CN102269684A - Small-diameter pipeline liquid-liquid two-phase flow flow pattern identification system and method - Google Patents
Small-diameter pipeline liquid-liquid two-phase flow flow pattern identification system and method Download PDFInfo
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Abstract
本发明公开了一种小管道液液两相流流型辨识系统与方法。它由透明绝缘管道、电容传感器、电容/电压转换器、电容数据采集单元、光学传感器、光电流/电压转换器、光学数据采集单元以及计算机组成。首先利用电容传感器和光学传感器同时获得反映液液两相流流态变化的测量信号，然后提取测量信号的时域特征量（均值和标准差）、幅值域特征量（概率密度函数曲线的峰度和偏度）和频域特征量（信号在不同频段所占的能量百分比），再将特征量输入最小二乘支持向量机流型分类器，最终实现小管道液液两相流流型辨识。本发明具有非接触、精度高等优点，不仅能对小管道液液两相流的多种流型进行有效辨识，而且可为液液两相流其他参数测量问题提供有益的借鉴。
The invention discloses a system and method for identifying a liquid-liquid two-phase flow pattern in a small pipeline. It consists of a transparent insulating pipe, a capacitive sensor, a capacitive/voltage converter, a capacitive data acquisition unit, an optical sensor, a photoelectric current/voltage converter, an optical data acquisition unit and a computer. First, the capacitive sensor and the optical sensor are used to obtain the measurement signal reflecting the change of the liquid-liquid two-phase flow state at the same time, and then the time domain characteristic quantity (mean value and standard deviation), the amplitude domain characteristic quantity (the peak value of the probability density function curve) of the measurement signal are extracted degree and skewness) and frequency-domain feature quantity (the energy percentage of the signal in different frequency bands), and then input the feature quantity into the least squares support vector machine flow pattern classifier, and finally realize the flow pattern identification of liquid-liquid two-phase flow in small pipes . The invention has the advantages of non-contact and high precision, not only can effectively identify various flow patterns of liquid-liquid two-phase flow in small pipes, but also can provide useful reference for other parameter measurement problems of liquid-liquid two-phase flow.
Description
技术领域 technical field
本发明涉及多相流测量领域，尤其涉及一种小管道液液两相流流型辨识系统及方法。 The present invention relates to the field of multiphase flow measurement, in particular to a flow pattern identification system and method for liquid-liquid two-phase flow in a small pipeline.
背景技术 Background technique
液液两相流系统广泛存在于石油、日化、食品、制药等工业领域。近年来，随着工业设备小型化趋势的发展，毫米级小管道液液两相流体系得到越来越多的研究和应用，其参数的在线检测也受到越来越多的关注。然而，相对于其他尺度下的液液两相流而言，毫米级小管道液液两相流的机理研究和工程应用还相对薄弱，相应的检测技术更是极为缺乏，急需加强。 Liquid-liquid two-phase flow systems are widely used in petroleum, daily chemical, food, pharmaceutical and other industrial fields. In recent years, with the development of the miniaturization trend of industrial equipment, the liquid-liquid two-phase flow system in millimeter-scale small pipes has been more and more researched and applied, and the online detection of its parameters has also attracted more and more attention. However, compared with liquid-liquid two-phase flow at other scales, the mechanism research and engineering application of liquid-liquid two-phase flow in millimeter-scale small pipes are still relatively weak, and the corresponding detection technology is extremely lacking, which urgently needs to be strengthened.
流型作为液液两相流的一个重要参数，不仅影响着两相流的流体动力学特性和传热传质性能，而且在很大程度上影响着对两相流其他参数的准确测量。因此，流型的准确辨识对液液两相流的研究和工程应用具有重要的意义。然而，液液两相流流动特性非常复杂，并且由于尺度不同，小管道液液两相流又常常表现出与常规管径液液两相流不同的特性，这些都为小管道液液两相流的流型辨识提出了更高的要求和挑战。目前，小管道液液两相流流型辨识方面的文献报道还极为有限，急需大力研究发展。 As an important parameter of liquid-liquid two-phase flow, flow pattern not only affects the hydrodynamic characteristics and heat and mass transfer performance of two-phase flow, but also affects the accurate measurement of other parameters of two-phase flow to a large extent. Therefore, accurate identification of flow pattern is of great significance to the research and engineering application of liquid-liquid two-phase flow. However, the flow characteristics of liquid-liquid two-phase flow are very complex, and due to different scales, liquid-liquid two-phase flow in small pipes often exhibits different characteristics from liquid-liquid two-phase flow in conventional pipes. The flow pattern identification of the flow puts forward higher requirements and challenges. At present, the literature reports on the flow pattern identification of liquid-liquid two-phase flow in small pipes are still very limited, and vigorous research and development are urgently needed.
