Negative Pressure Wave Research Articles

QUALITATIVE ANALYSIS OF TEMPERATURE ERROR OF NEGATIVE PRESSURE WAVE METHOD FOR DETERMINING THE LOCATION OF A PIPELINE LEAK

The article is devoted to the qualitative analysis of the temperature error of the negative pressure wave method for determining the location of a pipeline leak. Recording the arrival time of the negative wave at both ends of the pipeline allows you to determine the location of a pipeline leak. In contrast to known works on this topic, this article proposes a method for qualitative analysis of the error in determining a leak location. Based on the variational optimization method, an optimal ratio of the mode indicators at which the minimum error in determining the location of a leak can be achieved is defined. A method for qualitative analysis of the error in determining the leak location using the negative pressure difference wave method is proposed. The optimal correlation of the mode functions is determined at which the minimum error in determining the leak location is achieved. An expression for estimating the relative error in determining the leak location using the negative pressure difference wave method is obtained.

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.

Research and Application of Leakage Monitoring Techniques for Gas Field Water Pipelines

Abstract To study the effectiveness and application effects of leakage monitoring techniques for gas field water pipelines in the Sichuan-Chongqing region, seven kinds of flow limitation holes with different diameters were used to simulate the leakage of the gas field water pipeline to carry out a field test. The monitoring conditions of two leakage monitoring techniques, namely dynamic pressure wave compound method and negative pressure wave and transmission balance method, were compared and analyzed under different working conditions. The test results showed that: (1) When the pipeline was full, the leakage with apertures being smaller than 2 mm could not be effectively monitored. A single-end alarm could be achieved using the dynamic pressure wave compound method, but the positioning was ineffective. An alarm could not be effectively achieved using the transmission balance method. (2) When the pipeline was full, for the leakage with apertures being 2 mm and above, early warning could be well achieved using the both methods, and the monitoring effects were nearly the same, with the average positioning error being about 48 m and the average alarm response time being about 58 s. (3) When there were empty pipe slug flows in the pipeline, only apertures being 5 mm and above could be alarmed; however, positioning could not be effectively achieved, and system technical indicators could not be reached. (4) When there were large elevation differences in the gas field water pipeline and empty pipe slug flows could not be eliminated, the both techniques were not applicable.

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.

Cyclic Aspiration in Mechanical Thrombectomy: Influencing Factors and Experimental Validation.

Mechanical thrombectomy is a fundamental intervention for acute ischemic stroke treatment. While conventional techniques are effective, cyclic aspiration (CyA) shows potential for better recanalization rates. We aim to investigate factors affecting CyA and compare them with static aspiration (StA). StA setup consisted of an aspiration pump connected to pressure transducer. CyA was tested with 5 subsequent iterations: single solenoid valve with air plus saline (i1) or saline alone (i2) as aspiration medium; 2 solenoid valves with air plus saline (i3) as aspiration medium; complete air removal and saline feeding (i4); and pressurized saline feeding (i5). To assess the efficacy of clot ingestion, the pressure transducer was replaced with a distal aspiration catheter. Moderately stiff clot analogs (15 mm) were used to investigate the ingestion quantified as clot relative weight loss. Additionally, the aspiration flow rate was assessed for each setup. With CyA i1, the amplitude of the achieved negative pressure waves declined with increasing frequencies but progressively increased with each subsequent iteration, achieving a maximum amplitude of 81 kPa for i5 at 1 Hz. Relative clot weight loss was significantly higher with i5 at 5 Hz than with StA (100% versus 37.8%; P = .05). Aspiration flow rate was lower with CyA than with StA (i5 at 5 Hz: 199.8 mL/min versus StA: 311 mL/min; P < .01). CyA with the appropriate setup may represent an encouraging innovation in mechanical thrombectomy, offering a promising pathway for improving efficacy in clot ingestion and recanalization. The observed benefits warrant confirmation in a clinical setting.

Research on Signal Noise Reduction and Leakage Localization in Urban Water Supply Pipelines Based on Northern Goshawk Optimization.

