Pipeline Location Research Articles

Pipeline leak detection and localization based on the flow balance and negative pressure wave methods

The traditional water supply pipeline leak detection and location method has problems of false alarms, low positioning accuracy, and low stability. This paper focuses on the pipeline leak detection and location experimental platform to investigate water supply pipeline leaks, followed by simulation and experimental validation. This study integrates the mass flow balance method and pressure change inflection points to determine pipeline leaks and introduces an improved negative pressure wave method for locating leakage points. The results demonstrate that the system accurately detects pipeline leaks. The average positioning error of the improved negative pressure wave method for the leakage point is 4.76%, which has good stability and high positioning accuracy.

Locating method of buried PE pipeline based on vibration signal analysis

Abstract This paper proposes a buried PE gas pipeline positioning method based on vibration signal analysis. Firstly, the collected signal is denoised using the Dual-tree complex wavelet transform (DTCWT) method, and then the delay time of the denoised collected signal is extracted through the cross-correlation function to locate the buried PE pipeline. A simulation model is established on this theoretical basis, and sensor asymmetric and symmetric arrangements are simulated in COMSOL to observe the peak values of the collected signal in the time domain, determining the relationship between the time difference of the two signals and the pipeline position. Through simulation, it is known that the pipeline location can be judged by the magnitude of the delay time. The method proposed in this paper addresses the shortcomings of existing pipeline positioning methods and provides a basis for future pipeline positioning.

Signals denoising of leakage pressure in water supply pipelines using an improved wavelet filter algorithm

Abstract Accurate identification of leakage pressure signal is crucial for leakage detection and location of water supply pipelines. However, there is a lot of noise signals in the negative pressure waves generated during leakage accidents, making it difficult to identify leakage signals, and thus seriously affecting the accuracy of leakage detection. Therefore, in this study, we carried out leakage test of water transmission pipeline on our self-built test platform for transient flow with long-distance water transmission pipeline (pipeline length is 160 m, and diameter is 100 mm), and obtained the transient leakage pressure signals under various flow rates (15–55 m3/h). An improved wavelet filtering algorithm was proposed to filter the leakage pressure signal by optimizing the calculation of decomposition layers and the threshold processing strategy, and then compared with the traditional wavelet filtering method. The results show that the improved algorithm can denoise the leakage signals effectively, and the signal-to-noise ratio (SNR), mean square error (MSE) and mean absolute percentage error (MAPE) are all superior to those of the traditional wavelet algorithm. The results can provide support for leakage detection and location of water supply pipeline systems.

Wave-induced sloping seabed residual response around a buried pipeline

Most studies of the wave interaction with pipeline were conducted on a flat seabed. This paper presents the results from the numerical modelling simulation to investigate the wave induced response around a half-buried pipeline on a sloping seabed. The numerical model is validated using the experimental data of the wave-pipeline-seabed interaction. The validated model is then applied to simulate the wave generated pore pressure distribution around the pipeline buried in the sloping seabed. Effects of the pipeline buried depth, the pipeline position and the slope gradient on the wave generated residual pore pressure as well as the potential soil liquefaction within the sloping seabed are simulated and analyzed. Results demonstrate that the pipeline location on the sloping seabed can significantly affect the residual pore pressure within the sloping seabed. This is particularly true when the pipeline is placed at the junction between the flat seabed and slope.

Detection of Harmful H2S Concentration Range, Health Classification, and Lifespan Prediction of CH4 Sensor Arrays in Marine Environments

Underwater methane (CH4) detection technology is of great significance to the leakage monitoring and location of marine natural gas transportation pipelines, the exploration of submarine hydrothermal activity, and the monitoring of submarine volcanic activity. In order to improve the safety of underwater CH4 detection mission, it is necessary to study the effect of hydrogen sulfide (H2S) in leaking CH4 gas on sensor performance and harmful influence, so as to evaluate the health status and life prediction of underwater CH4 sensor arrays. In the process of detecting CH4, the accuracy decreases when H2S is found in the ocean water. In this study, we proposed an explainable sorted-sparse (ESS) transformer model for concentration interval detection under industrial conditions. The time complexity was decreased to O (n logn) using an explainable sorted-sparse block. Additionally, we proposed the Ocean X generative pre-trained transformer (GPT) model to achieve the online monitoring of the health of the sensors. The ESS transformer model was embedded in the Ocean X GPT model. When the program satisfied the special instructions, it would jump between models, and the online-monitoring question-answering session would be completed. The accuracy of the online monitoring of system health is equal to that of the ESS transformer model. This Ocean-X-generated model can provide a lot of expert information about sensor array failures and electronic noses by text and speech alone. This model had an accuracy of 0.99, which was superior to related models, including transformer encoder (0.98) and convolutional neural networks (CNN) + support vector machine (SVM) (0.97). The Ocean X GPT model for offline question-and-answer tasks had a high mean accuracy (0.99), which was superior to the related models, including long short-term memory–auto encoder (LSTM–AE) (0.96) and GPT decoder (0.98).

