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[1]梁法春,赵靖文,孟佳,等.基于语义分割的气液两相塞状流持液率测量[J].油气储运,2021,40(11):1272-1277.[doi:10.6047/j.issn.1000-8241.2021.11.010]
　LIANG Fachun,ZHAO Jingwen,MENG Jia,et al.Gas-liquid plug flow liquid holdup measurement using semantic segmentation[J].Oil & Gas Storage and Transportation,2021,40(11):1272-1277.[doi:10.6047/j.issn.1000-8241.2021.11.010]
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基于语义分割的气液两相塞状流持液率测量

《油气储运》[ISSN:1000-8241/CN:13-1093/TE] 卷: 40 期数: 2021年11期 页码: 1272-1277 栏目: 工艺与工程 出版日期: 2021-11-25
Title:
Gas-liquid plug flow liquid holdup measurement using semantic segmentation
文章编号:
1000-8241（2021）11-1272-06
作者:
梁法春1; 2; 赵靖文1; 孟佳1; 李琦瑰1; 李乃明2
1. 中国石油大学（华东）储运与建筑工程学院；2. 江苏福吉特管业有限公司
Author(s):
LIANG Fachun1; 2;  ZHAO Jingwen1;  MENG Jia1;  LI Qigui1;  LI Naiming2
1. College of Pipeline and Civil Engineering, China University of Petroleum (East China); 2. Jiangsu Forged Pipe Fittings Co. Ltd.
关键词:
油气田开发; 气液两相流; 持液率; 语义分割; 深度学习; 高速摄像; 测量
Keywords:
oil-gas field development; gas-liquid two-phase flow; liquid holdup; semantic segmentation; deep learning; high-speed camera; measurement
分类号:
TE832
DOI:
10.6047/j.issn.1000-8241.2021.11.010
文献标志码:
A
摘要:
持液率是表征气液两相流动的重要参数之一，受图像噪声干扰，传统基于图像处理的持液率 测量方法难以准确提取气液界面，导致持液率测量误差很大。为此，应用深度学习的语义分割算法， 建立基于Deeplab V3+的网络模型，并通过塞状流流型采集实验得到的图像数据集对模型进行学习 训练，进而识别并提取塞状流气、液流动区域界面，实现气液两相塞状流持液率的测量。结果表明： 语义分割模型可实现对气液两相流图像的在线提取，并可实现对气相区、液相区及背景区的精确分 割；顶部界面提取获得的持液率偏高，底部界面提取获得的持液率偏低，而平均液膜厚度对应的持 液率与采用WMS（Wire-mesh Sensors）网格成像传感器测量得到的真实持液率最为接近，最大误差 小于10％。研究成果为实现持液率的实时监测提供了新的途径。（图12， 参18）
Abstract:
Liquid holdup is one of the most important parameters of gas-liquid two-phase flow. Affected by the image noise, the traditional liquid holdup measurement method based on image processing is difficult to accurately extract the gas-liquid interface, resulting in the great error of the liquid holdup measurement. Hence, a network model based on Deeplab V3+ was established with the semantic segmentation algorithm of deep learning, which was also trained by the image data set obtained from the slug flow pattern acquisition experiment, and then the interface of the gas and liquid flow area in the slug flow was identified and extracted to realize the measurement of the liquid holdup of the gas-liquid two-phase slug flow. The results show that the semantic segmentation model can extract the images of the gas-liquid two-phase flow online, and accurately divide the gas zone, liquid zone and background zone. In addition, the liquid holdup obtained by the top interface extraction is relatively high, while that obtained by the bottom interface extraction is relatively low, but the liquid holdup obtained by the average liquid film thickness is the closest to the true value measured by WMS （Wire-mesh Sensors） grid imaging sensors, with the maximum error less than 10%. The research results provide a new way for real-time monitoring of liquid holdup. (12 Figures, 18 References)

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备注/Memo

收稿日期：2021-06-30；修回日期：2021-07-27；编辑：张静楠
基金项目：国家自然科学基金资助项目“水下油气临界分流取样计量理论及实现方法”，51574272；国家重点研发计划“临海油气管道及陆上终端设施损伤机理与演化规律研究”，2016YFC0802301。
作者简介：梁法春，男，1977 年生，教授，2006 年博士毕业于西安交通大学动力工程与工程热物理专业，现主要从事油气储运专业方向的研究工作。地址：山东省青岛市黄岛区长江西路66 号，266580。电话：0532-86981224。Email：liangfch@upc.edu.cn

更新日期/Last Update: 2021-11-25