Detection of small leakage from long transportation pipeline with complex noise

In the long distance pipeline remote monitoring system, small leak detection becomes an important issue. Weak singularities in small leak signals are usually difficult to detect precisely under complicated noise background, which may cause false alarm or miss alarm. The advantage of applying the harmonic wavelet method is explored in this paper. Pipeline small leak sensitive characteristics are recognized and the negative pressure wave inflexions are extracted by harmonic wavelet analysis, expressed in terms of harmonic wavelet time-frequency mesh map, time-frequency contour map, and time-frequency profile plot. This paper also presents a comparative study of both Daubechies wavelet and harmonic wavelet analysis when applied to pipeline small leak detection under complicated background noises. Results of simulating test and field experiment show that it is possible to distinguish weak non-stationarities from complicated noises by harmonic wavelet analysis in pipeline small leak detection system. The comparison clearly illustrates that harmonic wavelet based pipeline small leakage detection method is significantly more accurate than other wavelets analysis such as Daubechies wavelet. This work provides a reliable and safe guarantee for oil and gas long distance transportation, reducing petroleum product losses and protecting surrounding environment.     

基于广义概念的城市燃气管道泄漏精确定位

为了准确地检测城市燃气管道泄漏,提出了一种基于广义概念的管道泄漏检测定位方法。声发射技术对于管道泄漏的检测、定位是一个极好的工具,但由于泄漏源的传播容易受到周围背景噪声以及复杂工况的影响,其定位误差较大。基于时延估计的互相关信号处理方法被广泛用于管道泄漏检测定位,但由于泄漏应力波传播通道的动态特性,使得源信号在传播过程中会产生波形变化,给互相关函数峰值位置的确定带来困难。由此引入广义相关分析方法,通过对信号进行前置滤波,在一定程度上减少了传播通道动态特性因素对泄漏点定位的不利影响,得到了更为准确的时延估值。在此基础上,通过模拟实验,编写Matlab神经网络代码,构造GRNN模型,进一步预测定位。结果表明,GRNN预测的声发射检测值、互相关定位值以及广义相关定位值,相比之前定位精度分别得到提高,其中基于广义相关的延时估计方法定位最为精确,将该方法用于工程实际中,可以更加精确地定位出泄漏点。     

Leak detection for long transportation pipeline using a state coupling analysis of pump units

Leak detection for long transportation pipeline with a large economic and environmental impact has been an area of intensive research for more than five decades. This paper presents a novel pipeline leak detection scheme based on a state coupling analysis (SCA). Instead of monitoring the pipeline and pump units separately, SCA introduces a new detecting method of analyzing data in a coupling running condition. A novel capture method for abnormal pressure based on logical reasoning algorithm is proposed. Hamming approach degree arithmetic is applied to calculate the matching mode identifying the state of units. SCA is used to reduce the rate of false alarm and detect the leak with a high detecting sensitivity for long transportation pipeline. An on-line software system based on SCA is utilized to achieve superior accuracy and implementation. An industrial case study for coupling system pipeline leak detection is used as an example to validate the effectiveness of the proposed method.     

Integrated-signal-based leak location method for liquid pipelines

Leaks in pipelines can cause major incidents resulting in both human injuries and financial losses. Among the considerable leak detection and location methods, the Negative Pressure Wave (NPW) based method has been widely used in locating leaks in liquid pipelines. The NPW based method only monitors the pressure changes at two ends of a pipeline. But the pressure is apt to be fixed by the end equipment and the change of it induced by a small or slow leakage is too small to be detected, which limit the application of the NPW based method in these situations. This paper presents a novel leak location method based on integrated signal, which is a combination of the pressure and flow rate signals. The representation of the integrated signal is derived from the transient analysis of the leakage. For the change of the integrated signal induced by a leakage is larger than the pressure change and it is also unaffected by the end equipment, the proposed method can be used to detect and locate small or slow leakage in a pipeline and can also be used in pipelines which end pressures are fixed by some kinds of equipment. The validation of the proposed method also confirms its advantages.     