发明内容 Contents of the invention
本发明的目的是克服现有研究和技术的不足，提供一种小管道液液两相流流型辨识系统及方法。 The purpose of the present invention is to overcome the deficiencies of the existing research and technology, and provide a small pipeline liquid-liquid two-phase flow pattern identification system and method.
小管道液液两相流流型辨识系统包括透明绝缘管道、电容传感器、电容/电压转换器、电容数据采集单元、光学传感器、光电流/电压转换器、光学数据采集单元以及计算机；电容传感器和光学传感器分别安装于透明绝缘管道上，电容传感器与电容/电压转换器相连接，电容/电压转换器经电容数据采集单元与计算机相连接，光学传感器与光电流/电压转换器相连接，光电流/电压转换器经光学数据采集单元与计算机相连接。 The small pipeline liquid-liquid two-phase flow pattern identification system includes a transparent insulating pipeline, a capacitance sensor, a capacitance/voltage converter, a capacitance data acquisition unit, an optical sensor, a photocurrent/voltage converter, an optical data acquisition unit, and a computer; the capacitance sensor and The optical sensors are respectively installed on the transparent insulating pipe, the capacitance sensor is connected with the capacitance/voltage converter, the capacitance/voltage converter is connected with the computer through the capacitance data acquisition unit, the optical sensor is connected with the photocurrent/voltage converter, and the photocurrent The /voltage converter is connected with the computer through the optical data acquisition unit.
所述的电容传感器为：两片尺寸相同的金属电极，即激励电极和检测电极，相对于绝缘管道中心轴对称地粘贴在绝缘管道外壁，激励电极与导线相连，检测电极也与导线相连，激励电极与检测电极之间紧贴管道外壁安装保护电极，整个测量管道外侧包裹金属屏蔽罩，保护电极与金属屏蔽罩相连接。 The capacitive sensor is as follows: two metal electrodes of the same size, that is, the excitation electrode and the detection electrode, are symmetrically pasted on the outer wall of the insulation pipe relative to the central axis of the insulation pipe, the excitation electrode is connected to the wire, and the detection electrode is also connected to the wire. The protective electrode is installed close to the outer wall of the pipeline between the electrode and the detection electrode, and the outer side of the entire measurement pipeline is wrapped with a metal shield, and the protective electrode is connected to the metal shield.
所述的光学传感器包括透明管道、激光器、柱透镜和光电池，激光器和柱透镜顺次安装于透明管道一侧，激光器和柱透镜光轴垂直于透明管道中心轴，在透明管道另一侧与激光器和柱透镜光轴垂直的平面安装光电池。 The optical sensor includes a transparent pipe, a laser, a cylindrical lens and a photocell. The laser and the cylindrical lens are installed on one side of the transparent pipe in sequence. The photocell is mounted on a plane perpendicular to the optical axis of the cylindrical lens.
小管道液液两相流流型辨识方法的步骤如下： The steps of the flow pattern identification method for liquid-liquid two-phase flow in small pipes are as follows:
1）分别由电容传感器和光学传感器同时获得反映小管道液液两相流流态变化的测量信号，电容测量信号经电容/电压转换器转换成电压信号，经由电容数据采集单元送入计算机，光学测量信号经光电流/电压转换器转换成电压信号后，经由光学数据采集单元送入计算机； 1) The measurement signal reflecting the change of the liquid-liquid two-phase flow in the small pipeline is obtained simultaneously by the capacitance sensor and the optical sensor respectively. The capacitance measurement signal is converted into a voltage signal by a capacitance/voltage converter and sent to the computer through the capacitance data acquisition unit. After the measurement signal is converted into a voltage signal by the photocurrent/voltage converter, it is sent to the computer through the optical data acquisition unit;
2）提取小管道液液两相流电容测量信号和光学测量信号的时域、幅值域和频域特征量； 2) Extract the time domain, amplitude domain and frequency domain feature quantities of the small pipeline liquid-liquid two-phase flow capacitive measurement signal and optical measurement signal;
3）将所提取的电容测量信号及光学测量信号的特征量输入由最小二乘支持向量机建立的流型分类器，对小管道液液两相流流型进行在线辨识。 3) Input the extracted characteristic quantities of the capacitance measurement signal and the optical measurement signal into the flow pattern classifier established by the least squares support vector machine, and conduct online identification of the flow pattern of the liquid-liquid two-phase flow in the small pipe.
