Model-based image reconstruction for electrical capacitance tomography with a prior calculated database

One of the advantages of electrical capacitance tomography (ECT) systems is that they can generate real-time images, usually 100 frames per second. To achieve both high-speed imaging and quantitative measurements of e.g. a multiphase flow is challenging. Among many image reconstruction algorithms, which have been developed for ECT, the model-based algorithm can obtain accurate estimation of the parameters for some flow regime. As an iterative method, the model-based algorithm requests to solve the forward problem in each iteration, to minimize the error between the measured capacitance and the calculated capacitance and hence minimize the error between the reconstructed image and the real distribution. This paper presents an approach to solve the forward problem in advance and use a set of saved solutions to speed up the iterative image reconstruction process. The procedure for implementing the model-based algorithm is given. Some results show that the water-in-liquid ratio (WLR) and gas volume fraction (GVF) in an oil-gas-water flow can be estimated by the proposed method.