Identifying Flow Pattern of Horizontal Oil-Water Two-Phase Flow Based on Multiscale Ordinal Transition Entropy

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2024-12-11 DOI:10.1109/JSEN.2024.3509976

Qianru Dai;Weikai Ren;Jiachen Zhang;Ningde Jin

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Abstract

To comprehend the complex flow structure and elucidate the dynamic evolution mechanism of horizontal oil-water two-phase flow, a more precise and effective method for identifying and analyzing flow patterns is urgently required. In this study, we conduct the experimental simulations under various flow conditions using a small-diameter acrylic glass pipe to gather data. Tap water and 3# industrial oil are used in these simulations. Utilizing a high-speed camera along with the signal response from mini-conductance probes, we classify the standard flow patterns under different conditions. Four typical flow patterns were observed: stratified flow (ST), ST with mixing at the interface (ST&MI), dispersion of oil in water and water (D O/W&W), and dispersion of water in oil and oil in water (D W/O&O/W). Employing an ordinal network, we calculated the entropy index of ultrasonic velocity signals. The mean value and slope of entropy at different scales were combined to construct a joint plane, which yielded satisfactory results in the flow pattern map. Multiscale entropy effectively captures the complex characteristics of two-phase flow and aids in explaining the transition mechanism between flow patterns. Experimental applications confirm the practical utility of this approach. The ordinal transition entropy provides insights into fluid flow characteristics and aids in understanding the flow pattern evolution process.

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基于多尺度有序过渡熵的水平油水两相流流型识别

为了理解复杂的流动结构，阐明水平油水两相流动的动态演化机制，迫切需要一种更精确、更有效的流型识别和分析方法。在本研究中，我们使用小直径丙烯酸玻璃管进行了不同流动条件下的实验模拟，以收集数据。在这些模拟中使用自来水和3#工业油。利用高速摄像机和微型电导探头的信号响应，我们对不同条件下的标准流模式进行了分类。观察到四种典型的流动模式：分层流动（ST）、界面混合流动（ST&MI）、油在水和水中的分散（D O/W&W）、水在油和油在水中的分散（D W/O&O/W）。利用有序网络计算了超声速度信号的熵指数。将不同尺度下的熵均值和熵斜率组合成一个联合平面，得到了满意的流型图。多尺度熵有效地捕捉了两相流的复杂特征，有助于解释流型之间的转换机制。实验应用证实了该方法的实用性。序转捩熵提供了对流体流动特性的认识，有助于理解流型演化过程。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice