A New Electrical Capacitance Tomography Method Using Online Pressure and Temperature Data Measurements

In this paper, a new formulation of the Electrical Capacitance Tomography (ECT) problem for real-time image reconstruction of the multiphase flow fluid passing through a given section of a pipeline is presented. The suggested Regularized Constrained Gauss-Newton (RCGN) algorithm determines the dielectric distribution of the internal fluid by solving the inverse and forward problems on the data captured from both the electrical electrodes surrounding the pipeline and the pressure and temperature sensors distributed at different locations of the target process. By measuring the pressure and temperature at different locations of the target, an estimation of its density distribution is performed using its fluid mechanic properties. Experimental results on a set of different images clearly show that the proposed method achieves more accurate results than the traditional methods which use only boundary electrodes, while keeping the computation time almost same.