This paper presents results for a tomographic system using an array of electrodynamic sensors. Sensitivity maps are derived for the individual sensors and then used by a back-projection algorithm to calculate concentration profiles from measured sensor values. Limitations in linearity over the sensing area are reduced by applying a filter to the images. The filtered back-projection algorithm is tested both on uniformly and on artificially produced non-uniformly distributed solids' flows.

This paper describes an investigation into the optimum design of optical fibre sensing arrays to be incorporated in an optical tomographic measurement system for on-line monitoring of particles and droplets. Two approaches are considered to cover opaque and transparent materials; optical path length and optical attenuation. Four flow models are investigated: single-pixel flow representing a single particle or droplet, two-pixel flow as a simple check on aliasing in the reconstructed image, half flow representing half the sensing cross section filled with material and full flow, where the whole sensing cross section is full of material. Six projection geometries of the fibre sensors are considered. For tomographic imaging, the forward problem, which assumes particles are placed in specific places in the measurement cross section and calculates voltage outputs for the individual sensors, is modelled. The solutions from the forward problem are used to solve the inverse problem, which uses actual sensor voltage readings to estimate the spatial distribution of the material in the measurement cross section. The solution of the inverse problem is used to derive the linear back projection (LBP) and filtered LBP algorithms. In order to improve image quality, a hybrid reconstruction algorithm is implemented. This algorithm first checks if any sensors read zero and sets (locks for this estimation) all pixels associated with them to zero (no material). The algorithm then proceeds as for the LBP.

This paper describes measurements made on a gravity drop conveyor using two arrays of axially spaced electrodynamic sensors to measure axial velocities close to the wall of the conveyor and velocity profiles both of flowing sand and of plastic beads. The level of correlation obtained using pixels is investigated. The velocity profile is combined with a tomographic concentration profile to estimate the mass flow profile, which is summed over the measurement cross section to estimate the mass flow rate. A calibration of the tomographically determined mass flow rate versus the actual mass flow rate is presented.

This paper describes the further development of optical sensor hardware for a process tomography system in which emitters and detectors are used to exploit the optical characteristics of multiphase flow regimes. The optical arrangement is described and the importance of fibre beam position discussed. The proportion of the measurement volume interrogated by the beams is derived. The response of a single fibre is shown followed by a reconstructed concentration profile.

This paper describes how the circuit analysis package HSPICE can be used to model an electrical resistance tomography system in two and three dimensions. Reasons for developing an HSPICE model using discrete components are introduced followed by a discussion of the theory underlying this technique. Image reconstructions using a simplified back projection algorithm are presented which simulate the movement of resistive discontinuities through an electrode plane in an attempt to investigate process flows.