步骤2）所述的提取小管道液液两相流电容测量信号和光学测量信号的时域、幅值域和频域特征量的步骤为： Step 2) The steps of extracting the time domain, amplitude domain and frequency domain feature quantities of the small pipeline liquid-liquid two-phase flow capacitive measurement signal and optical measurement signal are:
（1）时域特征量提取 (1) Time-domain feature extraction
所提取的时域特征量为小管道液液两相流测量信号的均值和标准差， The extracted time-domain feature quantity is the mean value and standard deviation of the measurement signal of the liquid-liquid two-phase flow in the small pipe,
均值： 
标准差：
其中
（2）幅值域特征量提取 (2) Amplitude Domain Feature Extraction
所提取的幅值域特征量为小管道液液两相流测量信号概率密度函数曲线的峰度
峰度：
偏度： Skewness:
其中
（3）对小管道液液两相流的电容测量信号和光学测量信号进行经验模态分解，得到多层固有模态函数分量，求取前12层固有模态函数分量的能量各自占所有固有模态函数分量总能量的百分比， (3) Perform empirical mode decomposition on the capacitive measurement signal and optical measurement signal of the liquid-liquid two-phase flow in a small pipeline to obtain the multi-layer intrinsic mode function components, and calculate the energy of the first 12 intrinsic mode function components. percentage of the total energy of the modal function components,
其中，
（4）获得代表小管道液液两相流流型特征的32个特征量 (4) Obtain 32 characteristic quantities representing the flow pattern characteristics of liquid-liquid two-phase flow in small pipes
其中， in,
为16个电容测量信号特征量， Measure signal characteristic quantities for 16 capacitors,
为16个光学测量信号特征量。 Signal characteristic quantities are measured for 16 optics.
步骤3）所述的将所提取的电容测量信号及光学测量信号的特征量输入由最小二乘支持向量机建立的流型分类器，对小管道液液两相流流型进行在线辨识的步骤为： Step 3) The step of inputting the extracted characteristic quantities of the capacitance measurement signal and the optical measurement signal into the flow pattern classifier established by the least squares support vector machine, and performing online identification of the flow pattern of the liquid-liquid two-phase flow in the small pipe for:
对于所辨识的多种小管道液液两相流流型，在每两种流型之间均设计一个基于最小二乘支持向量机的两类分类器，每个流型分类器的决策函数都具有如下的形式： For the identified various flow patterns of liquid-liquid two-phase flow in small pipes, a two-class classifier based on the least squares support vector machine is designed between each two flow patterns, and the decision function of each flow pattern classifier is has the following form:
其中，
对于待测试流型样本，首先提取信号在时域、幅值域以及频域的特征量，然后将所提取的特征量输入每一个分类器进行测试，并根据测试结果向相应的流型投一票，最终得票最多的流型就作为当前流型辨识的结果。 For the sample of the flow pattern to be tested, first extract the feature quantity of the signal in the time domain, amplitude domain and frequency domain, and then input the extracted feature quantity into each classifier for testing, and cast a test value to the corresponding flow pattern according to the test results. votes, and finally the flow pattern with the most votes is used as the result of the current flow pattern identification.
本发明提供了一种小管道液液两相流流型辨识系统及方法。具有非接触、辨识精度高等优点，不仅为小管道液液两相流的流型辨识提供了一条可行且有效的途径，而且可为小管道液液两相流其他参数测量问题提供有益的借鉴。 The invention provides a flow pattern identification system and method for liquid-liquid two-phase flow in a small pipeline. With the advantages of non-contact and high identification accuracy, it not only provides a feasible and effective way for flow pattern identification of liquid-liquid two-phase flow in small pipelines, but also provides a useful reference for other parameter measurement problems of liquid-liquid two-phase flow in small pipelines.
附图说明 Description of drawings
图1是小管道液液两相流流型辨识系统结构框图； Fig. 1 is a structural block diagram of the flow pattern identification system for liquid-liquid two-phase flow in a small pipeline;
图2是本发明的电容传感器构成示意图； Fig. 2 is a schematic view of the composition of the capacitive sensor of the present invention;
图3是本发明的光学传感器构成示意图； Fig. 3 is a schematic view of the composition of the optical sensor of the present invention;
图4是小管道液液两相流流型辨识方法的流程图。 Fig. 4 is a flowchart of a flow pattern identification method for liquid-liquid two-phase flow in a small pipeline.