Numerical and experimental study on the generation and propagation of negative wave in high-pressure gas pipeline leakage

Negative-wave-based leakage detection and localization technology has been widely used in the pipeline system to diminish leak loss and enhance environmental protection from hazardous leak events. However, the fluid mechanics behind the negative wave method has yet been disclosed. The objective of this paper is to investigate the generation and propagation of negative wave in high-pressure pipeline leakage. A three-dimensional computational fluid dynamic (CFD) study on the negative wave was carried out with large eddy simulation (LES) method. Experimentally validated simulation presented the transient wave generation at the leak onset and the comprehensive wave evolution afterwards. Negative wave was proven to be a kind of rarefaction acoustic waves induced by transient mass loss at the onset of leakage. Diffusion due to the density difference at wave fronts drives the negative wave propagation. Propagation of negative wave can be categorized into three states – semi-spherical wave, wave superposition and plane wave, based on different wave forms. The wave characteristics at different states were elucidated and the attenuation effects were discussed respectively. Finally, a non-dimensional correlation was proposed to predict the negative wave amplitude based on pipeline pressure and leak diameter.     

A dual-sensor-based method to recognize pipeline leakage and interference signals

During the detection of pipeline leakages, false alarms of leak detection could be markedly reduced if the interference signals resulting from pressure regulating, pump regulating or valve movements could be accurately distinguished. A digital recognition method for interference signals and leakage signals based on a dual-sensor system is proposed in this paper. It is demonstrated that the direction of the signal can be recognized by a cross-correlation calculation between two signals from the dual-sensor, one of which undergoes forward linear interpolation and backward linear interpolation. Based on this theory, the interference signal and the leak signal can be discriminated exactly, and the distance between the two sensors in the dual-sensor system can be considerably reduced without needing to increase the sampling frequency. The monotonicity of the cross-correlation function is demonstrated, and a fast discrimination algorithm based on a binary extreme search method, which decreases the computational load and maintains global optimization, is also proposed. A pre-processing method of the actual signal is proposed to decrease the identity requirement for the two sensors in a dual-sensor system. In the experiment based on artificial signals, the proposed discrimination algorithm could achieve accurate recognition of the abnormal signal, and as such, the theory and application of pipeline leak detection based on dual-sensor systems are extended.     

Fault diagnosis of pipeline and pump unit systems using status coupling analysis

Earlier studies on fault diagnosis of the pipeline and pump unit systems (PPU) relied mainly on independent equipment analyses, which usually lead to false alarms because of the loss of information fusion. The aim of this study is to utilize the status coupling relationship to improve fault detection sensitivity and reduce false alarm rate. A real-time status identification of related equipment step is added between capturing abnormal signals and listing out diagnosis results. For example, when the pipeline pressure fluctuation is found abnormal, a status analysis of pump units is performed immediately, if the pump units are proven to be operational normally, then the pipeline leak alarm is acknowledged valid. The logical reasoning algorithm is used to capture abnormal conditions of pipeline pressures. The pump unit faults are captured by combining information from multiple sources. Field applications show that the proposed method significantly improves the PPU fault detection capability on fault detection sensitive and accuracy.     

Image rotation method for identification of NPW signals in the localization of pipeline leakage

Gas and oil are mainly transported through long-distance pipelines on land. Pipeline leaks lead to severe hazards to the environment and economy and even imperil human lives. Negative pressure wave (NPW)-based methods are fast and effective for leak monitoring and localization. The key problem for an NPW-based method is to determine the NPW and its arrival time, which is characterized by the knee point in the time domain signal. In this paper, an image rotation method is proposed based on the shape characteristic of the time domain signal induced by an NPW. Through image rotation, the knee point turns into the highest point, which is easy to detect. To verify the performance of the proposed method, leakage experiments were conducted on liquid and gas pipeline models. Previously developed FBG pipe fixture sensors were used to detect an NPW. These sensors were equidistantly installed on the pipeline, forming a sensor array. Based on the sensing array, a novel leak localization algorithm was used to compute the leakage position. The experimental results indicated that the image rotation method has good performance for identifying an NPW, even though many noise- and pressure-induced fluctuations exist in the signals. This method enables automated real-time monitoring and has potential for practical application.     

Leak location of pipelines based on characteristic entropy

The leakage of oil/gas pipelines is one of the major factors to influence the safe operation of pipelines. So it is significant to detect and locate the exact pipeline leakage. A novel leak location method based on characteristic entropy is proposed to extract the input feature vectors. In this approach, the combination of wavelet packet and information entropy is called “wavelet packet characteristic entropy” (WP-CE). The combination of empirical mode decomposition and information entropy is called “empirical mode decomposition characteristic entropy” (EMD-CE). Both pressure signal and flow signal of low noise and high noise of pipeline leakage are decomposed to extract the characteristic entropy. The location of pipeline leak is determined by the combination of the characteristic entropy as the input vector and particle swarm optimization and support vector machine method (PSO-SVM). The results of proposed leak location method are compared with those of PSO-SVM based on physical parameters. Under the condition of high noise, the results of proposed leak location method are better than those of PSO-SVM based on physical parameters.     

