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.     

Real-time leak detection in oil pipelines using an Inverse Transient Analysis model

Based on Inverse Transient Analysis (ITA) method, a real-time leak detection method is proposed to capture leak location and the associated leak rate in oil pipe conveyance systems. In the proposed approach, location and flow rate of leak (if any), the fluid properties, as well as physical parameters of the system, are calculated in consecutive periods through minimizing the discrepancy between the calculated and measured flow parameters of the system. The method of characteristics is employed to numerically calculate the transient responses of the system and the genetic algorithm is utilized as the optimization engine. The proposed approach was applied to several real pipeline systems in which the required transient flow data are either directly collected from the field or fabricated with a third-party numerical software. Extensive numerical explorations were conducted to investigate the performance of the proposed method in real-time leak detection and to determine the extent to which field data errors, stemming from Supervisory Control and Data Acquisition (SCADA) systems and measurement equipment, affect the leak flow rate and location detectability of the proposed approach. The results show that the proposed approach provides promising results under a variety of transient and steady-state flow conditions even in the case with small leak flow rate of around 2% of the line rate. The results also reveal that the noises in the measurement data and the errors originated from SCADA systems do not significantly compromise the leak detectability of the proposed approach, confirming that the proposed approach can be utilized in practice.     

串接组合式迷宫螺旋泵的气液两相流数值模拟及试验研究

为研究串接组合式迷宫螺旋泵在实际污水处理过程中的曝气增氧效果和内部的流动情况,应用计算流体力学FLUENT软件,基于混合物多相流模型,对串接组合式迷宫螺旋泵内部三维多相流场进行了数值模拟,分析了不同含气率条件下流场的压力、速度、气相分布情况,分析得出:泵的压力梯度在不同含气率下有所不同,但压力分布都是沿着轴向方向增加,增压效果明显;转子流域的速度明显高于定子流域,且随着含气率的增大,转子流域速度越来越小,定子流域速度越来越大;泵整体含气率比较均匀,随着含气率的增大,出口流域含气率明显高于进口流域和螺旋环流域,有大量气体聚集的现象。试验结果表明:泵的扬程模拟曲线和试验曲线基本吻合,扬程误差值在7%左右,说明数值模拟结果较为准确,串接组合式迷宫螺旋泵在进行气液混输时出口气泡均匀,水中含氧量多,具有良好的曝气增氧效果。     

Prediction of flammability limits of fuel-air and fuel-air-inert mixtures from explosivity parameters in closed vessels

Flammability limits of fuel-air and fuel-air-inert gaseous mixtures, especially at non-atmospheric conditions, are essential properties required for establishing safety operating conditions for handling and processing flammable gases. For pure fuels, an important data pool exists, formed by the flammability limits of fuel-air and fuel-air-inert gaseous mixtures at ambient initial conditions measured by standard methods. Such methods can be used for experimental determination of flammability limits for multi-fuels mixed with air, with or without additives, under non-atmospheric conditions. Their use is however a time- and material-consuming process; in addition, the flammability limits obtained by various standard methods may be scattered as a result of different choices in the operating parameters, for each standard method. It appears that a preliminary estimation of the flammability limits for fuel-air and fuel-air-inert gaseous mixtures can minimize the effort of measuring them in specific initial conditions.The present paper describes a new method for estimating the flammability range of fuel-oxidizer gaseous mixtures based on measurements of explosivity properties e.g. the peak explosion pressure and maximum rate of pressure rise recorded during closed vessel laminar explosions of fuel-oxidizer mixtures far from limits. Data obtained for several hydrocarbon-air gaseous mixtures with or without inert gas addition are used to examine the accuracy of estimated flammability limits (LFL – the lower and UFL – the upper flammability limit) as well as of the Limiting Oxygen Concentration (LOC) and the Minimum Inert Concentration (MIC). The predictive ability of the proposed method is examined against the predictive ability of other recently described methods.     

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.     

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.     

