油气水三相流多模式超声测试信号分析与流型辨识

doi:10.16085/j.issn.1000-6613.2024-1759

摘要/Abstract

摘要：

针对水平管道油气水三相流流型的准确辨识问题，提出一种脉冲波/连续波超声组合式测试手段与多域特征提取方案。研究中，首先利用单晶的脉冲波超声传感器与双晶的连续波超声传感器对水平管道油气水三相流开展动态实验测试，同步获取流动过程中的回波强度数据与多普勒频移数据。通过分析测试数据在不同流型下的响应特性，揭示了油气水三相流不同流型的流动特点，并从回波强度剖面中峰值所在管道径向位置的概率分布、平均流速波动时间序列与多普勒频移的频率分解中提取了相关特征，量化了相界面的空间域分布特性与流速的时域、频域波动特性。最终，利用所提取的多域特征向量搭建了基于随机森林的分类器，实现了水平管道中8种油气水三相流流型的准确识别，平均识别率达96.6%。所提方法为复杂工业多相流的流型辨识问题提供了一种简单、高效、低成本、非侵入性的解决方案，具有重要的科学与工程应用价值。

关键词: 油气水三相流, 流速, 界面, 测量, 流型识别, 仪器仪表

Abstract:

Aiming at the accurate identification of horizontal oil-gas-water three-phase flow pattern, a combined pulse-wave and continuous-wave ultrasonic sensing measurement method and a multi-domain feature extraction scheme were proposed. In this study, horizontal oil-gas-water three-phase flow dynamic experiments were firstly conducted, and a pulse-wave ultrasonic sensor with a single piezoelectric chip and a continuous-wave ultrasonic sensor with two piezoelectric chips were adopted to synchronously acquire the echo intensity data and Doppler frequency shift data during the flow process. By analyzing the signal responses to different flow patterns, the flow characteristics of different oil-gas-water three-phase flow patterns were revealed. Then, the probability distribution of the radial position of the maximum value in the echo intensity profile, the time series of the average flow velocity and the decomposition of the Doppler frequency shift signal were calculated, and several features were extracted from them to quantify the distribution characteristics of phase interfaces in spatial domain and the fluctuation characteristics of the flow velocity in time and frequency domains. Using the extracted multi-domain feature vector, a classifier based on the random forest was finally constructed, and 8 types of horizontal oil-gas-water three-phase flow patterns were accurately identified with a total identification accuracy of 96.6%. The proposed method provides a simple, efficient, low-cost, and non-invasive solution for the flow pattern identification of complex industrial multiphase flows, which has important scientific and engineering significance.

Key words: oil-gas-water three-phase flow, velocity, interface, measurement, flow pattern identification, instrumentation

中图分类号:

史雪薇, 谭超, 董峰. 油气水三相流多模式超声测试信号分析与流型辨识[J]. 化工进展, 2025, 44(4): 1834-1848.

SHI Xuewei, TAN Chao, DONG Feng. Oil-gas-water three-phase flow pattern identification based on multi-mode ultrasonic signal analysis[J]. Chemical Industry and Engineering Progress, 2025, 44(4): 1834-1848.

图/表 11

图1 脉冲波/连续波超声传感器结构与工作时序示意图

图2 多普勒频移信号获取方法

图3 油气水多相流实验测试环路

图4 水平管道中油气水三相流流型

图5 不同流型下的回波幅值时空分布

图6 不同流型下回波强度剖面中峰值所在管道径向位置的概率分布

图7 不同流型下的平均流速波动时间序列

图8 不同流型下多普勒频移信号的EEMD分解及IMF分量能量占比结果

图9 随机森林原理

图10 基于十折交叉验证的油气水三相流流型识别结果

表1 基于十折交叉验证的油气水三相流流型整体分类准确率

序号	样本总量	被正确分类的样本量	准确率/%
1	61	60	98.4
2	61	58	95.1
3	61	59	96.7
4	61	60	98.4
5	61	58	95.1
6	61	58	95.1
7	61	58	95.1
8	61	61	100
9	61	58	95.1
10	61	59	96.7

