الفهرس 
BACKGROUND AND AIMSOnly 14 pages are availabe for public view
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Abstract
Electrical Impedance Tomography (EIT) is a new technique for industrial imaging that can be
used to visualize the runtime changes of impedance entire along a pipeline to measure the
industrial continuous processes of flow velocity profile distribution. This thesis presents a full
three-dimensional (3D) pipeline sensing strategy that considers the 3D nature of the EIT
sensing field. The proposed strategy includes a new 3D sensing system and an implementation
of the fast-forward solver using Finite Element Modelling (FEM). In this work, we have two
different techniques of image reconstruction inverse solver. The implementation of the onestep Gauss-Newton solver reconstruction inverse solution algorithm is introduced first, and
then the implementation of the Graz consensus reconstruction algorithm for the EIT (GREIT)
solver reconstruction inverse solution algorithm is introduced. A comparative analysis is
applied by using these algorithms for image reconstruction. The evaluation of the results of
both techniques is introduced also. An application of correlation coefficient function R and the
structure deviation function structural similarity index metric (SSIM (X, Y)) are chosen to
evaluate the image quality under different signal-to-noise ratio (SNR) values. The
reconstructed centred images obtained by the EIT system for the object moves from the
upstream sensing section to the downstream sensing section on the surface of the pipeline
are also introduced. By extracting and analyzing impedance information for industrial
properties, this study aims to make this tool an additional method with high sensitivity and
specificity for industrial processes. this study aims to improve the 3D resolution of tomograms
used in EIT pipeline imaging as well as dynamic flow visualization and velocimetry
measurements.the techniques of measurement of pipeline multiphase flows are dealt with
and thus, better processing guidance.