具体实施方式 Detailed ways
发明针对小管道液液两相流流型辨识方法缺乏的现状，综合利用电容传感器、光学传感器，以及概率密度函数（Probability Density Function, PDF）、经验模态分解(Empirical Mode Decomposition, EMD)和最小二乘支持向量机(Least Squares Support Vector Machines, LS-SVM)等先进的信息处理技术，提出了一种小管道液液两相流流型辨识的系统与方法。具有非接触、精度高等优点，能对小管道液液两相流的多种流型进行有效辨识。 The invention aims at the current situation of the lack of flow pattern identification methods for liquid-liquid two-phase flow in small pipelines, and comprehensively utilizes capacitive sensors, optical sensors, and probability density functions (Probability Density Function, PDF), Empirical Mode Decomposition (Empirical Mode Decomposition, EMD) and minimum Using advanced information processing technologies such as Least Squares Support Vector Machines (LS-SVM), a system and method for flow pattern identification of liquid-liquid two-phase flow in small pipes are proposed. With the advantages of non-contact and high precision, it can effectively identify various flow patterns of liquid-liquid two-phase flow in small pipes.
如图1所示，小管道液液两相流流型辨识系统包括透明绝缘管道、电容传感器、电容/电压转换器、电容数据采集单元、光学传感器、光电流/电压转换器、光学数据采集单元以及计算机；电容传感器和光学传感器分别安装于透明绝缘管道上，电容传感器与电容/电压转换器相连接，电容/电压转换器经电容数据采集单元与计算机相连接，光学传感器与光电流/电压转换器相连接，光电流/电压转换器经光学数据采集单元与计算机相连接。 As shown in Figure 1, the small pipeline liquid-liquid two-phase flow pattern identification system includes a transparent insulating pipeline, a capacitance sensor, a capacitance/voltage converter, a capacitance data acquisition unit, an optical sensor, a photocurrent/voltage converter, and an optical data acquisition unit and a computer; the capacitance sensor and the optical sensor are respectively installed on the transparent insulating pipe, the capacitance sensor is connected with the capacitance/voltage converter, the capacitance/voltage converter is connected with the computer through the capacitance data acquisition unit, and the optical sensor is connected with the photocurrent/voltage conversion The photoelectric current/voltage converter is connected with the computer through the optical data acquisition unit.
如图2所示，电容传感器为：两片尺寸相同的金属电极，即激励电极1和检测电极2，相对于绝缘管道中心轴对称地粘贴在绝缘管道3外壁，激励电极与导线4相连，检测电极与导线5相连，激励电极与检测电极之间紧贴管道外壁安装保护电极6，整个测量管道外侧包裹金属屏蔽罩7，保护电极与金属屏蔽罩相连接。
As shown in Figure 2, the capacitive sensor is: two metal electrodes of the same size, that is, the excitation electrode 1 and the detection electrode 2, are symmetrically pasted on the outer wall of the insulating pipe 3 with respect to the central axis of the insulating pipe, and the excitation electrode is connected with the wire 4. The electrodes are connected to the
如图3所示，光学传感器包括透明管道、激光器、柱透镜和光电池，激光器和柱透镜顺次安装于透明管道一侧，激光器和柱透镜光轴垂直于透明管道中心轴，在透明管道另一侧与激光器和柱透镜光轴垂直的平面安装光电池。传感器工作时，激光器产生的点光源经柱透镜后转变为片光，该片光作为入射光正交地投射到透明管道上，穿过管内液液两相流，从透明管道另一侧出射，投射于光电池上，光电池将所探测到的光强转换为电流信号输出。 As shown in Figure 3, the optical sensor includes a transparent pipe, a laser, a cylindrical lens, and a photocell. The laser and the cylindrical lens are installed on one side of the transparent pipe in sequence, and the optical axes of the laser and the cylindrical lens are perpendicular to the central axis of the transparent pipe. Mount photocells on a plane with sides perpendicular to the optical axis of the laser and cylindrical lens. When the sensor is working, the point light source generated by the laser is transformed into a sheet of light after passing through the cylindrical lens. The sheet of light is projected onto the transparent pipe orthogonally as the incident light, passes through the liquid-liquid two-phase flow in the pipe, and exits from the other side of the transparent pipe. Projected on the photocell, the photocell converts the detected light intensity into a current signal output.
