Leak Aperture Research Articles

Leak aperture recognition of natural gas pipeline based on variational mode decomposition and mutual information

The acoustic emission (AE) signals generated by natural gas pipeline leaks are affected by various noises, making the accurate extraction of feature signals a challenging task. Therefore, this paper introduces a novel adaptive signal denoising approach utilizing Variational Mode Decomposition (VMD).and mutual information (MI). Firstly, the parameters K and α of VMD are optimized using the energy difference. Simultaneously, the correlation coefficient between adjacent IMF components is used as the evaluation criterion to determine the optimal values of K and α. Then, based on MI, a screening criterion is proposed to select effective IMF components for reconstruction. Finally, the ISSA-SVM model was established by introducing Tent chaotic mapping and inertia weight adjustment strategy on the basis of the traditional sparrow search algorithm (SSA). Experimental results demonstrate that the proposed method effectively eliminates noise from pipeline leak AE signals, with a recognition accuracy reaching up to 96.09%.

Study on Leakage and Diffusion Behavior of Liquid CO2 Vessel in CCES

Numerical simulations of the leakage and diffusion behavior of liquid CO2 vessels and security analyses were conducted in this paper, based on a CO2 compression energy storage system. With isentropic choking model, the leakage of vessels under specific conditions was numerically simulated. The influence of different wind speeds on leakage in near-zone field was studied. Meanwhile, the diffusion characteristics of CO2 under three different influencing factors were investigated with the UDM (Unified Dispersion Model) diffusion model, and the diffusion ranges of certain concentrations were detected in the far-zone field. The results show that the low-temperature zone of the 50 mm leak aperture can reach 0.74 m downwind, and basically does not change with wind speed. In the leakage direction, the maximum damage zone of high-speed flow can reach 7.70 m. For the far-zone field, the diffusion area and downwind distance of a dangerous concentration decrease with the increasing of wind speed, and the hazardous area of the low concentration is greatly affected. Based on specific conditions, the maximum diffusion area is 78.46 m2 at 1 m/s wind speed, and the dangerous range reaches 36.32 m downwind. The larger the leakage aperture, the faster the growth trend of the low concentration area under the same conditions. As the equivalent radius of the leakage aperture is less than 50 mm, the maximum diffusion area is proportional to the cubic of the leakage aperture radius. The higher the height of the leakage source, the smaller the concentration range at 1.5 m, which is the average human breathing height. The overall cloud moves upward, meaning that the ground risk decreases. When the leakage aperture is 50 mm and the wind speed is 1 m/s, the maximum cloud diffusion range is 857.35 m2 at the leakage height of 2 m, and the dangerous range reaches 109.53 m downwind, where the maximum concentration is 14.65%.

Study on temperature field distribution and leakage point localization of buried carbon dioxide pipeline leakage

Leakage from buried CO2 pipelines is a critical issue in the context of carbon capture and storage (CCS). Therefore, we developed a small-scale experimental system for buried CO2 pipeline leakage. to investigate the effects of leak pressure, leak aperture size, and soil type on the temperature distribution near the leak point. The results of the study showed that the lowest soil temperature appeared directly above the leak. The minimum temperature at the soil axial measurement point increased with increasing leak pressure, but the peak maximum temperature difference decreased. 3 mm and 5 mm leak pore sizes, the peak maximum temperature difference occurred at 10 cm and 20 cm, respectively. At all pressures, the maximum temperature difference peaked at 20 cm. Soil surface temperature variations were mainly influenced by leak pressure. The maximum peak temperature difference at the soil surface measurement points also increased with increasing leak pressure. Smaller leakage apertures slowed down the decrease of soil surface temperature. In addition, based on the experimental results, we propose a new method to locate leaks based on the soil temperature gradient.

Research on the hydraulic parameters and leak rate of natural gas flow in natural gas pipelines based on the methods of characteristic line and successive approximation

Pressure and flow rate are the most important hydraulic parameters in natural gas pipeline flow, and leak rate is the most crucial parameter after a leak accident occurs. The study of these parameters is vital to the safey of natural gas pipelines and risk assessment after accidents. In this research, based on the conservation laws universally applicable to the motion of objects, we establish the fundamental control equation group for natural gas flow. Then, for both normal and leak conditions of pipelines, we use the characteristic line method to derive the corresponding difference equations for the fundamental control equations, thereby providing calculation methods for pressure and flow rate. Finally, we investigate the calculation method of natural gas pipeline leak rate under different leak aperture sizes, and validate the accuracy of this method through simulation examples.