Mechanical responses of shallowly buried pipelines to adjacent deep excavations considering heavy rainfall influence

Climate change has resulted in a high global incidence of heavy rainfall, severely damaging the urban infrastructure. The analytical method used to predict the mechanical response of pipelines under the influence of rainfall influence could serve as a valuable design basis in the preliminary stage. This study developed an analytical solution based on the stratified Green-Ampt model and displacement-controlled two-stage method. The first stage evaluates the greenfield soil displacement at pipeline elevation by employing the Mindlin solution and considering the superposed effects of excavation (unloading) and rainfall infiltration. The second stage predicts the mechanical responses of the pipeline by simplifying the pipeline–soil interaction into a continuous Euler–Bernoulli beam resting on a Winkler foundation model. The analytical solution was calculated using the finite difference method and verified against a published study. Finally, parametric studies were conducted to investigate the rainfall– excavation–pipeline interaction, including the rainfall intensity and duration, maximum lateral wall deflection, and pipeline location. The results showed that a 48-8-mm/h rainfall increased the maximum displacement and maximum bending moment of the pipeline by 6.54% and 7.93%, respectively. The prediction results provide practical guidance for designing deep excavations adjacent to pipelines buried under heavy rainfall conditions.

Gas pipeline leakage detection and location by using w-FBG array based micro-strain sensing technology

In addressing the significant security concerns associated with urban natural gas transportation, particularly the potential catastrophic consequences of leaks, this paper introduces a novel approach for detecting and locating leaks in natural gas pipelines using weak fiber Bragg grating (w-FBG) array micro-strain sensing technology. The field pipeline model is established, w-FBG array is applied to pipeline leakage experiment, and the pipeline leakage is detected by analyzing the change trend of micro-strain. The pipeline leakage experiments under different pressures were carried out. The experimental results show that there is a good linear relationship between the pipeline leakage pressure and the wavelength change of w-FBG, and the linearity is greater than 0.99, which is consistent with the theoretical analysis and verifies the applicability of w-FBG. According to the characteristics of micro-strain transfer in pipeline leakage process, a ‘abrupt change point’ capturing method based on peak to peak slope and threshold judgment is proposed. Results indicate that the proposed algorithm effectively detects pipeline leaks and accurately locates the point of leakage, with a positioning error of approximately 0.5 m. Compared with the traditional method, the proposed method has higher precision.

Superimposed imaging of acoustic wave reflections for the detection of underground nonmetallic pipelines

Due to the non-conductive and non-magnetic properties, nonmetallic pipelines are difficult to be detected by traditional pipe location technologies. This paper presents a superimposed imaging method of acoustic wave reflections for pipe location, which operates on the propagation of elastic waves. The propagation and attenuation model of elastic waves in soil are constructed according to the geometric relationship between the acoustic source, geophone array and pipelines. The two-dimensional and three-dimensional acoustic field diagrams of underground pipeline are generated by superimposed imaging of the cross-correlation coefficients between the signals from the sound source and geophone array, with the attenuation caused by hysteretic damping and geometric dissipation considered in the imaging process. In order to suppress clutter interference on the imaging results, the strategy of ‘multi-point transmit, multi-point receive and cross-correlation coefficient superposition’ is adopted. In the simulation, comparison is made to demonstrate the influences of different excitation sources on the detection imaging results, including the single frequency signal, multi-frequency signal, Gaussian pulse signal and sweep signal. It is found that the excitation signals with rich frequency components are more conducive to improving the resolution of detection images. The effectiveness of the proposed imaging method is further verified in the experimental work, which may be beneficial for the visualization and determination of the location, depth and orientation of underground non-metallic pipelines.

GPR detection localization of underground structures based on deep learning and reverse time migration

Ground penetrating radar (GPR) is widely used in detection localization of underground structure anomalous bodies. However, it is impossible to achieve accurate imaging localization of underground structures targets only by the waveform of GPR detection profiles due to the interference of clutter signals in engineering application. In this paper, a RefineNet deep learning network based on hybrid loss function is proposed to remove clutter signals in GPR profiles, and a reverse time migration (RTM) imaging algorithm based on total variation(TV) regularization is developed to perform migration imaging on GPR profiles processed by RefineNet network to realize accurate imaging localization of underground structures targets. Numerical simulations demonstrate that the developed RefineNet deep learning network can significantly remove clutter signals and improve GPR profiles quality, and the proposed RTM imaging algorithm based on TV regularization can accurately obtain location and shape information of underground structures targets. The full-scale experiment and field detection show that the proposed algorithm can accurately obtain the location of underground pipelines, cavities and other anomaly bodies. It is concluded that the developed algorithm provides a strong technical support for the GPR detection localization of underground structures targets.