参考文献 34

1	THORN Richard, JOHANSEN Geir Anton, HAMMER Erling. Recent developments in three-phase flow measurement[J]. Measurement Science and Technology, 1997, 8(7): 691-701.
2	谭超, 董峰. 多相流过程参数检测技术综述[J]. 自动化学报, 2013, 39(11): 1923-1932.
	TAN Chao, DONG Feng. Parameters measurement for multiphase flow process[J]. Acta Automatica Sinica, 2013, 39(11): 1923-1932.
3	史雪薇, 谭超, 董峰. 基于环形电导传感器的气液两相流流型识别与过程参数测量[J]. 化工进展, 2024, 43(2): 637-648.
	SHI Xuewei, TAN Chao, DONG Feng. Gas-liquid two-phase flow pattern identification and flow parameters measurement based on the ring-shape conductance sensor[J]. Chemical Industry and Engineering Progress, 2024, 43(2): 637-648.
4	SALGADO W L, DAM R S F, SALGADO C M. Optimization of a flow regime identification system and prediction of volume fractions in three-phase systems using gamma-rays and artificial neural network[J]. Applied Radiation and Isotopes, 2021, 169: 109552.
5	LIU Weiling, TAN Chao, DONG Feng. Doppler spectrum analysis and flow pattern identification of oil-water two-phase flow using dual-modality sensor[J]. Flow Measurement and Instrumentation, 2021, 77: 101861.
6	ZHAI Lusheng, WANG Yuqing, YANG Jie, et al. Visualization of vertical oil-water-gas flows using conductance compensated wire-mesh sensor[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 71: 7500516.
7	WANG Qiang, WANG Mi, WEI Kent, et al. Visualization of gas-oil-water flow in horizontal pipeline using dual-modality electrical tomographic systems[J]. IEEE Sensors Journal, 2017, 17(24): 8146-8156.
8	LIANG Fachun, HANG Yue, YU Hao, et al. Identification of gas-liquid two-phase flow patterns in a horizontal pipe based on ultrasonic echoes and RBF neural network[J]. Flow Measurement and Instrumentation, 2021, 79: 101960.
9	SHI Xuewei, DONG Feng, TAN Chao. Horizontal oil-water two-phase flow characterization and identification with pulse-wave ultrasonic Doppler technique[J]. Chemical Engineering Science, 2021, 246: 117015.
10	张立峰, 王智. 基于多域特征提取的气液两相流流型识别[J]. 计量学报, 2023, 44(10): 1509-1516.
	ZHANG Lifeng, WANG Zhi. Gas-liquid two-phase flow pattern recognition based on multi-domain feature extraction[J]. Acta Metrologica Sinica, 2023, 44(10): 1509-1516.
11	WANG Z Y, JIN N D, GAO Z K, et al. Nonlinear dynamical analysis of large diameter vertical upward oil-gas-water three-phase flow pattern characteristics[J]. Chemical Engineering Science, 2010, 65(18): 5226-5236.
12	SUN Bo, CHANG He, ZHOU Yunlong. Flow regime recognition and dynamic characteristics analysis of air-water flow in horizontal channel under nonlinear oscillation based on multi-scale entropy[J]. Entropy, 2019, 21(7): 667.
13	周云龙, 王圣博, 刘起超. 基于ICEEMDAN和SVM的起伏振动气液两相流流型识别[J]. 热能动力工程, 2024, 39(2): 109-116.
	ZHOU Yunlong, WANG Shengbo, LIU Qichao. Flow pattern identification of fluctuating vibration gas-liquid two-phase flow based on ICEEMDAN and SVM[J]. Journal of Engineering for Thermal Energy and Power, 2024, 39(2): 109-116.
14	XU Qiang, LI Xiangyu, JIANG Shuaizhi, et al. Features selection for recognition of severe slugging in a long pipeline with an S-shaped riser by decision tree[J]. Flow Measurement and Instrumentation, 2024, 96: 102537.
15	QUINTINO André Mendes, NAVARRO DA ROCHA Davi Lôtfi Lavôr, FONSECA Júnior Roberto, et al. Flow pattern transition in pipes using data-driven and physics-informed machine learning[J]. Journal of Fluids Engineering, 2021, 143(3): 031401.
16	LI Chaofan, SONG Yajing, XU Long, et al. Prediction of the interfacial disturbance wave velocity in vertical upward gas-liquid annular flow via ensemble learning[J]. Energy, 2022, 242: 122990.
