Electrical impedance tomography (EIT) is an imaging technique for detecting the internal conductivity distribution of an object by voltage measurements taken by an exterior electrode. EIT has been researched in many different application areas in the world as a simpler, cheaper alternative to many other imaging methods. The topic of this PhD study is mainly focused on a number of key developments in both hardware and software implementation. The basic theories of EIT, including forward problem, inverse problem of EIT and the sensor design have been described. Major contributions of the thesis are in computational and experimental aspects of EIT in a wide variety of geometries. A sparse and memory efficient method has been presented to solve large scale 3D EIT problems. A parallel conjugate gradient (PCG) has been applied to demonstrate computational improvements using synthetic and experimental data. 3D EIT has been implemented for planar array geometry for limited access tomography. Furthermore, multiple frequencies with complex conductivity reconstruction are presented and applied to an EIT-based fabric pressure mapping sensor. A comparative study with traditional tank phantom is presented to provide a context for a fabric pressure mapping sensor. As the motivation for different frequency response with different conductivity inclusions, frequency difference EIT has been implemented to overcome problems of time difference EIT.
|Date of Award||13 Apr 2015|
|Supervisor||Manuchehr Soleimani (Supervisor)|