Study on image reconstruction of capacitively coupled electrical impedance tomography (CCEIT)

Abstract

The aim of this work is to study the image reconstruction of capacitively coupled electrical impedance tomography (CCEIT) by using total impedance of a gas–liquid two-phase flow. The results of image reconstruction that utilise the real part, the imaginary part, the amplitude of the impedance, and the image reconstruction results by making use of different parts of the total impedance are investigated and discussed. By combining a linear back projection (LBP) algorithm and a K-means clustering algorithm, a new image reconstruction algorithm for CCEIT is proposed. The LBP is used to obtain the original reconstructed image. The K-means is adopted to automatically obtain the gray level threshold. The final reconstructed image is acquired with an established gray level threshold filter. With the new algorithm (LBP + K-means), the images reconstructed by using different parts of the impedance are obtained. To make full use of total impedance information, an image fusion method based on the weighted combination method is presented. With a developed 12-electrode CCEIT prototype, the image reconstruction experiments are conducted. Experimental results show that all three parts of the impedance can reflect the phase distribution characteristics of the gas–liquid two-phase flow from different aspects. Image fusion results indicate that making full use of the different parts of the total impedance of the gas–liquid two-phase flow can effectively improve the quality of the image reconstruction. The experimental results also verify the feasibility and the effectiveness of the proposed new image reconstruction algorithm. Compared with conventional algorithms, the proposed image reconstruction method can obtain comparable/better image reconstruction results with less prior knowledge. The influence of manual intervention on the image reconstruction results can be effectively avoided.