17	苏茜, 夏志飞, 刘振兴. 基于RBF的油气水段塞流流型超声识别方法[J]. 化工进展, 2024, 43(2): 628-636.
	SU Qian, XIA Zhifei, LIU Zhenxing. Ultrasound recognition method for flow patterns in oil-gas-water slug flow based on RBF neural network[J]. Chemical Industry and Engineering Progress, 2024, 43(2): 628-636.
18	AÇIKGÖZ M, FRANÇA F, LAHEY JR R T. An experimental study of three-phase flow regimes[J]. International Journal of Multiphase Flow, 1992, 18(3): 327-336.
19	WEGMANN Adrian, MELKE Julia, RUDOLF VON ROHR Philipp. Three phase liquid-liquid-gas flows in 5.6mm and 7mm inner diameter pipes[J]. International Journal of Multiphase Flow, 2007, 33(5): 484-497.
20	MUKHERJEE Tanumoy, Gargi DAS, Subhabrata RAY. Sensor-based flow pattern detection gas-liquid-liquid upflow through a vertical pipe[J]. AIChE Journal, 2014, 60(9): 3362-3375.
21	GAO Zhongke, JIN Ningde. Nonlinear characterization of oil-gas-water three-phase flow in complex networks[J]. Chemical Engineering Science, 2011, 66(12): 2660-2671.
22	GAO Zhongke, DU Meng, HU Lidan, et al. Visibility graphs from experimental three-phase flow for characterizing dynamic flow behavior[J]. International Journal of Modern Physics C, 2012, 23(10): 1250069.
23	LI Zhao, TAN Chao, ZHANG Shumei, et al. Global-local state analysis and monitoring-based velocity measurement of oil-gas-water three-phase flow[J]. Chemical Engineering Journal, 2024, 497: 154759.
24	SPEDDING P L, DONNELLY G F, COLE J S. Three phase oil-water-gas horizontal co-current flow Ⅰ. Experimental and regime map[J]. Chemical Engineering Research and Design, 2005, 83(4): 401-411.
25	ZHANG Lifeng, WANG Zhi, WU Sicheng. Gas-liquid flow behavior analysis based on phase-amplitude coupling and ERT[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 4502410.
26	KINSLER Lawrence E, FREY Austin R, COPPENS Alan B, SANDERS James V. Fundamentals of acoustics[M]. 4th ed. New York: John Wiley & Sons Inc., 2000.
27	张俊哲. 无损检测技术及其应用[M]. 2版. 北京: 科学出版社, 2010.
	ZHANG Junzhe. None-destructive testing technology and applications[M]. 2nd ed. Beijing: Science Press, 2010.
28	DONG Xiaoxiao, TAN Chao, DONG Feng. Gas-liquid two-phase flow velocity measurement with continuous wave ultrasonic Doppler and conductance sensor[J]. IEEE Transactions on Instrumentation and Measurement, 2017, 66(11): 3064-3076.
29	SHI Xuewei, TAN Chao, WU Hao, et al. An electrical and ultrasonic Doppler system for industrial multiphase flow measurement[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 70: 7500313.
30	TRALLERO J L, SARICA Cem, BRILL J P. A study of oil-water flow patterns in horizontal pipes[J]. SPE Production & Facilities, 1997, 12(3): 165-172.
31	茆诗松, 程依明, 濮晓龙. 概率论与数理统计教程[M]. 3版. 北京: 高等教育出版社, 2020.
	MAO Shisong, CHENG Yiming, PU Xiaolong. Probability and mathematical statistics tutorial[M]. 3rd ed. Beijing: Higher Education Press, 2020.
32	WU Zhaohua, HUANG Norden E. Ensemble empirical mode decomposition: A noise-assisted data analysis method[J]. Advances in Adaptive Data Analysis, 2009, 1(1): 1-41.
33	陈思睿, 毕景良, 王雷, 等. 气液两相流流型特征无监督提取的卷积自编码器: 机理及应用[J]. 化工学报, 2024, 75(3): 847-857.
	CHEN Sirui, BI Jingliang, WANG Lei, et al. Unsupervised-feature extraction of gas-liquid two-phase flow pattern based on convolutional autoencoder: Principle and application[J]. CIESC Journal, 2024, 75(3): 847-857.
34	HE Haikang, ZHOU Ziqiang, SUN Baojiang, et al. Study on the prediction method of oil-water two-phase flow pattern and oil holdup[J]. Geoenergy Science and Engineering, 2025, 246: 213627.

