基于IEEMD样本熵分析的管道泄漏定位

为降低城市管道泄漏定位误差,提出1种改进的集合经验模态分解（IEEMD）样本熵分析的管道多点泄漏定位方法。首先通过在EEMD中添加自相关函数计算和EMD算法,得到IEEMD;然后应用IEEMD可将原始泄漏信号直接去噪并分解为真实信号分量和冗余分量,经样本熵分析计算剔除冗余分量,获得有效泄漏信号;最后根据互相关时延计算和声发射时差定位法精确计算泄漏点位置。结果表明:该方法泄漏信号提取效果好、计算效率更高,有效提高了信号的信噪比,降低了信号的均方误差;该方法将管道泄漏定位误差降低至4.06%,较大程度提高了管道泄漏定位精确度。     

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.     

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.     

基于特征提取的输油管道泄漏系数预测*

为准确预测管道泄漏系数,估计管道泄漏量,以基于瞬变流方法的模拟数据为例,建立多个管道泄漏系数预测模型(多层感知机、长短期记忆网络、随机森林、支持向量机以及K近邻回归),综合考虑管道流量和压力数据特点,提出序列提取法和均值提取法2种管道时序数据预处理方法,模型评价指标为相关系数（R2）和平均绝对百分比误差（MAPE）。研究结果表明:随机森林和多层感知机的抗噪性较强,在5%的噪声影响下,模型准确度下降幅度较小;均值提取法去噪功能较好,可在一定程度上降低噪声影响;基于均值提取法的多层感知机模型效果相对较好,R2为0.997 5,MAPE为1.599%,研究结果可为准确预测管道泄漏系数、估计泄漏量提供指导。     

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.     

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.     

基于声信号特征分析的燃气管道探测识别方法

为了探测和辨识地下燃气管道,避免燃气管道改扩建的过程发生第三方破坏引发安全事故,提出1种基于声信号特征分析的燃气管道探测识别方法,该方法考虑燃气管道声信号声压级低以及易衰减的特点,采用Hilebert-Huang变换算法分析燃气管道流噪声信号特征,建立燃气管道流噪声信号的特征数据库,并通过BP神经网络进行模式识别,判别...     

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.     

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FXLMS算法的矿用有源耳罩的研究

基于矿井中低频噪声突出,存在时间长、危害大,尤其周期性噪声比重较大,而传统降噪技术对其降噪效果并不明显,提出了基于fxlms 算法的自适应有源降噪耳罩降低矿井中的低频周期性信号,并采用离线建模方法建立了次级通道模型,利用MATLAB8.0拟合了64阶的滤波器,对 矿井中具有代表性的1kHz低频周期噪声和伴有随机噪声的1kHz低频周期性噪声进行了降噪仿真研究。结果表明:1kHz低频周期性噪声的降噪量 达到了30dB。而且在本模型下,随机噪声对低频周期性噪声的降噪效果几乎没有影响。     

基于小波包熵与AFSA-SVM的压力管道泄漏识别

为了快速、准确地诊断出输气压力管道不同的泄漏状态,提出了一种基于小波包熵与人工鱼群优化支持向量机(AFSA-SVM)相结合的压力管道泄漏模式识别方法。该方法首先对管道泄漏时产生的声发射信号进行小波包分解,并对分解的最后一层节点重构信号进行相关性分析,以获得敏感的节点信号。然后求取这些敏感节点信号的小波包熵值,作为管道不同泄漏信号的特征向量。最后将小波包熵值输入到SVM中,并运用AFSA方法对SVM分类器中惩罚因子C与核函数参数g进行全局优化,以提高其分类准确率。实验结果表明,该方法能准确地识别压力管道不同的泄漏状态,为天然气管道泄漏状态监测提供新方法。     

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。     

多传感器耦合区域火灾报警技术研究

早期预警与低误报率一直是建筑火灾探测面临的挑战与难题。已有研究多针对特殊场所特定燃烧产物或多种传感器耦合,普适性不强,探测设备成本高,无法大规模应用。通过将火灾烟气蔓延规律与探测器信号时空分布融合,在不增加探测器数量和分布的情况下,提出了一种基于建筑结构微元的多传感器耦合区域火灾报警模型。对典型火灾场景的烟气蔓延情况进行了模拟分析,狭长结构中探测器信号强度变化具有一定的规律性。应用区域火灾报警模型后,报警时间较传统模式提前了14.7%,基本杜绝了单个探测器误报引发建筑物火灾报警的问题。结果表明:多传感器耦合探测模式显著缩短了火灾报警时间,降低了火灾探测误报率,实现了火灾的早期准确识别与预警。     

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EMD-HHT可定位长输天然气管道第三方破坏事件监测技术

为适应目前管道安全监测需要,满足对扰动信号分类监测的实际需求,提出1种基于希尔伯变换和经验模态分解(EMD-HHT)的信号特征提取技术,利用基于φ-OTDR分布式光纤传感系统采集振动信号,通过EMD+HHT区分算法对管道沿线振动事件进行分解并提取6个典型特征向量,各特征事件数据经过EMD后选取IMF3为最终提取特征向量的原始数据,BP神经元网络可有效识别机械破坏、敲击破坏、车辆经过、人工挖掘、动力干扰5种事件。研究结果表明：在长输管道信号识别中,BP神经网络对5类事件平均识别率高达98.6%,该技术分类识别5类事件扰动信号,能够达到较高准确性,并且误报率平均在1.3%,能较好满足现场安全实时监测需求。研究结果对长输油气管道附近第三方破坏扰动信号分类监测具有一定参考意义。     

基于稳态模型的井下抽采主管道泄漏检测方法研究*

为准确检测煤矿井下瓦斯抽采主管道泄漏位置,提出基于稳态模型的管道泄漏检测与定位方法,采用Comsol数值模拟及地面相似实验研究压力梯度法对煤矿井下抽采管道泄漏检测与定位的可行性及准确性。研究结果表明:管道未泄漏时,管内沿线压力呈均匀分布,当管道突发泄漏时,管内压力分布呈现明显弯折现象,弯折处即为管道漏点位置,并对管道阻力计算公式进行修正,提高了检测准确性;随着管道泄漏程度的加大,湍流效应显著增强,漏点处速度、压力产生明显突变,且当其他条件恒定时,随着管道泄漏孔径的扩大,管道的漏入量越大,定位的相对误差越小;在宏岩矿开展地面相似实验,实验结果绝对误差为4.5 m,相对误差为6%;在阳煤五矿井下8421抽采巷进行现场应用,绝对误差134 m,相对误差约7.95%。     

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。     

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.     

可变径管道漏磁检测有限元仿真与实验研究

为了更好地支持压力管道检验,降低事故率,本文基于漏磁检测原理,利用有限元分析软件建立了管道外漏磁检测模型,对管道漏磁检测进行了仿真计算,得到了缺陷处漏磁场特征曲线,模拟了圆柱形缺陷对管道外壁漏磁场的影响,得出了不同参数缺陷对漏磁场的影响规律,并且基于理论和有限元计算结果试制了可变径管道外漏磁检测仪的样机,利用该检测仪对壁厚为8mm的带有人工缺陷的管道进行扫描检测,研究不同参数缺陷对漏磁场信号的影响规律。结果表明,所得结果与有限元仿真的结果吻合良好,且缺陷检测精度及效果满足要求,另外,检测装置对内外壁缺陷检测同样可行有效,适合特种设备（压力管道）检测的工程应用。