In order to enhance the accuracy and adaptability of urban water supply pipeline leak localization, based on the Northern Goshawk Optimization, a novel joint denoising method is proposed in this paper to reduce noise in negative pressure wave signals caused by leaks. Firstly, the Northern Goshawk Optimization optimizes the decomposition levels and penalty factors of Variational Mode Decomposition, and obtains their optimal combination. Subsequently, the optimized parameters are used to decompose the pressure signals into modal components, and the effective components and noise components are distinguished according to the correlation coefficients. Then, an optimized wavelet thresholding method is applied to the selected effective components for secondary denoising. Finally, the signal components that have been denoised twice are reconstructed with the effective signal components, and the denoised negative pressure wave signals are obtained. Simulation experiments demonstrate that compared to wavelet transforms and Empirical Mode Decomposition, our method achieves the highest signal-to-noise ratio improvement of 12.23 dB and normalized cross correlation of 0.991. It effectively preserves useful leak information in the signal while suppressing noise, laying a solid foundation for improving leak localization accuracy. After several leak simulation tests on the leakage simulation test platform, the test results verify the effectiveness of the proposed method. The minimum relative error of the leakage localization is 0.29%, and an average relative error is 1.64%, achieving accurate leakage localization.

A Bayesian detector-based approach for determining arrival and departure times of negative pressure waves in pipeline leakage localization

A Bayesian detector-based approach for determining arrival and departure times of negative pressure waves in pipeline leakage localization

Model for the Failure Prediction Mechanism of In-Service Pipelines Based on IoT Technology

With the rapid increase in pipeline mileage in China, the accurate prediction of corrosion issues in in-service pipelines has become crucial for ensuring safe pipeline operation. Traditional pipeline leakage monitoring methods are significantly limited by human factors and equipment precision, making it challenging to predict and identify leakage points accurately. Therefore, aligned with the trend of intelligent pipeline development, this study aims to construct a failure pressure prediction mechanism model for corroded pipelines based on IoT technology. This model leverages intelligent sensing and prediction to assess the safety status of corroded pipeline sections. Ultrasonic phased array technology detects specific corrosion points and detailed defect parameters within pipeline sections. The parameters are then utilized in the Simdroid domestic finite element analysis model to simulate the ultimate burst pressure of the pipeline. A single-variable approach is employed to analyze the sensitivity of different parameters to the pipeline’s ultimate burst pressure, with the minimum burst pressure point of multi-point corroded sections selected as the overall segment failure pressure. Finite element simulation data are integrated into a neural network database to predict the pipeline failure pressure. The real-time operational data of the pipeline are monitored using negative-pressure wave sensing. The operational pressure of the corroded points is compared with the algorithm-predicted failure pressure; if the values approach a critical threshold, an alarm is triggered. Moreover, the remote control terminals evaluate the pipeline’s self-rescue time, providing a buffer for pipeline leakage self-rescue. The failure prediction mechanism model for in-service pipelines was applied to the Fujian–Guangdong branch of the West–East Gas Pipeline III to verify its accuracy and feasibility. The research results offer technical support for the maintenance and emergency repair of pipeline leakage scenarios, leveraging intelligent pipeline technology to reduce costs and increase the efficiency of pipeline operations, thereby supporting the sustainable development of China’s oil and gas pipelines with theoretical and technical backing.

Research on Leak Detection of Low-Pressure Gas Pipelines in Buildings Based on Improved Variational Mode Decomposition and Robust Kalman Filtering.

Aiming at the complex characteristics of negative pressure waves in low-pressure pipelines inside of buildings, we proposed an estimation method of pressure fluctuation trends based on the robust Kalman filter and the improved VMD, which can be used for leakage detection. The reconstructed baseline signal can accurately describe the fluctuation trend of the negative pressure wave after the pressure drop, and quantitatively express the characteristic difference between the leakage condition and the gas usage condition. The robust Kalman filter was used to estimate the pressure fluctuations. The parameters of VMD were adaptively calculated based on the WAA and discrete scale space. The trend components contained in the IMFs were separated by a reconstruction based on the Fourier series. Based on the simulation signal, the method can accurately restore the trend component contained in the complex pressure signal. Based on the actual signals, the accuracy of small leakage detection is 96.7% and the accuracy of large leakage detection is 73.3%.

