基于小波包和支持向量机的ERT系统流型识别  

Flow Regime Identification of Electrical Resistance Tomography System Based on Wavelet Packet and Support Vector Machine

作　　者：张华[1] 刘玥波[1] 

机构地区：[1]吉林建筑工程学院城建学院计算机科学与工程系,长春130011

出　　处：《吉林建筑工程学院学报》2012年第1期83-85,共3页Journal of Jilin Architectural and Civil Engineering

基　　金：吉林省教育厅"十一五"科学技术研究项目(吉教科合字2010第503号)

摘　　要：两相流体具有复杂的流动特性,流型的准确识别是两相流参数准确测量的基础,是两相流研究的重点内容之一.本文首先采用小波包分析方法对ERT系统中的测量数据进行特征提取,然后将提取的特征数据输入支持向量机多类分类模型,对两相流的4种流型进行识别.仿真实验证明小波包分析和支持向量机的结合是两相流流型识别领域的一种有效方法.Two-phase fluid has complex flow characteristic,accurate identification of flow regime is the foundation of measuring two-phase flow＇s parameter accurately and an important role of two-phase flow research.First,wavelet packet analysis is adopted to extract the feature of the electrical resistance tomography system.Then the extracted feature data is taken as input information of the support vector machine multi-class classifier,so the four kinds of two-phase flow regime can be identified.Experiment simulation analysis proved the wavelet packet analysis and support vector machine is an effective method of two-phase flow regime identification.

关 键 词：电阻层析成像 流型识别 小波包 支持向量机 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]