[1]	郭伟, 刘传平, 童莉葛, 王立. 新型热扩散式测量技术助力气液多相流监测[J]. 化工进展, 2025, 44(4): 1781-1785.
[2]	苏茜, 白凡, 刘振兴, 刘彰. 基于XGBoost的气液两相流流型超声识别方法[J]. 化工进展, 2025, 44(4): 1786-1793.
[3]	李凌涵, 张淑美, 董峰. 少样本场景下的气液两相流动状态识别[J]. 化工进展, 2025, 44(4): 1794-1805.
[4]	陈诺恒, 王胜南, 孔明. 基于多频电容的气固相含率在线检测电路设计[J]. 化工进展, 2025, 44(4): 1806-1814.
[5]	孙铭聪, 覃晴, 王彦晗, 赵宁, 闫晓丽. 基于集成学习的垂直管环状流界面波速预测模型[J]. 化工进展, 2025, 44(4): 1849-1858.
[6]	王艳, 冯致, 张正阳, 吴昊, 张文宇, 杨露露, 张文硕, 禹芹芹, 刘维, 王进卿, 孔明. 基于LED离轴数字全息的液滴蒸发过程三维形貌测量方法[J]. 化工进展, 2025, 44(4): 1867-1875.
[7]	赵天楠, 赵畅, 孙昊, 陆建民, 杨荟楠. 基于吸收光谱技术的冻结液滴高度测量系统[J]. 化工进展, 2025, 44(4): 1907-1912.
[8]	王昊, 马柳昊, 杜建国, 周晨, 王玮, 王伟, 王宇. 基于频分复用激光吸收光谱技术的高湿烟气中痕量甲烷-氨双元燃料逃逸测量[J]. 化工进展, 2025, 44(4): 1913-1922.
[9]	邹藻, 田昌, 苏明旭, 尹华模, 屈延阳, 何冠松. 基于改进Swin Transformer的HMX造型粉图像处理方法[J]. 化工进展, 2025, 44(4): 1957-1967.
[10]	岳磊, 栗培龙, 丁湛, 夏雷, 安琳玉. 沥青再生剂扩散行为表征方法研究进展[J]. 化工进展, 2025, 44(4): 2068-2080.
[11]	薛立新, 董永平, 陈梦瑶, 高从堦. 十二烷基硫酸钠（SDS）和强碱（NaOH）对聚酰胺复合纳滤膜的协同调控机理[J]. 化工进展, 2025, 44(4): 2225-2237.
[12]	李家豪, 范海明, 魏志毅, 程思远. 纳米材料在低渗透油藏中的研究进展及展望[J]. 化工进展, 2025, 44(3): 1485-1495.
[13]	陈可欣, 李熙, 常福城, 武萧衣, 娄嘉诚, 李会雄. 螺旋管内水-水蒸气两相流压降及流型转变特性[J]. 化工进展, 2025, 44(2): 613-624.
[14]	王雪莉, 杨卫亚, 张会成, 王少军, 凌凤香. 金属有机框架（MOF）基混合基质膜界面改性方法及其气体分离性能[J]. 化工进展, 2025, 44(2): 928-940.
[15]	张晓方, 甘汶, 纪之骄, 许明, 李初福, 何广利. 电化学氮还原合成氨电解质利用现状与调控策略[J]. 化工进展, 2025, 44(2): 809-819.