A multiresolution reconstructive algorithm based on network theory for electrical capacitance tomography

The electrical capacitance tomography technique reconstructs the dielectric constant distribution in an object by measuring the capacitances between the electrode pairs which are mounted around the object. Because of the limitations of measurement conditions, the measured data are incomplete. The paper describes a multiresolution reconstructive algorithm which is based on network theory for the electrical capacitance tomography technique. The dielectric constant distribution of the flow of two kinds of components in a pipeline is reconstructed. The algorithm is as follows. Firstly, construct a rough, first level system model. The region to be reconstructed is divided into larger units. After some iteration, the dielectric constant of each unit can be reconstructed. Secondly, construct a finer, second level system model. The initial dielectric constant of each unit in the second level is related to the first level. After iteration, the image of the cross section of the pipeline can be obtained. The simulation results show that this algorithm is effective and promising.