination of its location. Case study

Investigating the possibility of leakage detection in water distribution networks using cosmic ray neutrons in the thermal region

Water distribution systems can experience high levels of leakage, originating from different sources, such as deterioration due to aging of pipes and fittings, material defects, and corrosion. In addition to causing financial losses and supply problems, leakages in treated water distribution also represent a risk for public health. Despite several techniques for leak detection are already available, there is still a lot of interest in new non-invasive approaches, especially for scenarios where acoustic techniques struggle, such as in noisy environmental conditions.In this work we investigated the possibility of using cosmic ray (CR) neutrons for the detection of underground leakages in water distribution networks, by exploiting the difference in the above ground thermal neutron flux between dry and wet soil conditions. The potential of the technique has been assessed by means of an extensive set of Monte Carlo simulations based on GEANT4, involving realistic scenarios based on the Italian aqueduct design guidelines. Simulation studies focused on sandy soils and results suggest that a significative signal, associated with a leakage, could be detected with a data-taking lasting from a few minutes to a half-hour, depending on the environmental soil moisture, the leaking water distribution in soil, and the soil chemical composition.Finally, a brief description of a new portable and low-cost detector for thermal neutrons, currently under commission, is also presented.

Influence of Buried Pipeline Leakage on the Development of Cavities in the Subgrade

The rapid pace of urbanization has led to an increasing frequency of road collapses, posing a significant threat to urban traffic safety. Underground pipeline leakage stands out as the primary cause of such collapses. This paper presents a macroscopic analysis of the subgrade seepage erosion process caused by pipeline leakage. Model tests were conducted to investigate the formation mechanism and explore the influence of water level, water flow rate, and soil type. The study revealed that the subgrade seepage erosion caused by pipeline leakage undergoes four distinct stages: infiltration, slow erosion, rapid erosion, and erosion convergence. Soil erosion shares similarities with sand erosion in its developmental process. The water level plays a pivotal role in determining the shape and size of the eroded area caused by sand seepage erosion. The size of the erosion cavities formed during the soil seepage erosion increased along with the increase in the water flow rate. The size of the erosion cavity increased by up to 55.7% when the flow rate was increased by three times. In addition, clay soils do not undergo significant erosional damage but do produce significant settlement. The soil erosion process caused by underground leakages in pipelines was investigated using model tests in this study, which provided valuable information for researchers performing an in-depth analysis of the mechanism of roadbed cavities generated by urban underground pipeline leakage, which is critical for safeguarding people’s travel safety and decreasing social and economic losses.

Радиометрический метод получения портретов влажности почвы для исследования гидрологии дамб

The methods for the artificial hydraulic structures condition monitoring using trace microwave radiometers are considered, in order to timely detect places of underground leaks to ensure trouble-free operation. Several practical examples of the use of microwave radiometers on various ground-based mobile carriers are described. The characteristics of microwave radiometers used in practice for hydrological monitoring of earthen dams are given. The possibility of detecting potentially dangerous sections of dams, places of erosion of the dam cover, possible places of underground leaks is shown. The possibility of combining microwave radiometers with other means of remote sensing, such as optical video cameras, thermal infrared cameras and georadars, is being considered. The advantages of multisensory sensing to increase the reliability of detecting places of underground leaks are substantiated.

Employing Robotics and Deep Learning in Underground Leak Detection

Leaks in water distribution networks (WDNs) produce significant economic losses. These leaks from underground pipelines affect the surrounding environment in different ways that can be detected using various technologies. This article introduces an unmanned ground vehicle (UGV) equipped with an infrared temperature sensor to remotely detect thermal anomalies on the surface caused by underground leaking pipelines. An MLX90614 low-cost thermopile infrared sensor was proposed to trace the surface temperature above leaking pipelines and record the corresponding position of each reading. Two positioning techniques were tested independently: a satellite navigation system and odometry using a magnetic encoder. Raw data from the temperature sensor along with the corresponding locations were recorded on a MicroSD card using an Arduino Uno Board through analog-to-digital converters (ADCs) and serial peripheral interface (SPI) bus. Experimental work showed the ability of the robot in detecting thermal anomalies caused by leaks accurately with the required trace resolution. Finally, a 2-D convolutional neural network (CNN) solution is introduced for distinguishing true detections from false alarms.

Effects of vegetation restoration types on soil erosion reduction of a shallow karst fissure soil system in the degraded karst areas of Southwestern China

AbstractShallow karst fissures are the main hydrological paths, underground loss channels, and one of the most critical root habitats in fragile karst rocky desertification areas. Revegetation may alter the type of vegetation cover in fissures, resulting in changes to soil properties and erosion reduction. In this study, we evaluate the influence of revegetation on the soil erosion reduction of fissure‐soil–plant systems (FSPS) for three vegetation types (herbs, shrubs, and trees) in FSPS and use bare FSPS without vegetation as a control in a karst rocky desertification area. The results show that the soil physicochemical properties of FSFS degraded first and then improved after abandonment, resulting in the order of soil erosion reduction of FSPS with vegetation succession being: shrub < herb < bare < tree. Vegetation restoration can significantly improve the soil erosion resistance of the 10–20 cm soil layer in the fissure zone, making it stronger than that in the non‐fissure zone, thus reducing the risk of underground leakage on the slope. The results obtained in this study deepen our knowledge of the impact of vegetation restoration type on soil erosion reduction and has significant implications for guiding vegetation restoration and preventing underground leakage in karst areas.

