Robert Banasiak

Metrological evaluation of a 3D electrical capacitance tomography measurement system for two-phase flow fraction determination

The industrial diagnostic and monitoring systems still require new methods offering new possibilities of non-invasive observation and analysis of the two-phase gas–liquid mixture flows. This paper demonstrates a new measurement system dedicated for non-invasive void fraction calculation and flow structure identification in vertical and horizontal pipelines. The study of the metrological validation of the designed three-dimensional capacitance tomography measurement system is discussed here. This research includes the 3D ECT sensor structure optimization process, the metrological evaluation of the image reconstruction accuracy and the developed liquid void fraction calculation method efficiency, in comparison with other common techniques. As a result of the performed analysis the advantages of the designed 3D ECT measurement system for non-invasive real-time dynamic flow process identification were discussed.

Tunnel-based method of sensitivity matrix calculation for 3D-ECT imaging

Purpose – The purpose of this paper is to introduce a significant modification of the sensitivity maps calculation process using electric field distribution analysis. A sensitivity matrix is typically a crucial part of a deterministic image reconstruction process in a three-dimensional capacitance tomography (3D ECT) and strictly decides about a final image quality. Commonly used sensitivity matrix computation methods mostly provide acceptable results and additionally allow to perform a recalculation of sensitivity maps according to the changing permittivity distribution. Design/methodology/approach – The new “tunnel-based” algorithm is proposed which traces the surfaces constructed along the electric field lines. The new solution is developed and tested using experimental data. Findings – To fully validate the new technique both linear and non-linear image reconstruction processes were performed and the criteria of image error estimation were discussed. This paper discusses some preliminary results of th...

Magnetic Induction Tomography with High Performance GPU Implementation

Magnetic induction tomography (MIT) is a non-invasive medical imaging technique with promising applications such as brain imaging and cryosurgery monitoring. Despite its potential, the realisation of medical MIT application is challenging. The computational complexity of both the forward and inverse problems, and specific MIT hardware design are the major limitations for the development of MIT research in medical imaging. The MIT forward modeling and linear system equations for large scale matrices are computationally expensive. This paper presents the implementation of GPU (graphics processing unit) for both forward and inverse problems in MIT research. For a given MIT mesh geometry composed of 167,488 tetrahedral elements, the GPU accelerated Biot-Savart Law for solving the free space magnetic field and magnetic vector potential is proved to be over 200 times faster compared to the time consumption of a CPU (central processing unit). The linear system equation arising from the forward and inverse problem, can also be accelerated using GPU. Both simulations and experimental results are presented based on a new GPU implementation. Laboratory experimental results are shown for a phantom study representing potential cryosurgery monitoring using an MIT system.