Landweber iterative algorithm based on regularization in electromagnetic tomography for multiphase flow measurement

For multiphase flow that contains conductive or magnetic permeable material, it is possible to use an electromagnetic tomography technique to measure its flow rate and phase density. The main challenge of this kind of measurement is how to improve the image reconstruction quality. In this paper the comparison of linear back project, Landweber iterative and Tikhonov regularization algorithms are studied for an electromagnetic tomography system. Then an improved method of the Landweber iterative is introduced which uses a Tikhonov regularization reconstruction image as the initial iterative value for the iterative. Compared with the original Landweber iterative using a linear back project result as the initial value, this method can improve the quality of the reconstructed image. Moreover, the convergence speed of the iterative can be improved by using this method. The effectiveness of this method is verified by simulation reconstruction.

► New Landweber iterative algorithm realized in electromagnetic tomography (EMT).
► Tikhonov regularization result is as the initial iterative value of the iterative.
► The comparison between this algorithm and others shows its performance improvement.
► Excitation frequency optimization and measurement data analyses are introduced.