Fast reconstruction of electrical resistance tomography (ERT) images based on the projected CG method

Electrical resistance tomography (ERT) is considered to be one of the most promising process tomography techniques for multi-phase flow measurement due to the advantages such as high speed, low cost and non-intrusive sensing. The image reconstruction for ERT is an inverse problem to find the conductivity distribution of an object by measuring the voltage between sets of electrodes placed around its periphery. The conjugate gradient (CG) method is one of the most popular methods applied for image reconstruction, although its convergence rate is low. In this paper, an advanced version of the CG method, namely the projected CG method, is proposed for image reconstruction of an ERT system. The solution space is projected into the Krylov subspace and the inverse problem is solved by the CG method in a low-dimensional specific subspace. Both simulation and experimental work were carried out for typical gas–water two-phase flow regimes. The flow regimes are identified according to the reconstructed images of the projected CG method and conventional methods. Results obtained indicate that the projected CG method improves the quality of the reconstructed images and dramatically reduces the computational time compared with the traditional sensitivity, Landweber, and CG methods. Therefore, the projected CG method is suitable for identification of online two-phase flow regimes.

► A projected CG method based on Krylov subspace is proposed in this paper.
► Two preconditioners are used in order to accelerate the convergence of iteration.
► The projected CG method dramatically reduces the computational complexity.
► The projected CG method achieves high reconstruction quality.
► Dynamic experiments were carried out to evaluate the projected CG method.