Integrated leakage detection and localization model for gas pipelines based on the acoustic wave method

With the development of natural gas transportation systems, major accidents can result from internal gas leaks in pipelines that transport high-pressure gases. Leaks in pipelines that carry natural gas result in enormous financial loss to the industry and affect public health. Hence, leak detection and localization is a major concern for researchers studying pipeline systems. To ensure the safety and improve the efficiency of pipeline emergency repair, a high-pressure and long-distance circular pipe leakage simulation platform is designed and established by similarity analysis with a field transmission pipeline, and an integrated leakage detection and localization model for gas pipelines is proposed. Given that the spread velocity of acoustic waves in pipelines is related to the properties of the medium, such as pressure, density, specific heat, and so on, this paper proposes a modified acoustic velocity and location formula. An improved wavelet double-threshold de-noising optimization method is also proposed to address the original acoustic wave signal collected by the test platform. Finally, the least squares support vector machine (LS-SVM) method is applied to determine the leakage degree and operation condition. Experimental results show that the integrated model can enhance the accuracy and precision of pipeline leakage detection and localization.     

埋地聚乙烯燃气管道基于失效模式的全面检验关键技术及工程应用

PE管道固有较高的性价比,广泛应用在能源、燃气等工程中,但因其焊接接头质量难以检测、位置探查难度大,使PE管道的安全状况难以控制,导致泄漏等事故。基于PE管材的失效模式,参照钢质管道的检验经验,中国特种设备检测研究院研究确定了PE管道基于失效模式的全面检验关键技术,并围绕关键技术开展了多项研究,取得了一系列科研成果,如：PE管焊接质量超声相控阵动态聚焦和B扫查成像检测、探地雷达、泄漏在线检测、老化及安全评价、风险评估方法等。这些系列成果,在新疆、青海、内蒙古、宁夏等城市PE燃气管网中得到了有效应用,检验出多项安全隐患,为城市燃气的安全提供了保障,为今后全面开展PE管线检验,提供了成功经验。     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

城市管道天然气在土壤中泄漏扩散实验研究

天然气在土壤中扩散行为的实验研究对埋地管道泄漏点的科学定位及泄漏事故的预防具有重要意义.采用全尺度气体泄漏实验系统,模拟真实埋地管道泄漏场景,对泄漏后的天然气在土壤中的扩散对流过程进行实验研究.基于自行研制的气体检测与数据采集系统和GasClam地下气体在线监测仪,分析天然气在土壤中的对流扩散规律.结果表明:埋地管道泄漏后天然气在土壤中的对流扩散过程可以分为4个阶段:孕育阶段、陡然增长阶段、缓慢增长阶段和稳定阶段,其浓度随泄漏时间的变化过程符合S型曲线特征.天然气扩散至检测点所需时间与距泄漏口距离呈现近似的幂指数关系.当检测点位于泄漏口附近区域时,泄漏压力起主导作用.当检测点位于远离泄漏口区域时,泄漏量起主导作用.     

Probabilistic multiple model neural network based leak detection system: Experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.     

Acoustic detection technology for gas pipeline leakage

Gas leakage from pipeline leads to significant environmental damages and industrial hazards, so small leakage detection for gas pipeline is essential to avoid these serious leakages. However, because of the high frequency component of leakage signal attenuates quickly, traditional detection method which inspects pressure or vibration signal has problem to get effective information from leakage signal. So, a novel detection method based on acoustic wave is proposed. This paper, firstly, researches on the phonation principle of pipeline leakage and the characteristic of sound source, and simulates the leakage acoustic field on the basis of aero acoustics. Secondly, using Wavelet Packet Transform method and Fuzzy Support Vector Machine pattern classification, the laboratory testing for identifying acoustic signal of gas pipeline leakage is presented. Finally, the field application demonstrates that the detection system could identify small gas leakage effectively and avoids false-alarms which caused by running conditions with a good prospect.     