在实际的流型在线辨识过程中，液液两相流进入测量管路，并流经电容传感器和光学传感器。电容传感器所获得的电容测量信号经电容/电压转换器转换成电压信号，再由电容数据采集单元送入计算机。光学传感器所获得的光学测量信号经光电流/电压转换器转换成电压信号，再由光学数据采集单元送入计算机。计算机对所获得的电容测量信号和光学测量信号进行存储、分析和计算。 In the actual process of on-line identification of the flow pattern, the liquid-liquid two-phase flow enters the measurement pipeline and flows through the capacitive sensor and the optical sensor. The capacitance measurement signal obtained by the capacitance sensor is converted into a voltage signal by the capacitance/voltage converter, and then sent to the computer by the capacitance data acquisition unit. The optical measurement signal obtained by the optical sensor is converted into a voltage signal by the photocurrent/voltage converter, and then sent to the computer by the optical data acquisition unit. The computer stores, analyzes and calculates the obtained capacitance measurement signal and optical measurement signal.
如图4所示，小管道液液两相流流型辨识方法的步骤如下： As shown in Figure 4, the steps of the flow pattern identification method for liquid-liquid two-phase flow in small pipes are as follows:
1）分别由电容传感器和光学传感器同时获得反映小管道液液两相流流态变化的测量信号，电容测量信号经电容/电压转换器转换成电压信号，经由电容数据采集单元送入计算机，光学测量信号经光电流/电压转换器转换成电压信号后，经由光学数据采集单元送入计算机； 1) The measurement signal reflecting the change of the liquid-liquid two-phase flow in the small pipeline is obtained simultaneously by the capacitance sensor and the optical sensor respectively. The capacitance measurement signal is converted into a voltage signal by a capacitance/voltage converter and sent to the computer through the capacitance data acquisition unit. After the measurement signal is converted into a voltage signal by the photocurrent/voltage converter, it is sent to the computer through the optical data acquisition unit;
2）提取小管道液液两相流电容测量信号和光学测量信号的时域、幅值域和频域特征量； 2) Extract the time domain, amplitude domain and frequency domain feature quantities of the small pipeline liquid-liquid two-phase flow capacitive measurement signal and optical measurement signal;
3）将所提取的电容测量信号及光学测量信号的特征量输入由最小二乘支持向量机建立的流型分类器，对小管道液液两相流流型进行在线辨识。 3) Input the extracted characteristic quantities of the capacitance measurement signal and the optical measurement signal into the flow pattern classifier established by the least squares support vector machine, and conduct online identification of the flow pattern of the liquid-liquid two-phase flow in the small pipe.
步骤2）所述的提取小管道液液两相流电容测量信号和光学测量信号的时域、幅值域和频域特征量步骤为： Step 2) The steps of extracting the time domain, amplitude domain and frequency domain feature quantities of the small pipeline liquid-liquid two-phase flow capacitive measurement signal and optical measurement signal are:
（1）时域特征量提取 (1) Time-domain feature extraction
所提取的时域特征量为小管道液液两相流测量信号的均值和标准差， The extracted time-domain feature quantity is the mean value and standard deviation of the measurement signal of the liquid-liquid two-phase flow in the small pipe,
均值： 
标准差：
其中
（2）幅值域特征量提取 (2) Amplitude Domain Feature Extraction
所提取的幅值特征量为小管道液液两相流测量信号概率密度函数曲线的峰度
峰度： Kurtosis:
偏度：
其中
（3）对小管道液液两相流的电容测量信号和光学测量信号进行经验模态分解，得到多层固有模态函数分量。 (3) The empirical mode decomposition is performed on the capacitive measurement signal and the optical measurement signal of the liquid-liquid two-phase flow in a small pipe to obtain the multilayer intrinsic mode function components.
