A specialized genetic algorithm for the electrical impedance tomography of two-phase flows

Abstract

The main objective of this work is to contribute to the development of a new tomographic reconstruction method well suited for processing signals obtained from electrical or other soft sensing field probes. The adopted approach consists in formulating the reconstruction problem in terms of an error function, which assesses the difference between a prospective and the actual internal contrast distribution (3D image), and searching for its minimum with the help of a specialized genetic algorithm (GA). Numerical simulations have been performed to demonstrate the feasibility of the proposed reconstruction method, as well as to emphasize the relation between the ill-posed nature of the problem and the topology of the minimization hyper-surface, and the importance of considering this relation when designing the numerical solution procedure. Results show that convergence is greatly enhanced when a priori information is introduced in the error function.