关键词: 电阻层析成像, 图像重建算法, 修正牛顿-拉夫逊算法, 正则化因子, 粒子群算法, 惯性权重

Abstract: Aiming to improve the precision of the image reconstruction algorithm when solving the inverse problem in electrical resistance tomography，research on the regularization factor of modified-Newton-Raphson algorithm is carried out.Motivated by the idea of decreasing inertia weight used in the improved particle swarm optimization，the upper bound of the regularization factor is updated automatically according to the imaging quality during the iteration process.Hence a novel improved Newton-Raphson reconstruction algorithm is proposed and applied to image reconstruction of two-phase typical flow regimes—stratified flow，bubble flow，annular flow，core flow and compound flow.Simulation results demonstrate that，compared with iterative linear back projection algorithm and modified Newton-Raphson algorithm，the new proposed algorithm can improve the imaging accuracy effectively under the same experimental condition.

Key words: electrical resistance tomography, image reconstruction algorithm, modified-Newton-Raphson algorithm, regularization factor, particle swarm optimization, inertia weight