Heat supply pipeline detection based on temperature gradient data of shallow ground

Heat supply pipelines are a critical component of urban infrastructure, with numerous underground projects relying on this crucial and often concealed system. In cases where blueprints are unavailable, it is crucial to determine the precise location and depth of heat supply pipelines. One of the most straightforward methods for detecting these pipelines is measuring underground temperature. Temperature gradient data is less sensitive to environmental temperature changes for detecting shallow heat sources than temperature data. This paper presents an extension of the correlation imaging method to handle temperature gradient data. This method can accurately determine the horizontal center position and the depth of the heat source. This temperature tomographic approach is reliable and has a high resolution, as evidenced by both synthetic and field examples.

Detection of subsurface water pipeline under SZJT Track Using Ground-Penetrating Radar Method

Surabaya’s public facilities and rapid infrastructure development will change the physical environment and require careful attention in all aspects of development. One aspect is the location determination of subsurface objects such as gas pipes, electrical cable lines, and water pipes. Lack of pipeline management and mapping can fail underground pipeline identification during excavation. The subsurface water pipe is one of the most important things to support people’s needs. Knowing the location of these pipes is essential for government agencies in carrying out maintenance, pipeline development, and repair activities. We identified the subsurface water pipeline using the Ground-Penetrating Radar (GPR) method. It is because of a non-destructive working type and very well applied in investigating underground infrastructure with significant electromagnetic contrast with the surrounding soil. We conducted this research around Surabaya Zoo and Joyoboyo Terminal (SZJT) track. We conducted data acquisition with the GPR GSSI SIR-3000 system with a shielded antenna frequency of 270 MHz on 21 measurement lines (JB07 to JB27). The aim is to determine the location, depth, and structure of the subsurface water pipeline at the research location. We processed the measurement data using MatGPR R-3.1 software by adjusting signal position, dc removal, dewow, median filter, inverse amplitude decay, background removal, K-L filter, bandpass filter, and time-to-depth conversion. We conducted 2-D and 2.5-D modeling to visualize the water pipeline. A hyperbolic anomaly, suspected to be a water pipe, is detected from the presence of high amplitude at a depth of 1 – 2 meters, which we saw in almost every line with velocity values from 0.0609 - 0.113 m/ns and dielectric constant value of 7.05 – 24.27. The 2.5-D modeling shows that the water pipeline continues from the research location’s south (Surabaya River) to the north.

Real-Time Leak Location of Long-Distance Pipeline Using Adaptive Dynamic Programming.

In traditional leak location methods, the position of the leak point is located through the time difference of pressure change points of both ends of the pipeline. The inaccurate estimation of pressure change points leads to the wrong leak location result. To address it, adaptive dynamic programming is proposed to solve the pipeline leak location problem in this article. First, a pipeline model is proposed to describe the pressure change along pipeline, which is utilized to reflect the iterative situation of the logarithmic form of pressure change. Then, under the Bellman optimality principle, a value iteration (VI) scheme is proposed to provide the optimal sequence of the nominal parameter and obtain the pipeline leak point. Furthermore, neural networks are built as the VI scheme structure to ensure the iterative performance of the proposed method. By transforming into the dynamic optimization problem, the proposed method adopts the estimation of the logarithmic form of pressure changes of both ends of the pipeline to locate the leak point, which avoids the wrong results caused by unclear pressure change points. Thus, it could be applied for real-time leak location of long-distance pipeline. Finally, the experiment cases are given to illustrate the effectiveness of the proposed method.

TMR-Array-Based Pipeline Location Method and Its Realization

Pipeline inspection is important to ensure the safe operation of pipelines. Obtaining the location of an underground pipeline is a prerequisite for most inspection technologies. Existing pipeline location methods can find a pipeline’s location, but they require multiple measurements and cannot be used by automatic inspection robots. In this paper, a tunnel magnetoresistance (TMR)-sensor-array-based pipeline location method is proposed to solve this problem. Firstly, a detection probe is designed using a TMR sensor array. It is calibrated by the improved ellipsoid fitting method to measure the magnetic field around the pipeline accurately. Secondly, a relative pipeline-position-locating method is proposed by detecting the phases of the magnetic induction signals at different frequencies. Thirdly, a three-dimensional pipeline location method is proposed. The horizontal and vertical distances and the angle between the pipeline and the probe are calculated by measuring the magnetic induction amplitude. Finally, a simulation model and a test platform are established, and the experimental results illustrate that, by adopting the TMR array, the three-dimensional pipeline location method can locate a pipeline in real time in three dimensions with good accuracy.