Application of Distributed Acoustic Sensing Technology in Pipeline Leakage Monitoring

Pipeline leak monitoring is an important industrial safety measure designed to ensure the safety of liquids or gases during transportation. Distributed acoustic sensing (DAS) technology is based on the reverse Rayleigh scattering inside the fiber to reflect the change of the measured physical quantity, and has great advantages in monitoring range, environmental adaptability, transmission loss control and system stability. In this paper, the pipeline leakage monitoring technology based on distributed acoustic sensing fiber is used to study the leakage signal of small leak aperture. In order to improve the sensitivity of leakage monitoring, the optical fiber is spiral wound on the pipe section. The identification method of pipeline leakage signal based on fast Fourier transform is proposed. By analyzing the vibration of the optical fiber in the time domain and the frequency domain, the leakage signal can be accurately monitored. Pipeline leakage tests with different leak apertures were carried out, and the leakage locations were studied by energy attenuation and cross-correlation techniques. The experimental results show that the time-domain signal fluctuates obviously and the full-band energy of the frequency-domain signal increases after pipeline leakage. The increase of leakage diameter will gradually increase the signal energy, and the leakage energy will gradually move from high frequency to low frequency. The energy attenuation positioning technique can locate the leakage within the range of a single sensing unit, and determine the leakage location through cross-correlation analysis with an error of less than 3 m.

Predicting leak aperture in the pipeline of ultra-long coal mine working faces under strong noise interference based on joint denoising and random forest

Ultra-long coal mine working faces are characterized by harsh conditions, making water supply pipelines susceptible to leakage incidents, posing risks to both personnel and equipment safety. However, detecting leaks using infrasound signals is challenging due to complex environmental noise interference. Additionally, spatial constraints make inspections difficult for maintenance personnel. Hence, it is vital to enhance the clarity of leakage data and accurately assess leak severity for effective pipeline maintenance. This study combines Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Sparse Representation (SR) techniques to create a signal processing model. This model serves two purposes: reducing extraneous noise interference and enhancing leak-related signals. Subsequently, we analyse leak signal characteristics across various operational scenarios and formulate a leak severity assessment model using the Random Forest (RF) algorithm. Empirical experiments confirm its effectiveness, with a root mean square error (RMSE) of 0.1135 millimeters between predicted and actual leak severity values. This result validates the method’s efficacy in estimating leak severity in water supply pipelines, offering a dependable approach to enhance pipeline maintenance and operations.

Pipeline leakage aperture identification method based on pseudolabel learning

Aiming at the problem of insufficient label data in the pipeline leak detection field, this paper proposes a pseudolabel (PL) adaptive learning method based on multiscale convolutional neural network (MSCNN) with the idea of transfer learning for pipeline leak aperture identification. First, the convolutional and pooling layers for transfer learning feature extraction are improved by using a dual-channel MSCNN. Second, the KL divergence function after dimensionality reduction is used to calculate the distribution distance between the source domain and the target domain to improve the robustness of distribution alignment in high-noise environments. In addition, considering the interference of PL noise, this paper develops a pseudolabel (PL) dynamic threshold to achieve the purpose of PL adaptive updating. Compared with the fixed threshold, the improved PL learning (PLL) can effectively improve the prediction accuracy of the model. The effectiveness of the method proposed in this paper is verified by predicting pipeline leakage conditions at different distances and under different pressures. The comparative analysis results show that the method in this paper is superior to other transfer learning methods in terms of prediction accuracy, stability, and convergence speed.

