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Multi-parameter Electromagnetic Tomography Based on Multi-source Information |
ZHANG WEN-biao,ZHENG Xiao-yuan |
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China |
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Abstract Electromagnetic tomography technology (EMT) has become the hot topic in the field of industrial process tomography. However, the existing EMT uses the single detection signal to visualize the distributions of conductivity or permeability separately. A multi-parameter EMT method based on multi-source information is presented. As shown in simulation results, conductivity and permeability distribution imaging is realized by using the information of magnetic flux intensity and mutual inductance respectively. By calculating the root mean square error and the correlation coefficient of the reconstructed image, it is found that the quality of the reconstructed image is improved when the number of coils and magneto resistive sensors increases from 8 to 12. Through the threshold segmentation and RGB model, the image fusion of conductivity and permeability distributions is realized. By using the complementary characteristics of fused images, the quality of reconstructed images can be improved and the flow pattern ofgas-iquid-solid three-phase flow can be visualized, which proves the feasibility of multi-parameter EMT method based on multi-source information.
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Received: 26 January 2021
Published: 13 January 2023
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Fund:Beijing Natural Science Foundation;Fundamental Research Funds for the Central Universities |
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