A new leak location method based on leakage acoustic waves for oil and gas pipelines

In order to study a new leak detection and location method for oil and natural gas pipelines based on acoustic waves, the propagation model is established and modified. Firstly, the propagation law in theory is obtained by analyzing the damping impact factors which cause the attenuation. Then, the dominant-energy frequency bands of leakage acoustic waves are obtained through experiments by wavelet transform analysis. Thirdly, the actual propagation model is modified by the correction factor based on the dominant-energy frequency bands. Then a new leak detection and location method is proposed based on the propagation law which is validated by the experiments for oil pipelines. Finally, the conclusions and the method are applied to the gas pipelines in experiments. The results indicate: the modified propagation model can be established by the experimental method; the new leak location method is effective and can be applied to both oil and gas pipelines and it has advantages over the traditional location method based on the velocity and the time difference. Conclusions can be drawn that the new leak detection and location method can effectively and accurately detect and locate the leakages in oil and natural gas pipelines.     

Study on leak-acoustics generation mechanism for natural gas pipelines

In order to figure out the principles of acoustic leak detection for natural gas pipelines, a study on the leak-acoustics generation mechanism is carried out. The aero-acoustics generation mechanism is analyzed and when leakage occurs the wave equations of sonic sources are developed. The leak-acoustics generated by the quadrupole and dipole sonic sources are then simulated to obtain the laws of the acoustic characteristics. The simulation data are compared with the experimental data to verify the simulation accuracy under variable operating conditions. The results show that the quadrupoles and the dipoles generated by turbulent fluctuations cause leak-acoustics; the main component of pressure perturbations acquired by the dynamic pressure sensor is acoustic perturbations; both the simulation method and the experimental method can be applied to study the leak-acoustics generation mechanism of natural gas pipelines.     

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.     

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.     

页岩水化特征及其井壁稳定分析

为深入研究页岩的水化特征及水化对井壁稳定的影响,以鄂尔多斯盆地石盒子组页岩为研究对象,开展了钻井液浸泡前后岩样的超声波透射实验、层理面直剪实验、三轴压缩实验,探讨了页岩水化的声学性质变化与岩石力学特征,分析了页岩水化对坍塌压力的影响。结果表明:弹性模量、泊松比等参数的变化难以准确评价页岩的水化特征,声波时差、衰减系数、时域曲线、频域曲线等超声波信号可作为研究页岩水化特征的有效手段;页岩水化直接导致其岩石力学性质发生变化,水化是坍塌压力上升的主要原因之一,对井壁稳定造成潜在的威胁;井壁稳定设计时应充分认识页岩的水化特征,避免井壁坍塌,确保钻井施工安全进行。     

Carbon dioxide pipelines: A statistical analysis of historical accidents

Carbon dioxide pipeline is an essential carrier in carbon capture, utilization, and storage (CCUS). Statistically revealing the accident rate and risk of carbon dioxide pipelines is conducive to integrity management. Based on 112 accident records collected from Pipeline & Hazardous Materials Safety Administration, this work analyzes the frequency, rate, and risk of accidents. In addition, the impact of relevant factors on risk is further discussed. Some primary conclusions are as follows: (1) For carbon dioxide pipelines, the leak is the leading form of accident. Most carbon emissions are generated in the form of leakage, but economic losses are mainly generated in other forms. (2) The pipelines that have been in service for 0–10 years have the highest frequency of accidents and the highest proportion of carbon emissions, but the pipelines that have been in service for 11–20 years have caused the most economic losses. (3) Among the accident causes, the number of accidents caused by equipment failure is the highest, while the economic loss caused by natural force damage is the highest, and the carbon emission caused by material failure is the highest.     

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。     

基于梅尔倒谱系数的矿山复杂微震信号自动识别分类方法

为了实现矿山复杂微震信号的自动高效识别与分类,保证后续微震分析的时效性和准确性,运用梅尔倒谱系数法,将原始的4种微震信号(岩体破裂、爆破振动、电磁干扰和钻机凿岩)转化为梅尔标度上的非线性频谱,再转换到倒谱域上,结合其在时域上的差分得到1组24维的特征参数向量,利用这些特征参数向量训练构建各类事件对应的混合高斯隐马尔可夫识别模型,进而实现对微震信号的自动识别分类。研究结果表明:运用基于梅尔倒谱系数的微震信号识别分类方法对矿山实际微震数据进行测试,微震事件的识别分类准确率达到92.46%,具有较高的准确性,为实现微震监测系统的实时性分析提供了技术支持。     