Leak monitoring and positioning of pressurized water pipeline network

Due to the presence of numerous branches in the pressurized water pipeline network (PWPN), leak-caused negative pressure wave (NPW) has non-unique propagation path, so leak detection and positioning for PWPN is highly challenging. This paper proposes a leak monitoring and positioning method for PWPN based on the time delay matching of NPW propagation. Via introducing the NPW velocity equation, the PWPN is divided into short segments with equal NPW propagation duration, and then the shortest NPW propagation path from each discrete point, namely hypothetical leak point, to each deployed pressure transmitter, is efficiently numerically searched and then used to calculate the NPW arrival time and establish a contrastive time delay library (CTDL) in advance. A set of signal processing algorithm are developed to capture the NPW arrival time and compare these measured values with the pre-established CTDL to accurately position leak point in the PWPN. The effectiveness of this method is verified via leak localization experiments on a field PWPN with an area of 12 × 12 km and 1478 branches. The proposed method can achieve leak positioning with errors less than 100 m throughout the entire pipeline network when only six pressure transmitters are effective.

Verification and evaluation methods for pipeline leak detection algorithms

Abstract As an important equipment in energy transportation and utilization, state detection is a key link to ensure the safety and environmental protection of the equipment. At present, there are many types of pipeline leakage detection algorithms, but there is less verification and evaluation of the actual performance and characteristics of the algorithm. Therefore, based on the evaluation index system, the entropy weight method (EWM), and the TOPSIS, we build a pipeline leakage inspection evaluation model of the measurement algorithm. In addition, the actual liquid pipeline transportation experiment platform is established. The negative pressure wave method is selected and combined with the CNN-LSTM algorithms to perform experiments. The results show that the algorithm used in this paper is better than the traditional negative pressure wave algorithm (NPW). The performance and calculation results can provide a reference for scientific research, engineering, teaching, etc.

AN NEGATIVE PRESSURE WAVE METHOD OPTIMIZATION FOR GAS PIPELINE LEAK LOCATION

The article is devoted to the optimization of the negative pressure wave method, designed to determine the location of leaks from a gas pipeline.The proposed negative pressure wave method provides a more accurate determination of the leak location, because a group of readable equally spaced sensors is used. To determine the location of a leak, the sign of the appearance of a minimum of a certain functional is used, which contains, as an integrand, the product of two exponential functions that cha racterize the weakening of a negative pressure wave propagating from the location of the leak to the position of the selected left and right sensors.Calculation formulas are given for calculating the optimal distance between a displaced pair of readable sensors, and the form of the optimal functional relationship between the distances from the place of leakage to the position of the sensors is established.

Cavitation and jetting from shock wave refocusing near convex liquid surfaces

We study the physical mechanisms behind the ejection of a liquid jet from a curved free surface, specifically a free-falling water drop. The jet is produced after a spherical shock wave emitted from a micro-explosion created by a focused laser pulse is refocused on the opposite side of its source. The analysis of high-speed videos of the liquid jet formation revealed that it originates from a larger, prolate cavitation bubble created by the strong tension produced after the reflection of the original wave on the air–liquid interface. The shock wave propagation and jet formation are modeled separately with finite volume simulations in OpenFOAM. Initially we study the pressure evolution inside the drop by comparing the numerical simulations with the distribution of bubbles nucleated after the passage of the negative pressure wave. The jet formation dynamics is explained by comparing the experiments with numerical results. The jet velocity is higher if the laser focus is closer to the drop surface.

EMDet: An entropy blending and multi-link parallel feature enhancement detection model for gas pipeline weak leakage detection

To improve the detection accuracy of gas pipeline leakage detection (PLD) especially when the leakage is weak, we propose a hybrid deep learning model, named EMDet in this paper, which incorporates two proposed algorithms called entropy blending (EB) and multi-link parallel feature enhancement (MPFE). Firstly, the EB algorithm is used to determine the optimal number of decomposition layer Lo and the optimal intrinsic mode function Io for variational mode decomposition (VMD), elevating the leakage-related information in Io. Then, three coarse-grained scales have been applied to extract effective and robust features, where the coarse-grained scales are calculated based on the sizes required by the MPFE algorithm. Moreover, the MPFE algorithm is proposed to enhance the representation of features, thereby improving the detection accuracy of PLD. After that, the performance of the proposed EMDet has been evaluated on the negative pressure wave (NPW) data collected from realistic urban environments. Compared with the state-of-the-art PLD models, the performance of EMDet not only reaches the total accuracy of 98.67%, the F1-score of 98.65%, and the fault detection rate of 98.68%, but also reduces the false alarm rate to 0.66% and the missing alarm rate to 1.32%. Finally, the robustness results demonstrate the superior performance and broad application prospects of EMDet for PLD.