Study on the leakage dispersion law of exposed high-pressure natural gas pipelines in the mountainous environment

The pipelines in mountainous areas have complex terrain conditions and pass through many densely populated areas. Once a pipeline leakage accident occurs, it will cause serious damage to the surrounding people and the environment. In this article, a leakage diffusion model of a bare natural gas pipeline is established for the exposed leakage scenario, and a simulation scheme is established according to the characteristics of pipeline-laying processes and environmental characteristics in mountainous areas. Research has been carried out on the diffusion pattern and the influence range of exposed gas transmission pipeline leaks under four types of factors: different leak apertures, ambient wind speed, mountainous obstacle conditions, and mountainous laying environment. The dangerous range formed by the gas diffusing along the ground and high altitude under different scenarios and the influence law of different influencing factors on the dangerous range are obtained, and suggestions for emergency rescue focus areas and emergency response strategies have been given. The research conclusions can provide a theoretical basis for emergency response strategies for exposed leakage accidents of high-pressure natural gas pipelines in mountainous environments and are of great significance to the quantitative analysis of the risk consequences of natural gas pipelines.

FLACS-Based Simulation of Combustible Gases Leaked from the Pressure Device for the Optimizing of Gas Detectors’ Setup

The leakage and diffusion of hazardous gases from steam methane reforming (SMR) equipment are investigated by Flame Acceleration Simulator (FLACS) software to optimize the layout of combustible gas detectors. A typical accident scenario, with the gases leaked from converter tubes with leak apertures of 5 mm, 25 mm, and 100 mm and medium pressure of 0.1 MPa, 1 MPa, and 10 MPa, is established. At the same time, the influence of the environment wind speeds from 0.2 m·s−1 to 6 m·s−1 on the diffusion process is also investigated. The research results show that the leakage source concentration and diffusion distance positively correlate with the leakage aperture. Suggestion on the distance between combustible gas detectors and possible leak point is within 5 m, 10 m, and 15 m in the scenario of the leak aperture of 5 mm (small-hole leak aperture), 25 mm (middle-hole leak aperture), and 100 mm (big-hole leak aperture). The most dangerous scenario is at the static ambient wind speed, and the diffusion process strengthens with the raising of wind speed. The turning point scenario occurs at a wind speed of 1 m·s−1, where the flammable area is minimal. The medium pressure relates to the jet speed of the combustible gases. The wind speed should be comprehensively determined when considering the layout of the combustible gas detectors affected by this factor. The orthogonal experimental design shows that the most significant influence factor on the diffusion process of the combustible gas is the leak aperture, followed by the medium pressure and, finally, by the ambient wind speed. Recommendations are listed for the optimization of the layout of gas detectors in related enterprises.

Characterization of carbon dioxide leakage process along faults in the laboratory

It is important to understand the process of multiphase carbon dioxide (CO 2 ) leakage in faults for the risk assessment of carbon capture and storage (CCS). To quantitatively characterize the CO 2 leakage process in the fault, pressure sensors, fiber Bragg grating (FBG) temperature and strain sensors were simultaneously used to monitor CO 2 leakage in the fault. Ten experiments were carried out, including five groups of gaseous CO 2 leakage tests with initial pressures of 1–5 MPa and five groups of liquid CO 2 leakage tests with initial pressures of 6–10 MPa. The results indicate that when liquid CO 2 leaked with an initial pressure of 7–10 MPa, the pressure and temperature of CO 2 dropped rapidly in the first few seconds and then remained unchanged. The behavior that CO 2 continues to leak while maintaining temperature and pressure unchanged is defined as “temporary pseudo-sealing (TPS)” behavior, which continues for the first 1/3 of the leakage period. However, this TPS behavior did not occur in gaseous CO 2 leakage. If only the pressure and temperature data were used to evaluate whether CO 2 leakage occurred, we would misjudge the risk of leakage in CCS projects during the TPS period. The causes and conditions of TPS behavior were further studied experimentally. The results show that: (1) TPS behavior is caused by the phase transition energy generated when liquid CO 2 leaks. (2) The condition for TPS behavior is a small leak aperture (0.2 mm). Only a small leakage rate can make the phase transition energy and pressure change from a dynamic equilibrium, and (3) The compression zone caused by the Bernoulli effect and fault “barrier” could reduce the CO 2 leakage rate and further promote the occurrence of TPS behavior. This study provides technical and theoretical support for the quantitative characterization of the CO 2 leakage process in faults of CCS projects.

