Image Reconstruction Algorithm Based on Algebraic Neural Network for Electrical Resistance Tomography

Two-phase fluid has complex flow characteristic and the accurate identification of flow regime is the basis of the accurate measurement of two-phase flow´s parameter. There are still many defects such as low reconstruction quality and low reconstruction speed in image reconstruction algorithm because of soft field characteristic, strong nonlinear and ill-posedness of electrical resistance tomography. This paper put forward a new image reconstruction algorithm for ERT based on algebraic neural network. This algorithm transformed image reconstruction into a problem of solving strictly diagonal-dominant linear equations. Through the simulation experiment analysis, this method has characteristics such as fast convergence, low cost and small error.