EMD分解根据信号自身的特点，按频率由高到低的顺序将原信号分解成有限层固有模态函数分量之和，每层固有模态函数分量都包含原信号的局部特征信息。每层经验模态函数分量需满足以下两个条件：1) 整个经验模态函数分量数据序列段，零点数与极点数相等或最多相差1，2）对任一数据点，局部极大值的包络和局部极小值的包络均值为零。依据此规则，固有模态函数分量被逐一“筛选”出来，直到时间序列变为一单调函数。最终，原始测量信号被分解为多层固有模态函数分量与趋势项的和，即： According to the characteristics of the signal itself, the EMD decomposition decomposes the original signal into the sum of finite layers of intrinsic mode function components in the order of frequency from high to low, and each layer of intrinsic mode function components contains local characteristic information of the original signal. The empirical mode function component of each layer needs to meet the following two conditions: 1) For the entire data sequence segment of the empirical mode function component, the number of zero points is equal to the number of poles or the difference is at most 1; 2) For any data point, the local maximum value The envelope and local minima have an envelope mean of zero. According to this rule, the intrinsic mode function components are “filtered” one by one until the time series becomes a monotone function. Finally, the original measurement signal is decomposed into the sum of multi-layer intrinsic mode function components and trend items, namely:
其中，
求取前12层固有模态函数分量的能量各自占所有固有模态函数分量总能量的百分比， Calculate the percentage of the energy of the first 12 layers of intrinsic mode function components to the total energy of all intrinsic mode function components,
其中，
（4）获得代表小管道液液两相流流型特征的32个特征量 (4) Obtain 32 characteristic quantities representing the flow pattern characteristics of liquid-liquid two-phase flow in small pipes
其中， in,
为16个电容测量信号特征量， Measure signal characteristic quantities for 16 capacitors,
为16个光学测量信号特征量。 Signal characteristic quantities are measured for 16 optics.
步骤3）所述的将所提取的电容信号及光学信号的特征量输入由最小二乘支持向量机建立的流型分类器，对小管道液液两相流流型进行在线辨识步骤为： Step 3) Input the extracted characteristic quantities of the capacitive signal and the optical signal into the flow pattern classifier established by the least squares support vector machine, and the online identification steps of the liquid-liquid two-phase flow flow pattern in the small pipeline are as follows:
对于所辨识的多种小管道液液两相流流型，如：塞状流、层状流、油基泡状流、水基泡状流、油核环状流以及水核环状流，在每两种流型之间均设计一个基于最小二乘支持向量机的两类分类器，六种典型流型总共设计15个两类分类器，每个流型分类器的决策函数都具有如下的形式： For the identified flow patterns of liquid-liquid two-phase flow in various small pipes, such as: plug flow, laminar flow, oil-based bubbly flow, water-based bubbly flow, oil-core annular flow and water-core annular flow, A two-class classifier based on the least squares support vector machine is designed between each two flow types. A total of 15 two-class classifiers are designed for six typical flow types. The decision function of each flow type classifier has the following form:
其中，
对于待测试流型样本，首先提取信号在时域、幅值域以及频域的特征量，然后将所提取的特征量输入每一个分类器进行测试，并根据测试结果向相应的流型投一票，最终得票最多的流型就作为当前流型辨识的结果。 For the sample of the flow pattern to be tested, first extract the feature quantity of the signal in the time domain, amplitude domain and frequency domain, and then input the extracted feature quantity into each classifier for testing, and cast a test value to the corresponding flow pattern according to the test results. votes, and finally the flow pattern with the most votes is used as the result of the current flow pattern identification.
已分别在内径为1.8mm，3.1mm和4.0mm的水平小管道上进行了油水两相流实验。利用本发明中所提出的系统与方法实现了对油水两相流六种典型流型：塞状流、层状流、油基泡状流、水基泡状流、油核环状流以及水核环状流的在线辨识，各管径下油水两相流流型辨识结果如表1所示。实验结果表明本发明所提出的小管道液液两相流流型辨识系统及方法是有效的，并取得了满意的流型辨识准确率，各管径下各典型流型的辨识准确率均在96%以上。 Oil-water two-phase flow experiments have been carried out on small horizontal pipes with inner diameters of 1.8mm, 3.1mm and 4.0mm, respectively. Using the system and method proposed in the present invention, six typical flow patterns of oil-water two-phase flow are realized: plug flow, laminar flow, oil-based bubble flow, water-based bubble flow, oil core annular flow and water The online identification of nuclear annular flow and the flow pattern identification results of oil-water two-phase flow under various pipe diameters are shown in Table 1. Experimental results show that the flow pattern identification system and method for liquid-liquid two-phase flow in small pipes proposed by the present invention are effective, and have achieved satisfactory flow pattern identification accuracy. The identification accuracy of each typical flow pattern under each pipe diameter is in the range of More than 96%.
the
表1 各管径下油水两相流流型辨识结果 Table 1 Flow pattern identification results of oil-water two-phase flow under various pipe diameters
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