Leak Identification Based on CS-ResNet Under Different Leakage Apertures for Water-Supply Pipeline

Considering the problem of difficulty in transmission and storage due to a large amount of data in the water-supply network monitoring system based on a wireless sensor network (WSN), we propose a sparse representation of the water-supply network monitoring data by using compressed sensing (CS) method. At the same time, aiming at the problem of low leakage identification accuracy caused by information loss under compressed sensing, we propose a leak identification method for a water-supply pipe network based on compressed sensing and deep residual neural network (ResNet). Firstly, under the condition that the observation matrix ensures the integrity of signal information, the compressed sensing theory is used to compress and observe leakage signals to obtain observation data, to reduce the redundant information and volume of the data. At the same time, the observation data is preprocessed to realize the transformation of a one-dimensional signal to a two-dimensional matrix. Then the residual neural network is trained by using the two-dimensional data to realize the automatic, efficient, and accurate leak identification under different leakage apertures. Experimental results show that the proposed method can obtain relatively high accuracy and greatly reduce the training time of ResNet by using compressed data. When the Compression rate (CR) is 70% and the observation matrix is a Gaussian random matrix, the average accuracy is 96.67% and the training time is only 50% compared to uncompressed data. The research work provides a new intelligent leak identification under different leak apertures using WSN and has important application prospects in saving water resources.

Electrification hazard of turbulent pipe flow: Theoretical approach and numerical simulation

The present paper deals with electrostatic characteristics, i.e., space charge density and electrostatic potential under turbulent flow in pipes with and without leakage. This paper considers the charge conservation equation and proposes theoretical models able to calculate the space charge density of intact and leak pipes. The distributions of the space charge density and electrostatic potential are investigated through numerical simulation. For the case study used for validation purposes, the space charge density obtained by numerical simulations is compared with the experimental results. The results show that the proposed model is capable of calculating adequately the distribution of the space charge density in pipes. The effects of flow velocity and pipe diameter on the electrostatic characteristics of intact and leak pipes are then investigated. The results show that, for intact pipes, the maximum electrostatic potential appears in the central area of the pipe and increases slowly with the increase of the velocity, while the maximum potential decreases with the increase of the pipe diameter. For leak pipes, the maximum potential takes place at the leak aperture, and increases with the increase of flow velocity and pipe diameter. In order to reduce the possibility of electrostatic discharge, the flow velocity ought to be controlled below 2.5 m/s, and the pipes with smaller diameter shall be used as far as possible when meeting the requirement for use.

Experimental study on the amplitude characteristics and propagation velocity of dynamic pressure wave for the leakage of gas-liquid two-phase intermittent flow in pipelines

Intermittent flow is one of the most complex flow patterns in gas-liquid two-phase flow in pipelines. The leakage of pipeline intermittent flow poses a threat to the operating safety. In order to improve the application of acoustic method to gas-liquid two-phase leakage detection, the amplitude characteristics and propagation velocity of dynamic pressure wave of intermittent flow for gas-liquid two-phase pipeline leakage were investigated. Experiments with conditions of superficial liquid velocity (vsL) from 0.57 m/s to 1.06 m/s, superficial gas velocity (vsG) from 0.3 m/s to 4.47 m/s, leakage aperture from 4 mm to 9 mm were carried out, and the characteristics were studied by time-domain analysis, frequency-domain analysis and time-frequency analysis. The propagation velocity formula of dynamic pressure wave in two-phase medium was fitted based on Levenberg-Marquardt algorithm, and the propagation velocity of straight pipe and elbow pipe was discussed. The experimental results indicate that the peak-to-peak value of dynamic pressure wave measured by sensor within 4.25 m increases during top or mid sustained leakage when leak aperture is larger than 4 mm in elongated bubble flow and 6 mm in slug flow. The amplitude of sustained leakage dynamic pressure increases as gas flow rate increases. The low frequency energy of signal increases immediately when leakage occurs, the energy of signal mainly concentrates at 0–15 Hz, the frequency amplitude of sustained leakage signal is much higher than normal flow signal and leak occur signal. As the gas volume fraction β increases from 0.23 to 0.75, the dynamic pressure propagation velocity decreases from 33.13 m/s to 26.5 m/s and then increases from 26.5 m/s to 66.25 m/s. The propagation velocity increases when it flows through an elbow pipe section. The results are meaningful for further study of two-phase pipeline slug flow leakage detection and location.