工业噪声对脑认知影响的功率谱估计分析

为明确工业噪声对大脑认知的负面影响,采集火电厂球磨机的工业噪声,征集10名在校大学生在90 dB(A)的稳态工业噪声状态下及安静状态下的32导联脑电图(EEG)。采用傅里叶变换方法进行频域分析,提取δ频段、θ频段、α1频段、α2频段和β频段功率谱,并进行统计分析。结果表明:噪声环境与静音环境相比较,被试在δ频段、θ频段功率谱值明显增加,在α1频段内,噪声状态的功率谱值高于静音状态,在α2频段内正好相反。生产性噪声刺激可导致被试注意力分散,可通过各波段功率谱值或比率参数等评估噪声对认知的影响程度大小。     

压力管道泄漏声发射源定位的实验研究

结合实验室声发射仪和油气管道设备,建立了充气管道泄漏声发射检测系统模型,分别在传感器间距、管道压力和泄漏量三种变化状态下进行了泄漏源定位影响实验。对管道泄漏声发射信号的时域统计特征、频域分布特征以及泄漏信号的相关性作了分析;从声信号能量累计和衰减特性方面对互相关定位法和幅度衰减测量区域定位法的可行性进行了计算,表明在传感器间距较小和泄漏量较小的状态下,在背景噪声较小的环境中,用互相关法具有较好的定位精度;而幅度衰减测量区域定位方法对泄漏源的定位误差较大。     

基于小波分析的声发射信号处理

小波分析作为一种新的信号分析处理方法，可对任意信号，信号的任一时刻、任一频段进行时频分析。将小波分析用于声发射信号处理，有助于声发射技术的发展与推广应用。     

五老峰隧道岩爆声发射参数特征研究

为研究岩爆事件的声发射特征,为岩爆灾害的进一步监测预警提供依据,对五老峰隧道掌子面附近区域岩爆事件进行声发射监测,以RA均值作为主要参数,研究岩爆发生前后的参数变化规律,并通过与b值等参数分析结果的相互印证,对比岩爆信号与爆破震动信号之间的区别。试验结果表明:不同传感器因为布设位置、耦合程度的差异,接收到的声发射信号数量与参数分布范围存在较大差异;RA均值作为参数分析依据,能够较好地反映岩爆事件的孕育发展过程,且能够一定程度上消除传感器接收信号数量差异的影响,更稳定地反映岩爆事件的信号特征;岩爆事件发生前RA均值与事件密度不断升高,峰值后则都迅速降低,而爆破产生的声发射信号则在RA值上存在一定突变性,且峰值后仍保持较高水平。本次监测中,共发生1次微型岩爆,而在左洞爆破后,声发射信号明显增多,但并未产生显著破裂事件。     

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.     

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.     

Leak location of pipelines based on transient model and PSO-SVM

An improved and integrated approach of support vector machine and particle swarm optimization theory (PSO-SVM) is first used to detect the leak location of pipelines and overcome the problem of multiple leaks. The calibration and predictive ability of improved PSO-SVM is investigated and compared with that of other common method, back-propagation neural network (BPNN). Two conditions are evaluated. One with a leak involves a set of 20 samples, while another with two leaks has 127 samples. Both internal and external validations are performed to validate the performance of the resulting models. The results show that, for the two conditions, the values calculated by improved PSO-SVM are in good agreement with those simulated by transient model, and the performances of improved PSO-SVM models are superior to those of BPNN. This paper provides a new and effective method to inspect the multiple leak locations, and also reveals that improved PSO-SVM can be used as a powerful tool for studying the leak of pipeline.     

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.     

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.     

浅埋隧道下穿超近距密集管线施工变形时空特性研究

为分析浅埋隧道下穿密集管线施工地层与管线群变形时空特性,基于南昌地铁三号线邓埠站1号出入口暗挖隧道工程,利用理论分析、数值分析结合现场监测的方法进行研究。研究结果表明：隧道上方密集管线中位于前方的管线先承担开挖释放的部分土体应力,使其后方管线的变形大幅减小,平均减幅达23%;地层变形始终朝向掌子面,在掌子面到达时水平位移最大;因管线-土体共同作用,土体释放部分应力转移到地下管线,使地层沉降减小24%～38%,沉降槽宽度扩大40%;施工期间建议对污水管变形重点监测,在管线平均变形速率急速增大时,需提高监测频率。研究结果可为该地区相似工程施工提供参考。     

基于一维卷积神经网络的燃气管道泄漏声发射信号识别*

为保障燃气管道系统安全运行,及时诊断管道故障,基于VGG-16模型提出基于一维卷积神经网络的燃气管道故障诊断模型,提取原始声发射信号特征参数,有效诊断燃气管道故障。结果表明:基于一维卷积神经网络的燃气管道故障诊断模型,能够有效解决燃气管道故障诊断过程中数据预处理复杂、特征提取困难以及识别准确率低等问题,可为燃气管道故障诊断提供技术支撑。     

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.