The underground leakage process of soil patches around bedrock outcrops in a karst rocky desertification area traced using rare earth elements

The loss of soil through underground leakage is a unique erosion process in the rocky karst desertification areas with abundant bedrock outcrops. Although some effort has been made to understand soil leakage loss, until now, the processes and ways that soil leakage loss occur have continued to puzzle us in this area. To solve this problem, three typical soil patches around bedrock outcrops were selected on a sloped farmland in a rocky karst desertification area located in Guizhou, China. Stable rare earth element tracing techniques combined with a streaking and marking method were used to observe the soil leaking process under three intervals of natural rainfall (accumulated rainfall was 104.5 mm, 151.2 mm and 332.7 mm for each interval). We found that rainstorms or heavy rainstorms are the key factors that cause the loss of soil around outcrop bedrock outcrops, where the main form of soil leakage is the downwards creeping of the soil layer. The soil creep displacement associated with the rainfall total of 104.5 mm (which consisted of one rainstorm, two moderate rain events and several light rain events) could account for more than 62.5% of the total creep associated with the rainfall total of 332.7 mm. However, the rainfall total of 181.5 mm (which consisted of a heavy rain episode, four moderate rain events and several light rain events) accounted for less than 15.0%. During different rainfall events, the concentrations of Ce, La and Sm in patches of soil around bedrock outcrops are negative compared with the background values in soil layers with treated with rare earth elements (REEs), while the concentrations of Ce, La and Sm used for comparison have a certain presence in other soil layers. Additionally, the concentrations of Ce, La and Sm at the rock-soil interface are not always higher or lower than those of the corresponding soil layer. It is proven that the soils in both the rock-soil interface and soil layer can leak downwards with a certain degree of probability. During the leaking processes, these soils do not move down uniformly or as a whole, but some particles in certain layers migrate to the lower layer separately. Therefore, improving soil anti-erodibility can prevent the creep leakage of soil patches to a certain extent and further preserve a sufficient material basis for plant restoration in rocky desertification areas.

Application of Improved DV-Hop algorithm in Wireless Sensor Network

To improve the problem of inaccurate wireless sensor network positioning algorithm of DV-Hop node is proposed. Firstly, the optimization scheme of the anchor nodes is completed by calculating the triangle area of the anchor nodes. Furthermore, the particle group optimization algorithm combines the genetic chaotic particle group theory, and finally, the improved particle group algorithm is used to correct the node position obtained by the DV-Hop algorithm. The simulation experiments show that improving the DV-Hop algorithm compared with the traditional D V-Hop algorithm to monitor the underground leakage accident position more accurately.

Supplementary Information for "Understanding Mid-to Large Underground Leaks from Buried Pipelines as Affected by Soil and Atmospheric Conditions – Field Scale Experimental Study"

Supplementary Information for "Understanding Mid-to Large Underground Leaks from Buried Pipelines as Affected by Soil and Atmospheric Conditions – Field Scale Experimental Study"

Development of an Intelligent Based Water Pipelines Damage Control System at the Supply Unit of the Federal Polytechnic Offa, Kwara State

Water is the most valuable means of life sustainability because it is a basic need of all households. The incessant water leakage levels in the water supply network on the mini campus, Federal Polytechnic Offa, is one of the most vital issues to address by the work unit on the School campus. Works unit provides services to all departments on campus, covering an area of the landmass of 1050 hectares with a population of staff and students of approximately 13 000. The work unit is in charge of correctional facilities and operation. The sub-service of the work unit on water supply system comprising a network of 1km of water pipes and 1500 litres capacity storage tower across units. The input system volume in the lose of water supply is approximately 56%, from which a significant proportion is about physical losses. This paper focused on intelligent-based leakage control to replace the traditional method used on campus parameters for backtesting tracing when physical damage becomes visible. However, the result of the study revolves around the design and implementation of a prototype system. The study created a management console as an intelligent decision support system. The realism of the study summarizes various operations by developing intelligent reporting software with data warehouse techniques to facilitate underground leak line pipes tracking.

Leak Detection in Smart Water Grids Using EPANET and Machine Learning Techniques

Water supply networks are liable to leakages, resulting in loss of large quantities of water. Hence, it is required to implement a leak detection and localization system through water network simulations and IoT enabled sensors which will enable faster leak detection and repairs to leaks such as underground leaks, which would otherwise go undetected for long durations. This study presents a clear and detailed procedure to set up the water network and leak simulation in EPANET, to generate the dataset, to apply machine learning classifiers to predict leakage and to apply the proposed system to a real-world leak detection system. Using extended period analysis in EPANET, emitters have been used to model leakages of various sizes and at different locations, while keeping in mind the real-world constraints. Leaks cause changes in the dynamic network parameters such as pressure and flow. This fact has been utilized for leak prediction implementation. Once the simulated model is validated, the trained machine learning classifiers can be used to predict and localize the leaks in real time.