Optimization of pipe circuits in energy tunnels

Geothermal energy is a kind of green and renewable energy. Conventionally, ground source heat pumps can be used to harvest geothermal energy from the subsurface. To reduce the initial investment, a good solution is to use tunnel linings as heat exchangers to extract/dump heat. This special infrastructure is called an energy tunnel. In addition to the thermal performance, the impact of pipe network configuration on thermal efficiency is still challenging in the design of energy tunnels. To solve this problem, this study makes the first attempt to carry out research on the optimization of pipe circuits in energy tunnels by a series of numerical analyses. A fully coupled thermo-hydraulic 3D finite element model is established to investigate the response of tunnel-soil interaction under cyclical thermal loading (initial soil temperature varies from 8 °C to 18 °C), as well as the thermal transient interactions among air, absorber pipe, tunnel linings and ground, to quantify the amount of useful heat that can be extracted from the tunnel and the ground. On the other hand, the influence of 3 various heat-carrying pipes layout is also investigated. It is found that higher heat transfer efficiency can be obtained when the entrance and exit of pipelines are located below the tunnel in the study. The spatial location of pipelines will also affect the exchanged heat output.

Honor, Duty, and Service: A Blueprint for Creating Regional STEM Pipelines To Serve U.S. Military Veterans

Veterans face the possibility of unemployment after their transition into civilian life. Creating STEM pipelines for local communities that guide veterans towards long-term employment is necessary. The implementation of localized veteran pipelines in STEM is instrumental to ensuring that veteran unemployment numbers decrease. Focusing efforts to a small area, such as a fifty-mile radius around a town, fosters intimate connections among the veterans and other members of the pipeline. Pipeline localization gives each program its own support systems to support STEM careers in that specific location, making a difference for veterans in cities and towns everywhere. Enhancing the resources available for veterans to access long-lasting and meaningful careers in STEM is possible with veteran pipelines in STEM programming.

Application of recursive VMD based on information entropy optimization in the water supply pipeline leak location

Abstract The leakage point location of the water supply pipeline (WSP) can be estimated by the time difference of the leakage characteristic signals obtained from both ends of the pipeline. It is very important to extract the characteristic signal in the frequency domain to accurately locate the leakage point. The variational mode decomposition (VMD) has been proven to be effective in extracting leakage characteristic frequency domain signals, but it needs to set parameters in advance to adjust the signal processing effect. Therefore, it is proposed to initialize the center frequency required for the VMD with the frequency corresponding to the peak of the power spectrum of the original signal and then solve the preset problem of VMD decomposition layers by the recursive method. In addition, mutual information is used as a screening criterion for composite pattern functions to select appropriate pattern components to reconstruct signals. The actual leak location results show that the location errors of the proposed algorithm are only 0.20 and 1.66% for 23.3 and 38.9 m pipeline lengths, respectively. This shows that the proposed method can achieve the accurate location of the water leakage point under long measurement distances and complex interference.

Research on the Early Warning Model for Pipelines Due to Landslide Geohazards under Multiple Influencing Factors

Because of the wide distribution of overland oil and gas pipelines, some pipelines will unavoidably pass through landslide-prone mountainous areas. Landslides may cause deformation or even damage to pipelines, affecting the normal working of the pipeline system. Therefore, it is necessary to study the multiple influence factors of pipeline deformation caused by landslides and establish a forewarning model for oil and gas pipelines buried in landslides. In the present research, the field investigation and a series of large deformation numerical simulations are conducted along four pipelines located in the southeast region of China. Results show that small soil landslides are the main types of landslides threatening the safety of pipelines, whose deformation degree mainly depends on the scale of the landslides and the location of the pipelines in the landslides. Through the investigation, the scale of landslides is the main factor determining the deformation of pipelines induced by landslides. Considering the variation of the scale of landslides, with the increase of the angles, thicknesses, and lengths of the landslides, the pipeline deformation keeps increasing. When crossing the landslides laterally, the pipeline buried in the leading edge of landslides is safer than in the tail edge. What is more, it is most dangerous when the pipeline is buried in the middle of a landslide. Considering the variation of the scale of landslides, including the longitudinal length, horizontal width, thickness, and slope of landslides, as well as the location of pipelines in the landslides, a piecewise forewarning model including those parameters was established based on the influence function for crossing pipelines in landslides. The proposed forewarning model can be used for monitoring and evaluating landslide geological disasters of pipelines and reduce the risk of pipeline landslide geological hazards in the monitored area effectively.