An Ultrasonic-Based Detection of Air-Leakage for the Unclosed Components of Aircraft

Air-leakage detection is among the most important processes at the assembly stage of unclosed components, especially for large aircraft. A series of air-leakage detecting methods are generally applied during the final assembly, nevertheless, many of them are less effective to detect the leakage at the assembly stage. The present study aims to discuss the principles of ultrasonic generation in negative pressure conditions to detect the air-leakage. An ultrasonic-based detection method is proposed and designed to detect the air-leakage of unclosed components for aircraft. A relationship between the acoustic power, sound pressure, and the leak aperture detection distance was identified and discussed. A leakage rate model related to leakage rate, leak aperture, and system pressure was implemented and confirmed through experiments. Findings have indicated that the air-leakage can be detected effectively within a detection distance of 0.8 m and a leak aperture greater or equal to 0.4 mm with this method. Besides, the leak location, leak aperture, and leakage rate was acquired in an accurate and fast way. It is an effective method of detecting the air-leakage of unclosed components at the aircraft assembly stage reducing the testing time, energy consumption, and cost for the air-leakage detection in the final assembly stage of large aircraft.

Modified Leakage Rate Calculation Models of Natural Gas Pipelines

The leakage rate is an essential parameter for the risk assessment and failure analysis of natural gas pipelines. The leakage rate of a natural gas pipeline should be calculated quickly and accurately to minimize consequences. First, in this study, models to estimate the leakage rate of natural gas pipelines are reclassified, and the theoretical range of application for each model is also analysed. Second, the impact of the leakage on the flow rate upstream of the leak point is considered, and the method of successive approximation is used to realize this feedback effect of flow rate change. Then, a modified hole-pipe model is developed to calculate the natural gas leakage rate in this paper. Compared with the leakage rate calculated by the hole-pipe model, the leakage rate calculated by the modified hole-pipe model is smaller and closer to the actual leakage rate due to the consideration of the feedback effect of the flow rate change. Finally, the leakage rate curves of the hole-pipe model and the modified hole-pipe model under different d/D conditions are obtained through simulation. The simulation results show that the modified hole-pipe model is able to calculate the leakage rate of any leak aperture, such as the hole-pipe model, and also at a higher accuracy level than the hole-pipe model.

Numerical simulations on the leakage and diffusion of tritium

Based on the knowledge that the surroundings of tritium leakage and diffusion in hydrogen storage vessels can be either open space or closed space, the subsonic jet flow of a slow tritium leak from a hydrogen storage bed under open and closed spatial conditions is simulated by Fluent finite element software. Furthermore, the quantitative relationship between mass flow rate and time is established by using the user defined function (UDF) to compile interface codes. The subsonic tritium jet, velocity profiles, tritium diffusion distance, and the tritium concentration along the jet trajectory are obtained in two different scenarios (open space and closed space). The results show that the closed space inhibits the vertical convection diffusion of tritium and has a favorable improving effect on the horizontal convection diffusion of tritium, whereas the open space has the opposite influence on the convection diffusion of tritium. In addition, an eddy current whirlpool develops under the closed space condition. The concentration distribution along the jet center line can be significantly influenced by the spatial boundary condition and leak aperture. An increase of leak aperture facilitates vertical diffusion of tritium and the velocity near the leakage hole. The oblique downward wind and horizontal wind lead to an enhancement of tritium cloud horizontal drifting. The oblique upward wind can be considered as a method to effectively dilute leaked tritium concentration.

Leak detection and location of flanged pipes: An integrated approach of principle component analysis and guided wave mode

As flanged pipes have a crucial role in oil and gas transportation, accidental leaks and their detection are of great importance, and represent a great concern in safety management of pipes. The present study develops an integrated approach, based on acoustic emission (AE) signals, in order to detect and locate leaks in flanged pipes. It is depicted into two main steps: leak detection (leak regional location) and precise leak location. The proposed method adopts the principal component analysis (PCA) as a semi-supervised learning method, relying on the Hotelling’s T2 statistic and the Q statistic (squared prediction error (SPE)) as the residuals, to detect the leak occurrence. Once the leak pipe segment is located, the precise leak location adopts variational mode decomposition (VMD) to decompose the leak AE signals to obtain the domain frequency band for determining the wave speed in combination with the dispersive curve of guided wave. Furthermore, de-noised signals can be obtained by reconstructing the intrinsic mode functions (IMF) of the VMD based on the energy ratio and after the basic cross-correlation is calculated to obtain the time delay of the de-noised signals. For illustrative purposes, an experimental setup, which includes 5 different leak apertures (10, 12, 15, 20 and 27 mm), is used for investigation. The experimental validations show that the PCA-based method can detect and locate a leak in a certain pipe segment. In addition, the precise leak location errors are all in acceptable interval values ranging from 0.8% up to 12.1%.

