Pipeline Leak Location Research Articles

Sparse representation of acoustic emission signals and its application in pipeline leak location

The acoustic detection of pipeline leaks is strongly influenced by the associated interference and noise. In this paper, acoustic emission signals are analyzed using a sparse representation method and the main components associated with the leakage are extracted. Dictionary learning is performed using training samples composed of the leakage signals and noise signals. The measured signal is sparsely decomposed on the composite dictionary, allowing the main leakage components to be estimated. The effects of dictionary dimensionality, redundancy, sparsity constraints, and other parameters on the performance of the sparse representation algorithm are investigated. Finally, the leak location in the pipeline is determined through cross-correlation analysis of the reconstructed acoustic signals. Experimental results show that the proposed sparse representation method effectively improves the signal-to-noise ratio of the acoustic emission signals, and correspondingly improves the accuracy and reliability of pipeline leak location compared with traditional localization methods.

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.

Prediction of the probabilistic water leak location in underground pipelines using Monte Carlo simulation

Abstract The water loss rates in Brazil are still very concerning and cause huge financial, social, and environmental damages. Although great advances have been made in acoustic leak detection methods, some of them are intrusive or at least demand convenient access points to the pipe's surface. Furthermore, some methods are expensive and require a highly experienced and qualified operator. Thus, the goal of this paper is to establish a benchmark using a simplistic analytical model for the ground surface analysis for leaks location, simplifying the search process carried out in water networks, and requiring minimal system interference. For leak location prediction, the proposed method considered two seismic wave paths – the compressional body waves and the Rayleigh superficial waves. The traveltime curves of the compressional waves are calculated as a function of the surface wave's experimental information. Monte Carlo Simulations were carried out to test each model's precision considering uncertainties related to the input parameters of the problem. At last, through a parametric study, the two seismic events were combined to obtain better accuracy in predicting the leakage epicenter location. In the results, the maximum absolute error found was 15 cm, and the minimum improvement obtained with the parametric study was 27.4%.

Leak Localization Method of Jet Fuel Pipeline Based on Second-Generation Wavelet Transform and Short-Time Energy Time Delay Estimation

There is a large error in the acoustic propagation speed of jet fuel pipeline based on cross correlation analysis, which leads to poor positioning accuracy of the leak location. Therefore, a new leak localization method of jet fuel pipeline based on second-generation wavelet (SGW) transform and short-time energy time delay estimation is proposed. Using SGW transform to extract the leak acoustic signal to reduce the interference of external noise in this method, the short-time energy function is estimated to calculate the sudden change time range of leak acoustic signal in the time window, so as to find the sudden change time range containing the sudden change point information of leak acoustic signal. According to the threshold of short-time energy function, the accurate sudden change time of leak acoustic signal is determined. When the accurate sudden change times of three acoustic sensors are obtained, the leak position of pipeline is calculated by a leak localization formula. The proposed method does not need to estimate the acoustic propagation speed, and it can obtain more accurate leak localization accuracy of pipeline leak. The field experimental pipeline results show that the average error rate of jet fuel pipeline leak localization is reduced from 1.25% of the cross correlation analysis method to 0.1% of the proposed method.

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.

Research on Leak Location Method of Water Supply Pipeline Based on MVMD

At present, the leakage rate of the water distribution network in China is still high, and the waste of water resources caused by water distribution network leakage is quite serious every year. Therefore, the location of pipeline leakage is of great significance for saving water resources and reducing economic losses. Acoustic emission technology is the most widely used pipeline leak location technology. The traditional non-stationary random signal de-noising method mainly relies on the estimation of noise parameters, ignoring periodic noise and components unrelated to pipeline leakage. Aiming at the above problems, this paper proposes a leak location method for water supply pipelines based on a multivariate variational mode decomposition algorithm. This method combines the two parameters of the energy loss coefficient and the correlation coefficient between adjacent modes, and adaptively determines the decomposition mode number K according to the characteristics of the signal itself. According to the correlation coefficient, the effective component is selected to reconstruct the signal and the cross-correlation time delay is estimated to determine the location of the pipeline leakage point. The experimental results show that this method has higher accuracy than the cross-correlation method based on VMD and the cross-correlation method based on EMD, and the average relative positioning error is less than 2.2%.

Estimating the coordinate error for leak location in oil pipelines

This paper discusses the method of hydraulic location for leak detection. A statistical criterion for leakage incident detection has been developed. A series of simulation experiments conducted has confirmed that the developed criteria are adequate. An algorithm has been developed to evaluate the sensitivity of a leak detection algorithm based on the availability of pressure instruments at the process section.

A stochastic material balance model for leak location in oil pipelines

The material balance method, being the basic algorithm of leak detection systems (LDS), is discussed. A criterion for making a decision concerning a leak is substantiated; the issue of determining the sensitivity limit of the material balance algorithm is discussed.

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%.

