Flow Pattern Identification of EMT Based on Signal Sparseness

doi:10.12068/j.issn.1005-3026.2016.01.003

Abstract

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

CLC Number:

TP391.4

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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