多点泄漏对天然气管道沿线压力的影响研究

为研究不同的多点泄漏工况对管道流动参数的影响,基于流动方程建立数学模型,讨论泄漏后压力下降幅值与泄漏位置、泄漏点数的关系,在室内输气环道采集多点泄漏工况下的压力信号并对理论分析结果进行验证。结果表明:泄漏点的上游和下游压力均减小,越靠近泄漏点压力降越大;2个泄漏点之间压力也下降,越靠近上游泄漏点,压力下降幅度越大;泄漏点距起点越近,泄漏引起的压力降低幅值越大。压力下降的幅值受距离起点最近的泄漏点位置影响最大,且随着泄漏点数的增多而增大。     

考虑心理阈值的突发事件多部门应急决策动态调整方法

针对多部门协同参与应急决策并执行应急方案的情形,提出一种考虑心理阈值的多部门应急决策动态调整方法。首先,将各部门的心理参照点作为识别框架,合成各部门心理参照点的基本概率分配,得到部门协同心理参照点;然后,引入心理阈值区间量化描述决策部门的心理行为,并结合部门协同心理参照点,得到不同情景关于经济损失和人员伤亡的满意度,进而合成情景属性满意度,计算各备选方案的总体满意度,并对方案排序择优;最后,通过案例分析验证本文提出方法的有效性和适用性。     

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.     

Modelling Complex Pipeline Network Leak Detection Systems

A novel model for detecting leaks in complex pipeline network systems has been developed. The model derives from the theory of Liapunov stability criteria. A leak is detected if the resulting eigenvalues from the deviation flow matrix have values less than a predetermined value. An advanced mesh network algorithm was used to decompose the complex pipeline network system into sub-networks. The flow model (equations of motion and continuity) which incorporates a leaking factor, k_L, is solved by a numerical technique that uses the method of characteristics and an implicit finite function. The unsteady state flow matrix of the complex pipeline network system was analysed using a modified Hardy Cross algorithm, where the velocity and pressure were computed for each node and pipeline loop in the complex network. The plots for the characteristic pressure and velocity eigenvalues show that pressure measurements are faster parameters for leak detection than volume measurements. Volume measurements appear to be suitable for larger leak systems and longer response time.     

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.     

基于风量-风压复合特征的通风系统阻变型故障诊断

为了避免风量单一特征进行故障位置诊断的不适定性,提出基于风量-风压复合特征的故障位置诊断方法,实现特征信息的多维互补,提高故障位置诊断的准确度。利用蒙特卡洛方法生成大致满足实际故障风阻值分布的故障仿真样本,为了避免不同变量之间不同量纲、不同数量级造成的数据损失,对原始风量、风压数据进行标准化处理,并分别以风量单一特征、风压单一特征、风量-风压复合特征作为支持向量机（SVM）的输入,构建通风系统阻变型故障位置诊断模型。通过故障模拟实验研究表明:风量、风压单一特征进行故障位置诊断的准确度分别为89.80%,90.34%,风量-风压复合特征进行故障位置诊断的准确度为98.23%,说明风量-风压复合特征进行故障诊断可以消除风量、风压单一特征进行故障诊断的不适定性,提高故障诊断的准确度。     

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.     

用于早期火灾分类的非线性决策树支持向量机

对早期火灾信息进行研究,提出了一种基于非线性决策树的支持向量机多类分类模型。该模型利用非线性映射将样本投影到高维特征空间,比较每类样本在高维空间的分布情况,进行聚类构造出一个二叉决策树,使容易区分的类别从根节点逐层分类出来,有效克服了错分积累和避免不可分情况;同时,各个节点采用二值最小二乘小波支持向量机,以获得较高的泛化能力。该文将该模型用于早期火灾分类,并与BP神经网络、K近邻法和决策树方法进行比较,实验结果表明,该模型对早期火灾的识别率更高。     