Extracting acoustic leakage signals in buried pipes

This paper develops a method for separation and extraction of pipeline leakage signals. The independent component analysis is applied to separate acoustic signals, which is then coupled with the image similarity distance matching fusion algorithm for the extraction of the signals due to leakage. Acoustic signals generated by real pipeline leakage and common interference noise are collected respectively in order to form a multi-channel matrix with random mixing of leakage signal and uncorrected noise signals. It is demonstrated that the suspected leakage signals extracted after re-sequencing match well with the original leakage signal in terms of coherence and peak cross-correlation. They are further verified based on the cumulative energy distribution and the energy ratio at low and high frequencies. By effective separation of leak signals from the uncorrected background noise signals, the method presented in this paper provides the basis for the improvement of pipeline leak localization.

Noise Reduction Based on CEEMDAN-ICA and Cross-Spectral Analysis for Leak Location in Water-Supply Pipelines

Due to the leakage vibration signal of the water-supply pipeline is easily interfered with by background noise, which leads to a significant leakage location error of time delay estimation. The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and independent component analysis (ICA) combined noise reduction method based on cross-spectral analysis is proposed and applied to leak location of water supply pipelines. Firstly, determine the frequency band range of the source leakage signal by cross-spectral analysis of the leakage vibration signal. At the same time, the leakage vibration signal is decomposed into a finite number of intrinsic mode functions (IMFs) using CEEMDAN. Then, the IMF components are filtered according to the effective amplitude ratio criterion, and the filtered components are reconstructed into a virtual noise channel. Finally, the leakage vibration signal and virtual noise channel are unmixed using FastICA to obtain the best estimate of the source leakage signal, which is used to estimate time delay using cross-correlation for determining the leak location. Simulation and experimental results show that the proposed method effectively improves the signal-to-noise ratio (SNR) and time delay estimation accuracy, and reduces leak location error. Compared with cross-correlation, CEEMDAN-ICA based on correlation coefficients, and CEEMDAN based on cross-spectral analysis, the average relative positioning error of the proposed method is respectively reduced by 11.07%, 9.7%, and 1.8%. In addition, the superiority of the proposed method compared with other state-of-the-art noise reduction methods is verified by comparative experiments.

TR Self-Adaptive Cancellation Based Pipeline Leakage Localization Method Using Piezoceramic Transducers.

In this paper, we propose a novel time reversal-based localization method for pipeline leakage. In the proposed method, a so-called TR self-adaptive cancellation is developed to improve the leak localization resolution. First of all, the proposed approach time reverses and back-propagates the captured signals. Secondly, the time reversed signals with the various coefficients are superposed. Due to the synchronous temporal and spatial focusing characteristic of time reversal, those time reversed signals will cancel each other out. Finally, the leakage location is distinguished by observing the energy distribution of the superposed signal. In this investigation, the proposed method was employed to monitor a 58 m PVC pipeline. Three manually controllable valves were utilized to simulate the leakages. Six piezoceramic sensors equipped on the pipeline, recorded the NWP signals generated by the three valves. The experimental results show that the leak positions can accurately revealed by using the proposed approach. Furthermore, the resolution of the proposed approach can be ten times that of the conventional TR localization method.

A novel pipeline leak detection and localization method based on the FBG pipe-fixture sensor array and compressed sensing theory

Low localization accuracy and instability have always been two primary problems for the pipeline leak detection and localization method based on the negative pressure wave (NPW) technique. In this paper, based on compressed sensing (CS) theory, a novel pipeline leak detection and localization method is proposed to replace the solutions of the arrival time difference of NPW knee points. In addition, based on the presented method, the localization accuracy can be improved without increasing the number of sensors. To validate the localization accuracy and stability of the presented method, a pipeline leak simulation test under flow conditions is conducted on a steel pipe leak test platform. The fiber Bragg grating (FBG) pipe-fixture sensor array is developed and applied to detect pipeline leakage and measure the pressure variations in the NPW signals, which provides the data basis for pipeline leak localization based on CS theory. A concept of the relative localization coefficient bCS is proposed, and the test results indicate that when bCS is 0.5, all localization errors of different leakage points with different leakage rates are 2 m.

Estimation of possibilities of calculations based on simplified models of the leak location in gas pipelines

For gas transportation through pipes in normal and emergency modes, a comparison of calculations based on mathematical models of various degrees of generality is presented. A mathematical model of a non-isothermal steady flow of a mixture of gases and its simplified versions are studied. For simplified options, simple analytical dependencies were obtained for calculating flow characteristics and calculating the location of an emergency gas leak. Examples of calculations of pressure distributions, temperature and leakage coordinates in gas pipelines of medium pressures according to the general and simplified models are provided. The examples cover the parameter change area of practical interest. The conditions for the admissibility of using simplified models for calculating the coordinates of a leak of medium intensity and different locations are determined. Keywords: gas pipelines, adequacy of the model, simplifications, calculation of the place of emergency leakage, compressibility factor.