Study of methane migration in the shallow subsurface from a gas pipe leak

With the increased use of natural gas, safety and environmental concerns from underground leaking natural gas pipelines are becoming more widespread. What is not well understood in leakage incidents is how the soil conditions affect gas migration behavior, making it difficult to estimate the gas distribution. To shed light on these concerns, an increased understanding of subsurface methane migration after gas release is required to support efficient leak response and effective use of available technologies. In this study, three field-scale experiments were performed at the Methane Emission Technology Evaluation Center in Colorado State University to investigate the effect of soil textural heterogeneity, soil moisture, and leak rate (0.5 and 0.85 kg/h) on methane migration caused by leaking pipelines. Subsurface methane concentrations, in addition to soil moisture and meteorological data, were collected over time. A previously validated numerical model was modified and used to understand the observed methane distribution behavior. Results of this study illustrate that the influence of soil texture, leak rate, and moisture on subsurface methane distribution is determined by the relative contribution of advection and diffusion and closely related to the distance to the leak source. Advection dominates gas transport within 1–1.5 m of the leak source, driving the migration of high concentration contours. Beyond this distance, diffusion dominates migration of lower concentration contours to the far-field. Although large leak rates initially result in faster and further gas migration, the leak rate has little influence on the diffusion dominated migration farther from the leak source. Soil moisture and texture complicate gas behavior with texture variations and elevated soil moisture conditions playing a dominant role in locally increasing methane concentrations. Scenarios highlight the importance of understanding the effects of soil moisture, texture, and leak rate on gas migration behavior in an attempt to unravel their contribution to the gas concentration within the soil environment.

Spatial variability of soil nutrients in seasonal rivers: A case study from the Guo River Basin, China

Agricultural non-point source pollution refers that substance such as nitrogen and phosphorus cause water environment pollution through surface runoff and underground leakage in agricultural production activities. Water environment pollution related to agricultural non-point source pollution in the Huaihe River Basin is becoming more and more prominent. Therefore, it is necessary to analyze the characteristic of soil nutrient in cultivated land and explore the spatial variation and influencing factors of soil nutrients at the watershed scale. A total of 239 topsoil samples were collected from the Guo river basin, and the related factors of soil organic matter (SOM), total carbon (TC), total nitrogen (TN), total phosphorous (TP), total potassium (TK) and potential of hydrogen (PH) were studied by using descriptive statistics and geostatistical methods. The results showed that TK and PH were weak variation, while SOM, TC, TN and TP were medium variation. Soil pH, TP, TK, TC and SOM had moderate spatial variability, which was caused by both random factors and structural factors such as soil texture, soil type, fertilization and local ecological restoration management. Soil TN showed a strong spatial correlation, mainly due to soil texture and soil type. If the recommended fertilization amount is still given based on the average value of soil nutrients ignoring the spatial heterogeneity, it will not only affect crop production efficiency and fertilizer utilization, but may also cause greater environmental pollution. This study can provide a theoretical basis for the management of agro-ecological environments throughout the basin area.

Research on Underground Chemical Gas Monitoring and Target Location Based on an Improved Moth Flame Algorithm

The danger of downhole work is mainly due to the chemical toxic gases and flammable gases NO2, CO, SO2, H2S, CH4, CO2, etc. When the concentration reaches a certain value, it will produce very great harm. With the continuous development of sensor technology and communication technology, it is necessary to monitor the relevant geographic features below the ground. Because of the complex environmental parameters of the coal mine roadway and the interference caused by various electrical equipment, the transmission of mine electromagnetic signals will be affected, resulting in low positioning accuracy. However, the underground chemical gas leakage leads to the life of underground workers which cannot be guaranteed, so it is necessary to effectively monitor the concentration of chemical gas components in underground mines. In this paper, a moth flame algorithm based on optimized inertia weights is proposed. By continuously improving the local inertia weights, the global optimum is determined by using the change of inertia weights in the iterative process of the algorithm. By testing the convergence and optimal value of several algorithms under common test functions, IMFO can obtain the global optimal solution. Finally, the concentrations of chemical gases NO2, CO, SO2, H2S, CH4, and CO2 are monitored by setting specific areas to see if they reach the early warning values. Then, 16 coordinates in the region are used to predict the above method, and the IMFO algorithm can achieve the best prediction effect.

SELF-POTENTIAL METHOD FOR DETECTION OF WATER LEAKAGE THROUGH DAMS

The self-potential (SP) method is a passive, non-invasive and cost-effective geophysical method based on the measurement of electrical potential naturally occurring on the earth’s surface. One of the main causes for the electrical potential at the earth’s surface is water seepage under the ground. In this work, we perform the SP measurement on a small artificial earthen dam built at Thuyloi University. Our result shows that the selection of electrode types is crucial in the SP measurements. Namely, Cu/CuSO4 porous pots are much better than copper stake electrodes for the SP measurement. Additionally, it is shown that the SP measurement using suitable electrodes can be applied to detect underground water leakage and flow direction in the dam based on an anomaly and variation of electric potential with position on the survey area.