Projeto ótimo de reservatórios hidropneumáticos em sistemas de bombeamento de água utilizando algoritmos genéticos multiobjetivos

ABSTRACT Protection devices can be used to protect a water transmission system in a hydraulic transient state, such as the Air Chamber, which can dampen both positive and negative pressure waves. This study proposes an optimal sizing of air chambers through genetic algorithms NSGA-II and NSGA-III combined with air valves in the pipeline. A real-life transmission system located in Brasilia-Brazil was simulated and analyzed. The results indicate the effectiveness of both algorithms in seeking optimal solutions and show the influence of guaranteeing safe minimum pressures in decision-making. We generate a Pareto front and highlight the best solutions.

Tracking and Localization Method of Pipeline Pigs Based on a Noise Reduction Autoencoder

In the pigging operation of an oil pipeline, the traditional pigging localization method can only achieve fixed-point detection and cannot track continuously. To ensure the normal operation of the pigging operation and track and locate the pig in a timely manner, a tracking and localization method of an oil pipeline pig based on a noise reduction autoencoder is proposed. First, using the advantages of U-Net (U-shaped Convolutional Neural Network) multi-scale feature extraction, combined with coding and residual-dense blocks, U-Net combined with Residual Dense Block U-shaped Network (RDBU) was proposed for noise reduction, and then real-time localization was calculated out based on the negative pressure wave localization formula of pigs. The experimental results show that, compared with the traditional method, the SNR of the RDBU is increased by 0.9dB and the root mean square error is reduced by 14.92%. The denoising algorithm in this paper can effectively eliminate the noise of the negative pressure wave signal of pigs.

Optimal Consensus of Attenuated Negative Pressure Waves for Pipeline Small Leakage Localization

Optimal Consensus of Attenuated Negative Pressure Waves for Pipeline Small Leakage Localization

Research on pipeline inspection gauges localization based on residual denoising autoencoder

To improve pipeline transportation efficiency, long-distance pipelines need to be cleaned regularly. Pipeline inspection gauges (PIGs) are widely used in pigging operations. The traditional PIG localization method generally has a large error and cannot achieve continuous tracking. To solve the problem of PIG real-time tracking and localization, this paper proposes a method of PIG localization for oil pipelines based on a denoising autoencoder(DAE). The attention deconvolution residual block (ADR) is introduced in the decoder part of the DAE, so that this model can learn and use global information to selectively emphasize key features, suppress useless features, and improve the noise removal performance of the model. After denoising, the negative pressure wave(NPW) signal is normalized, the time delay is extracted, and the PIG is located using the NPW localization formula. Experiments show that this method can effectively achieve real-time PIG localization. Compared with the EMD and DAE positioning methods, the relative positioning accuracy is increased by 3.5 times and 8.4 times, respectively.

Influences of Sediment Particles on Air Vessel Water Hammer Protection Effect in the Long-Distance Water Supply Systems

Abstract Long-distance water supply systems are important measures to improve the water resources distribution, and the water hammer protection devices such as air vessels are usually added in the project to ensure the safety and stable operation. However, the sediment particles are always ignored in the design. Hence, a numerical model and program were established for sediment laden water hammer based on the method of characteristics (MOC). Using the proposed model, the water hammer protection influences of sediment particles parameters are simulated for the same pipeline system of a water supply project. The result shows that the resistance loss of sediment-laden water in pipelines is larger than that of water, and the initial head of pump needed to be increased to ensure the water levels of downstream reservoirs are consistent. After power failure and pump stopping, the negative pressure wave of sediment-laden water is 2.97 m higher than that of water, and the theoretical minimum internal pressure along pipelines is 7.8 m lower. With the same air vessel protection, the lowest minimum internal pressure heads along pipelines decrease with the increase of quantities of sediment, while the results show no obvious influence by changes of median particle diameters. The lowest absolute pressure of pipeline could reach −0.69 m under the condition of 50 kg/m3 quantity of sediment and 0.05 mm median particle diameter. The relevant research results are of great significance sediment-laden water hammer numerical simulation and water hammer protection design.

Pipeline Leak Detection System

This article deals with a development of a pipeline leak detection system for monitoring hydrocarbon pipelines in real time. This system is based on the integration of methods of negative pressure waves of propagation and mass and momentum balance calculation. The system is designed to receive real-time data from multiple remote terminals which operate in the field and its processing in a monitoring center. For validation of the system, a liquefied gas pipeline of 20” diameter and 60 km in length was used. The validation of the system was done by comparing the events detected and located by the developed system and the results of verification of real leak locations. Some inspection results using this system are presented.