基于VPL的输油管道实时泄漏检测系统

针对现有管道泄漏检测技术在管道微小泄漏检测和油品泄漏损失计算方面存在的不足,基于流体动力学和容量守恒原理,开发基于VPL（Visual Pipeline）的输油管道实时泄漏检测系统。建立管道模拟平台,通过组态编辑器、图像界面、管道工作室和SCADA 接口,开展输油管道实时泄漏检测、定位与分析,实现管道实时泄漏检测、报警,以及泄漏量的定量计算。现场测试结果显示,所开发的输油管道泄漏检测系统最小泄漏检出率为0.7%,泄漏点定位精度为96.96%,泄漏量计算准确率为94.42%。研究结果表明:基于VPL的输油管道实时泄漏检测系统漏报、误报率低,检测定位精度较高,尤其对于微小泄漏优势明显;同时,该系统能够实时定量计算油品泄漏损失,可以用于输油管道泄漏检测与应急辅助决策。     

基于模糊相似优先比的供水管网渗漏同步诊断*

为加强城市供水管网渗漏诊断能力,采用基于模糊相似优先比的漏损判别方法实现供水管网漏损定位及漏损程度的同步诊断。通过MATLAB软件调用最新版EPANET V2.2建立供水管网模型,在管段中间加入扩散器模拟单次渗漏事件,通过更改扩散器系数实现渗漏量的控制;基于压力驱动水力分析得到各节点压力变化,遍历模拟各管段漏损后,通过建立节点压力灵敏度矩阵,采用K均值聚类法进行监测点布置;在此基础上,在易渗漏管段模拟产生不同渗漏级别的渗漏事件,以监测点压力变化值构建源范例库,在熵权法的基础上,采用模糊相似优先比方法同步诊断渗漏位置及渗漏程度。以某一实际管网为例,模拟产生50例历史渗漏事件,采用模糊相似优先比同步诊断新渗漏事件的渗漏位置及渗漏程度,并对比3种权重方法。结果表明:模糊相似优先比法可有效地实现渗漏定位与渗漏程度的同步诊断。     

ARX modeling approach to leak detection and diagnosis

This work presents a time series strategy for detection, location and quantification of leaks in large pipeline systems. The technology has two active components, which operate sequentially: the Detector and the Localizer. The Detector continuously screens real-time data, searching for any anomalies such as leaks, which are detected (or not) depending on their size and position. The Detector is based on auto-regressive multi-input/multi-output (MIMO) ARX predictors with one input filter. Subsequent to successful leak detection, the Localizer is launched to diagnose the leak via estimation of its parameters – diameter and location – using recorded data on a Search Time Window that includes information in the neighborhood of the instant of detection. The Localizer is also an ARX predictor, but with two input processors, the first is a filter for dynamic plant inputs and the second filter processes “parameter signals” of active leaks. The Localizer is developed beforehand via model identification with plant data under the action of known, artificially simulated, leaks. It is, therefore, able to recognize an active pattern of leak parameters, by maximizing the adherence of its predictions to data in the Search Time Window. The proposed detection and location methods were successfully tested in simulated leak scenarios for an industrial naphtha pipeline.     

A survey on gas leak detection and localization techniques

Gas leaks can cause major incidents resulting in both human injuries and financial losses. To avoid such situations, a considerable amount of effort has been devoted to the development of reliable techniques for detecting gas leakage. As knowing about the existence of a leak is not always enough to launch a corrective action, some of the leak detection techniques were designed to allow the possibility of locating the leak. The main purpose of this paper is to identify the state-of-the-art in leak detection and localization methods. Additionally we evaluate the capabilities of these techniques in order to identify the advantages and disadvantages of using each leak detection solution.     

Numerical investigation of surface conduit parallel gas pipeline explosive based on the TNT equivalent weight method

With the rapid development of petroleum industry, the transport pipelines of oil and gas are increasingly constructed to minimize land use conflicts. Therefore, the parallel pipelines are unavoidable in order to save land resource, reduce the pipeline construction and maintenance costs. The economy and security of pipeline laying and running is the primary problem considered in pipeline construction, which the parallel spacing plays a decisive role to. The leakage of natural gas is very serious and dangerous due to its flammable and combustible. The explosive of leak gas causes impact failure to parallel pipeline. Specific to the surface conduit parallel gas pipeline, numerical simulation of leak natural gas explosive was carried out based on TNT equivalent weight method. Explosive damage degree of pipeline decreased with the pipeline distance increasing. Consulting with the pipeline ovalization strain design criteria and the combustion effect, the safety parallel natural gas pipeline space maybe at least 4 m to ensure the surface conduit parallel pipeline safely and steadily operation.