Plastic Pipeline Leak Localization Based on Wavelet Packet Decomposition and Higher Order Cumulants

This paper presents a plastic pipeline leak localization method based on wavelet packet decomposition and higher order cumulants. The hydrophone sensors are used to capture the acoustic signals generated by the water leakage in the plastic pipe. The feature frequency band containing the most leak information is subsequently extracted by performing wavelet packet decomposition on the signals. The most suitable wavelet packet basis function for leak signals is obtained by comparing the effects of varieties of wavelet packet basis functions. Furthermore, the higher order cumulant method is used to estimate the time delay between the two sensors signals, from which the leak hole can be located. The simulation and experimental results show that, compared with the basic cross-correlation method (BCC) and the generalized cross-correlation method (GCC), the higher order cumulant method has higher leak localization accuracy. The relative error of the third-order cumulant method is 2.99% in experiment 1 and 7.58% in experiment 2, while the relative localization error of the fourth-order cumulant method is 1.96% in experiment 1 and 1.23% in experiment 2.

Adaptive Signal Enhancement Based on Improved VMD-SVD for Leak Location in Water-Supply Pipeline

The nonlinear non-stationary noise in surroundings leads to low signal to noise ratio (SNR) of leakage signal collected by acceleration sensors which generate larger leak location errors in water-supply pipelines. An adaptive signal enhancement based on genetic algorithm optimized variational mode decomposition (VMD) and singular value decomposition (SVD) is proposed for leak location in water-supply pipelines. Firstly, the fitness function was established as the optimization objective by minimum envelopment entropy of VMD modal component. Then the genetic algorithm was used for adaptive optimization of VMD parameters [ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> , K]. Secondly, the leakage signal is decomposed by adaptive-optimizing VMD into several intrinsic mode functions which can be selected by kurtosis analysis to reconstruct high-SNR (Signal to Noise Ratio) signal. Finally, Hankel matrix of the reconstructed signal is decomposed using SVD to further improve SNR. Simulation and experimental results show that the proposed signal enhancement is effective for reducing leak location errors. The SNR of the enhanced signal is improved by 94.27% compared with the initial signal and the average relative leak location error is reduced by 6.67 times using enhanced signal, which demonstrates feasibility and effectiveness of the proposed signal enhancement method.

Negative pressure wave denoising based on VMD and its application in pipeline leak location

Negative pressure wave denoising based on VMD and its application in pipeline leak location

Study on the influence of elbow with different curvature radii on pipeline leak location

Experimental and numerical methods are used to locate the pipeline leakage in the present work. The weak compressibility of the fluid is taken into account when simulating the propagation of negative pressure wave (NPW) in the pipeline. The NPW attenuation coefficient is used to describe the influences of curvature radius on location accuracy. The results indicate that when the curvature radius is small, the location accuracy of pipeline leakage is low. When the radius of curvature increases or the inlet pressure increases, the accuracy of pipeline leak location is improved. Besides, with the change of inlet pressure, pressure, and velocity distributions in the elbow with different curvature radii are investigated. When the curvature radius of the elbow is three to four times of pipe diameter, the measurement accuracy of leakage location is the best. When the inlet pressure of the pipeline is 0.7 MPa, the sensitivity of the pipeline detection is the highest. The cavitation corrosion at the elbow is the most obvious. Therefore, the elbow is the area where pipeline leakage occurs most frequently.

Multi‐Sensor Fusion for Transient‐Based Pipeline Leak Localization in the Dempster‐Shafer Evidence Framework

AbstractDetecting a small leak in a water‐supply pipe with a wave scattering power of the order of noise or smaller is a challenging problem because its signature in a measured signal is weak. Experimental data show that multiple sensors enhance the evidence about a leak in a transient test and, thus, increase the possibility of successful leak detection in noisy environments. Therefore, a leakage localization scheme is proposed, which fuses multi‐sensor measurements in the Dempster‐Shafer evidence framework. The signature of a leak in each measurement is extracted and translated into a piece of evidence regarding its presence and location. Then, the pieces of evidence from different sensors are fused using the Dempster's rule of combination to form a unified leak location estimation. The proposed method is model‐free and is thus insensitive to imprecise knowledge of pipe system. The gain of the multi‐sensor fusion mechanism on the leakage localization accuracy is demonstrated via both numerical and experimental data.

Case study of leak detection based on Gaussian function in experimental viscoelastic water pipeline

Abstract Leakage in transmission pipelines and water distribution networks causes water and energy loss and reduces water quality. The accuracy of leakage detection using transient-based methods depends on several factors. This study investigated the sensitivity of location and size of leaks in simple polyethylene transmission pipelines to dynamic parameters, flow regime, sample size, spatial-step increment, and leak size and location. For this purpose, a hydraulic transient solver was first developed to take into account the dynamic effects of unsteady friction, viscoelasticity of the pipe wall, and the leak. The leakage was assumed to function with a quasi-normal distribution around its real location to reduce problem dimensionality and unnecessary computations. This approach was evaluated based on experimental transient data in which leaks were simulated in different sizes and locations. Results revealed that the hydraulic transient model that includes only viscoelasticity effects could pinpoint leakage characteristics. The sample size evaluation indicated that half and a single period of the pressure signal are sufficient to determine the leakage location and size in simple viscoelastic transmission pipelines, respectively. The optimal ratio of the spatial step to pipe length (Δx/L) was 0.025.