Abstract
Though impedance CT (Computed Tomography) has been developed for medical applications at first, it is attractive to apply to the measurement of time-averaged void distribution in two-phase flow, because the device is simple and easy to handle. In the impedance CT, the image of void distribution is reconstructed from current signals of electrodes set up in outer boundary of the measurement area. Therefore the point of the development is how to solve the reverse-problem.This paper describes a method based on the neural-network theory to solve this reverse-problem and its verification by comparing with experimental data.