Numerical simulation based on a weakly compressible model in the multi-elbow pipe

The negative pressure wave method is a more important method used for pipeline leak detection and location in practical engineering applications. In this paper, a new method based on a weakly compressible model and a standard k-e turbulence model is proposed, which is used to simulate the propagation of negative pressure waves in pipelines. The purpose of the study is to capture the negative pressure wave propagation phenomenon in multi-elbow pipe leaks based on the weakly compressible method and to investigate the negative pressure wave propagation law in multi-elbow pipes. The results show that the negative pressure wave transmission phenomenon inside the leaking pipeline can be calculated by using the weakly compressible model, and the transmission law is consistent with the actual one. It was found that the propagation velocity of the negative pressure wave in the elbow was 1.4% higher than that in the straight pipe, and there was backflow in each elbow, which affected the propagation distance of the negative pressure wave at different locations in the elbow. The vortex viscosity and turbulence frequency in the axis of the elbow were 12.2% and 5.4% higher than those in the straight pipe, respectively. In addition, the high viscous force and pulsation frequency in the elbow accelerate the volume compression and expansion of the flow elements, for which the equivalent length equation of the elbow in the negative pressure wave leakage localization method is proposed to verify the applicability of the weakly compressible model. The research in this paper reveals the internal effects of the negative pressure wave method in the bend as well as provides an innovative equivalence formula for the negative pressure wave leak location method. This work will provide a more accurate method for pipeline leak detection and localization.

Диагностирование и определение аномальных зон магистральных трубопроводов на подводных переходах с использованием цифровой модели рельефа

The article considers the issues of geodetic support for monitoring the technical condition of main gas pipelines underwater crossings (MGPUC). The purpose of the research is to increase the accuracy of determining the depth of the gas pipeline underwater crossings of main gas pipelines by taking into account the zones of faulty location of the pipeline (anomalous zones) and the bottom surface above MGPUC. The main problem of determining the technical condition of the gas pipeline underwater crossing is the difficulty of determining the depth of the gas pipeline due to the influence of external factors (soil, constructions and communications) on the measuring equipment (underwater trace detectors). The study indicates the accuracy of building digital elevation models (DEM) of the bottom, from which the calculation of the protective roll over the gas pipeline, which affects the determination of the technical state, and the causes of anomalous zones, as well as the ways of their determination. The variants of increasing the accuracy of calculating the depths of the gas pipeline location taking into account the DEM data are studied. The approach to definition of the method of spatial interpolation for construction of the bottom DEM according to the echolocation data depending on the surface curvature changes is offered. The authors note the interrelation of determining the criterion of technical condition of under-water crossing with the accuracy of DEM construction and determination of the spatial position of the pipeline. The proposed approaches are aimed at reducing the influence of the systematic part of the error and increasing the accuracy of the depth of occurrence, which is an urgent task.

Research on Leakage Location of Pipeline Based on Module Maximum Denoising

Leak detection and location of water supply pipelines is an important area of research, and it is especially important to find the leakage location in time and repair them. In view of the problem, that a large amount of noise is mixed in the detection signal when the pipeline leaks, it will inevitably affect the detection and positioning effect. In this paper, a denoising algorithm based on improved module maximum is proposed. Firstly, a discrete binary wavelet transform is carried out on the noisy signal, and the module maximum point corresponding to the wavelet transform coefficients, on each scale, is obtained. Secondly, different thresholds are used for the module maximum of different scale layers and the wavelet coefficients are reconstructed according to the retained module maximum and their extremums. Thirdly, the alternative projection algorithm is used to effectively suppress the false oscillations in the reconstructed signal, improve the quality of the reconstructed signal, and obtain the noise reduction signal. Finally, according to the theory of the negative pressure wave, the inflection point of the negative pressure wave is identified by the wavelet decomposition method, and the location of leakage point is determined. In order to verify the effectiveness of the proposed algorithm, a leakage simulation experiment system of water supply pipeline is built. The analysis of the results shows that, compared with the wavelet denoising method and the EMD-based method, the method proposed in this paper achieves a better denoising effect, obtains a smoother pressure signal, retains the signal waveform characteristics, and identifies the obvious inflexion point of the negative pressure wave. The minimum relative error of leakage point location is 0.9%, and the maximum relative error is 2.5%.