Flow Pattern Identification of Porous Media Based on Signal Feature Extraction and SVM

被引：0

作者：

Li, Xiangyu ^{[1
]}

Li, Liangxing ^{[1
]}

Wang, Wenjie ^{[1
]}

Yang, Xiaoming ^{[2
]}

Ma, Rubing ^{[2
]}

Yuan, Yidan ^{[2
]}

Ma, Weimin ^{[3
]}

机构：

[1] State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an,710049, China

[2] China Nuclear Power Engineering Co Ltd., Beijing,100840, China

[3] Royal Institute of Technology (KTH), Stockholm,10691, Sweden

来源：

Kung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics | 2022年 / 43卷 / 11期

关键词：

Flow patterns - Frequency domain analysis - High speed cameras - Porous materials - Probability density function - Spectral density - Time domain analysis - Two phase flow;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In this paper, the visualization experiment of gas-liquid two-phase flow in porous media is carried out. The typical flow patterns of bubbly flow, slug flow and annular flow are photographed by high-speed camera, and the corresponding differential pressure fluctuation signals are measured and recorded, Using probability density function (PDF) and power spectral density (PSD) curves, the time-domain and frequency-domain characteristics of differential pressure signals corresponding to each flow pattern are analyzed, and the quantitative characteristic parameters are introduced to construct the characteristic vector reflecting the time-frequency characteristics of differential pressure signals. A two-phase flow pattern identification method in porous media based on support vector machine (SVM) is proposed. The results show that the overall recognition rate of the three flow patterns measured by the method is 98.18%, which can provide a new technical support for the on-line recognition of gas-liquid two-phase flow patterns in porous media. © 2022, Science Press. All right reserved.

引用

页码：2957 / 2965