An improved variational mode decomposition method based on particle swarm optimization for leak detection of liquid pipelines

Leak detection is critical for the safety management of pipelines since leakages may cause serious accidents. The present paper aims to develop an efficient method able to detect the presence and importance of leaks in pipelines.This method relies on adequate signal processing of acoustic emission (AE) signals, and improves the variational mode decomposition (VMD) for signal de-noising. In order to optimize the governing parameters, i.e. the penalty term and the mode number of VMD, the particle swarm optimization (PSO) algorithm is coupled to a fitness function based on maximum entropy (ME). After the signal reconstruction, based on the energy ratio of each VMD sub-mode, the waveform feature vectors for leak detection are extracted. Finally, the support vector machine (SVM) is employed for leak pattern recognition. For calibration purposes, artificial input signal is simulated. The results show that the proposed PSO-VMD method is capable of de-noising background noise.For validation purposes, experiments have been conducted on metal pipelines, with water flow. For sensitivity analysis, a set of five different leak apertures are adopted: aperture diameters as {10; 12; 15; 20; 27} mm, whereas the pipeline diameter is 108 mm. A database of AE signals is collected for each leak aperture, and different time sequences. The proposed method appears to be efficient since the classification accuracy of the SVM method reaches up to 100% in identifying the size of the leak on the basis of the AE signals collected in the database for the same leak size, and 89.3% on the basis of the whole database.

Study on acoustic source characteristics of gas pipeline leakage

The characteristics of acoustic source of gas pipeline leakage determine the accuracy and adaptability of leak detection for gas pipelines based on acoustic method. In order to explore the characteristics of leakage acoustic source of gas pipeline, a physical model of gas pipeline leakage was developed. Initially, generation mechanism of acoustic source of gas pipeline leakage is studied in order to identify the basic principle of leak detection of gas pipeline based on acoustic method. After that, the simulation model is developed according to the basic principle of aeroacoustics, the flow field, and sound source characteristics of the gas pipeline leakage. Then, the experimental platform for the study on acoustic source characteristics of gas pipeline leakage is set up using the basic principle of the leak detection based on acoustic method and simulation results. The characteristics of acoustic source of leakage are obtained through experiments. Finally, the simulation and experimental results of acoustic source of leakage under different operating conditions are compared, and the accuracy of the simulation results is verified, which provides a theoretical basis for the engineering application of leak detection for gas pipeline based on acoustic method. The results show that the acoustic source of gas pipeline leakage is mainly quadrupole source and the leakage acoustic energy is mainly in the range of less than 100 Hz. The mean value of sound pressure level is increased with the pressure in pipeline and the size of leak aperture.

Leak Detection and Location Based on ISLMD and CNN in a Pipeline

The key to leak detection and location in water supply pipelines is signal denoising and feature extraction. First, in this paper, an improved spline-local mean decomposition (ISLMD) is proposed to eliminate noise interference. Based on the ISLMD decomposition of a signal, the cross-correlation function between the reference signal and the product functions component can be obtained. And then the PF component containing the leak information can be extracted reasonably. Compared with improved local mean decomposition, the ISLMD has higher accuracy in leak location. Second, an image recognition method using a convolutional neural network for leak detection is proposed, which can better address the problem that the features of different leak apertures or locations are highly similar to each other. The images from the conversion of the reconstructed signals are used as the input of the AlexNet model, which is capable of adaptive extraction of leak signal features. The trained AlexNet model can effectively detect different leak apertures. Finally, the signal time-delay between the upstream and downstream pressure transmitters caused by the leak and propagation of negative pressure wave is determined according to generalized cross-correlation analysis, and thereby, the leak location is obtained. The experimental results show that the proposed method is effective for leak detection and location.