Image Reconstruction Algorithm Based on Kalman Filter for Electrical Capacitance Tomography

Abstract

ECT (Electrical Capacitance Tomography) is a kind of tomography technology. In ECT, capacitance values of the pair of electrodes around the object are measured, according to which permittivity distribution of the object can be computed, and spatial distribution inside of the object can be obtained. Because of some advantages such as non-intrusion, widely usage, safe, fast response, simple structure and so on, ECT is mainly used for detection of multiphase-flow in industrial pipeline. However, because of the limitations of ECT system, the precision of image reconstruction in electrical capacitance tomography system has been greatly restricted. So the successful application of ECT depends on the speed and precise of image reconstruction. In this paper, 12-electrode ECT system is studied. Based on in-depth analysis of different image reconstruction algorithms, federated Kalman filter is applied in local filtering for several reconstructed images. Local filters works in parallel, the filtering results will be comprehensively and processed orderly by the global filter, and the global optimal state estimation will be obtained. The experiment results show that applying Kalman filter in ECT system on Image fusion, there are advantages such as small calculation, convenient, flexible. Compared with the images according to other image reconstruction methods, the precise of reconstructed image is are improved in laminar flow, core flow and multi-trickle flow, which supports a good idea for practice of ECT system.