Electrical Impedance Tomography (ElT) has been used as a visualisation and measurement tool in many fields such as medical imaging, geophysical prospecting and industrial process applications. To date, single sensing ring strategies and two-dimensional (2D) electric field reconstruction algorithms are mostly used in ElT applications. The quality of measurement will be affected by the three-dimensional (3D) effects that cause imaging errors in both the near-sensor-region and the spatial coordination of a conventional 2D sensor. The typical errors include the object off-plane sensing and offpath trajectory effects - objects lying a short axial distance from the image plane are reconstructed closer to the central axis than their true position. There is a distinct possibility that it may also give a rise to erroneous velocity components normal to the axial direction. The aim of this thesis is to reduce the 3D effects by designing and implementing a full 3D pipeline sensing strategy which takes into account of the 3D nature of the ElT sensing field. The main approaches of the thesis are: (1) a new sensing system, the Zigzag sensor, which represents a new electrode configuration has been designed; (2) a fast forward solver, using Finite Element Modelling, has been implemented with the aim of achieving real-time processing of tomographic measurements; (3) the Sensitivity Conjugate Gradient (SCG) Algorithm has been adapted to 3D ElT for the first time. Moreover, the thesis contributes towards the application of the developed 3D ElT system for dynamic flow visualisation and velocimetry with 3D auto-correlation method which provided a balance between the requested imaging precision and computation speed. The thesis details both theoretical and experimental approaches as well as evidences that the zigzag sensor with the 3D SCG offers some advantage over conventional methods to reduce the 3D effects on ElT pipeline imaging.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:595849 |
Date | January 2013 |
Creators | Ismail, Khalid Nabil Abd Elwahed |
Publisher | University of Leeds |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
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