基于改进的未确知聚类模型的岩爆倾向性预测

在采用未确知聚类评价模型进行多指标分级评价时,常采用置信度识别准则作为待测对象的属性识别,该准则中置信度的取值由人为取定,当置信度取值不同时,得到的分级判定结果往往出现差异,甚至产生完全不同的判定结果。通过距离判别的思想将未确知聚类理论中的置信度识别准则进行改进,并运用到岩爆烈度的分级预测中。根据岩爆发生的主要影响因素,选取岩石单轴抗压强度σ_c、单轴抗拉强度σ_t、最大切应力σ_θ及岩石的弹性变形能指标W_(et)为岩爆主要影响因子。并以σ_c/σ_1、σ_θ/σ_c、W_(ey)为岩爆烈度等级评价因子,建立未确知测度模型,以距离判别改进后的属性识别方法进行分级预测,并与原置信度识别准则得到的判别结果进行分析和比较。为验证改进模型的实用性,以贵州开磷集团马路坪矿区为例,采用改进的未确知聚类模型对其岩爆烈度等级进行预测分析。结果表明,预测结果与实际情况基本吻合,证明采用改进后的未确知测度模型的判别结果不仅消除了由于置信度取值不同造成的判别结果误差,降低了人为主观因素的影响,而且具有较高的判别准确性和可行性。     

不同结构主扇扩散器局部阻力研究

在大主扇通风系统中多采用低压大流量风机,在风机出风段多安装扩散器,主要作用是降低出口动压提高风机静压而达到回收出风口断面动能的效果。重点分析风流在流经不同结构扩散器时的流场以及出口的动能损失,叙述了紊流过程中产生阻力的原因,实验测定风流在扩散器后的静压和出口断面的速度。通过数值模拟和实验证明:流线型扩散器局部阻力较小,且具有较高的动能回收率和扩散器效率。结果表明此内容研究对研究扩散器的最优设计参数和通风节能具有一定的指导作用。     

湿式纤维栅除尘器在KQl50型潜孔钻上的应用

介绍了用惯性除尘器、旋风除尘器、湿式纤维栅除尘器组成的三级串联除尘系统进行露天矿的钻机收尘,运行结果表明该系统运行可靠,阻力小,除尘效率高,系统出口含尘浓度达到排放标准.     

深水测试地面流程节流油嘴段温压场研究*

为对深水高压气井测试地面流程中的节流油嘴段的温压场及水合物生成情况进行研究,采用数值模拟的方式对整个节流管路进行气体流动特性分析。并利用P-T图回归公式法,得出不同温压场条件下的水合物生成情况,进行水合物生成范围对比。结果表明:针阀出口后端气体速度随着管路入口压力和针阀直径的增大而增大,随管路出口压力的增大而减小,而气体温度随管路入口压力、管路出口压力、针阀直径的变化趋势与之相反。管路入口压力的递增、管路出口压力的递减以及针阀直径的递增,都会导致针阀突变径处的速度场、温压场波动更加剧烈,并使得水合物生成范围扩大。     

Recognition on trigger condition of autonomous emergency braking system

Introduction: Automobiles carrying an autonomous emergency braking system (AEBS) are currently prevailing. While the reduction of traffic accidents is expected because of the widespread use of the system, concerns as regards many drivers using the system without proper understanding of the trigger conditions (TCs) have arisen. This research aims to grasp the degree of recognition of the AEBS TCs by a driver with a vehicle equipped with the system. Method: Using a web research company, we sent a survey sheet for screening to 9999 monitors randomly selected by gender and age group and confirmed own vehicle with an autonomous braking system ownership status. The number of answer targets was 200 for each of the four groups divided by age and gender. In this research, we developed a multivariate analysis model with the degree of understanding the AEBS TCs as the objective variable. The explanatory variables of this model were “Driver characteristics” and “Contact opportunities of information on the AEBS.” Results: Using PCA’s main component scores as the objective variable, two types of multiple regression models were constructed according to the AEBS TCs (do not work properly and work accidentally). The model analysis showed that gender, age, confidence in driving skill, and experience of the AEBS before purchasing are significant variables in both models. The recognition of the conditions of the “AEBS does not work properly” was influenced by the information-gathering ability and the degree of reference to various information. In contrast, the recognition of the conditions of the “AEBS work accidentally” was influenced by the interest of automobiles, such as the importance of automobile for self-expression and explanation taken up in a car magazine. Conclusions: This study clarified the driver characteristics and contact opportunities of information that have problems in recognizing the AEBS TCs. Practical Applications: Considering measures, such as public relations, utilizing this result will be meaningful in terms of road safety in the current stage, which is the transitional period of the AEBS.