基于信号稀疏性的EMT流型辨识

doi:10.12068/j.issn.1005-3026.2016.01.003

东北大学学报:自然科学版 ›› 2016, Vol. 37 ›› Issue (1): 11-14.DOI: 10.12068/j.issn.1005-3026.2016.01.003

基于信号稀疏性的EMT流型辨识

王静文，王旭

(东北大学信息科学与工程学院，辽宁沈阳110819)

收稿日期:2014-11-23 修回日期:2014-11-23 出版日期:2016-01-15 发布日期:2016-01-08
通讯作者: 王静文
作者简介:王静文 (1988-)，女，辽宁锦州人，东北大学博士研究生; 王旭(1956-)，男，辽宁沈阳人，东北大学教授，博士生导师.
基金资助:
中央高校基本科研业务费专项资金资助项目(N130404004).

Flow Pattern Identification of EMT Based on Signal Sparseness

WANG Jing-wen， WANG Xu

School of Information Science & Engineering， Northeastern University， Shenyang 110819， China.

Received:2014-11-23 Revised:2014-11-23 Online:2016-01-15 Published:2016-01-08
Contact: WANG Jing-wen
About author:-
Supported by:
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摘要/Abstract

摘要： 针对电磁层析成像流型识别率低的问题，提出基于信号稀疏性的EMT流型辨识方法.在Maxwell方程组电磁感应原理基础之上，用Comsol有限元仿真软件建立了带有8个电磁线圈的仿真模型.首先建立了几种不同流型的仿真模型并测量其电压值，将测量电压归一化后作为EMT流型辨识的判别依据；然后将其表示为稀疏性组合；最后通过信号稀疏性建立的数学模型求得最优解，从而实现流型归属.实验结果表明:本文方法能对环流、核心流等进行识别，且识别率较高，是一种值得进一步研究和推广的方法.

关键词: 电磁层析成像, 流型辨识, 信号稀疏性, 采样, 相关系数

Abstract: In view of lower recognition rate of traditional methods in flow pattern identification of electromagnetic tomography (EMT)， a flow pattern identification method of EMT was proposed based on signal sparseness. On the base of Maxwell’s electromagnetic induction equations principle，Comsol multiphysics software was used for the simulation of EMT system， which was composed of eight electromagnetic sensors. Firstly， simulation models of several flow pattern were established and the voltage values were measured， and the measurement voltages were normalized and represented as the basis of identification of electromagnetic tomography (EMT) as well.Then normalized voltage was represented as a sparse combination. Finally，the optimal solution was obtained to realize flow pattern. The experimental results show that the method can identify circulation， the core flow， etc.， and the recognition rate is higher， which is worthy of further research and extension methods.

Key words: electromagnetic tomography, flow pattern identification, signal sparseness, sampling, correlation coefficient

中图分类号:

TP391.4

王静文，王旭. 基于信号稀疏性的EMT流型辨识[J]. 东北大学学报:自然科学版, 2016, 37(1): 11-14.

WANG Jing-wen， WANG Xu. Flow Pattern Identification of EMT Based on Signal Sparseness[J]. Journal of Northeastern University Natural Science, 2016, 37(1): 11-14.

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基于信号稀疏性的EMT流型辨识

Flow Pattern Identification of EMT Based on Signal Sparseness

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