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油水两相流电阻层析成像系统流型的辨识
引用本文:陈德运,张华,朱波,于晓洋,张健沛. 油水两相流电阻层析成像系统流型的辨识[J]. 电机与控制学报, 2007, 11(6): 639-643
作者姓名:陈德运  张华  朱波  于晓洋  张健沛
作者单位:哈尔滨理工大学,计算机科学与技术学院,黑龙江,哈尔滨,150080;哈尔滨工程大学,计算机科学与技术学院,黑龙江,哈尔滨,150001;哈尔滨理工大学,计算机科学与技术学院,黑龙江,哈尔滨,150080;哈尔滨工程大学,计算机科学与技术学院,黑龙江,哈尔滨,150001
基金项目:国家自然科学基金 , 教育部科学技术研究项目 , 黑龙江省自然科学基金
摘    要:两相流体具有复杂的流动特性,流型的准确辨识是两相流参数准确测量的基础,流型的在线智能辨识是两相流研究的重点内容之一.以电阻层析成像(ERT)系统和油/水两相流的流型为研究基础,采用主成分分析方法对ERT系统中的边界测量电压数据进行特征提取,然后以提取的特征数据作为基于一对余类策略的支持向量机多类分类模型的输入,从而对两相流的四种流型进行识别.通过实验仿真分析,四种流型的平均识别率达到了88.75%,说明主成分分析和支持向量机的结合是一种两相流流型辨识的有效方法.

关 键 词:电阻层析成像  流型辨识  主成分分析  支持向量机
文章编号:1007-449X(2007)06-0639-05
收稿时间:2007-07-03
修稿时间:2007-07-03

Flow regime identification for oil/water two flows electrical resistance tomography system
CHEN De-yun,ZHANG Hua,ZHU Bo,YU Xiao-yang,ZHANG Jian-pei. Flow regime identification for oil/water two flows electrical resistance tomography system[J]. Electric Machines and Control, 2007, 11(6): 639-643
Authors:CHEN De-yun  ZHANG Hua  ZHU Bo  YU Xiao-yang  ZHANG Jian-pei
Abstract:Two-phase fluid has complex flow characteristic,accurate identification of flow regime is the foundation of measuring two-phase flow's parameter accurately.As a result,the onvline intelligent identification of flow regime is an important role of two-phase flow research.The research in this paper is based on electrical resistance tomography system and flow regime of oil-water two-phase flow.First,principal component analysis is adopted to extract the feature of the border measurement voltage data of the electrical resistance tomography system,then the extracted feature data is taken as input information of the support vector machine multi-class classifier which is based on one to all strategy,so the four kinds of two-phase flow regime can be identified.Through the experiment simulation analysis,the four kinds of flow regime's average recognition rate is up to 88.75%.It can be concluded that the combination of principal component analysis and support vector machine is an effective method of two-phase flow regime identification.
Keywords:electrical resistance tomography   flow regime identification   principal component analysis  support vector machine
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