RAHMAT, Mohd F. (1996). Instrumentation of particle conveying using electrical charge tomography. Doctoral, Sheffield Hallam University (United Kingdom)..
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10700907.pdf - Accepted Version
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10700907.pdf - Accepted Version
Available under License All rights reserved.
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Abstract
This thesis presents an investigation into the application of electrodynamic sensors to a tomographic imaging system. Several sensing mechanisms for measurement using non-intrusive techniques are discussed and their relevance to pneumatic conveying considered. Electrical charge tomography systems are shown to be worthy of investigation. Electrodynamic sensors are inherently low cost and simple in concept. This sensor is used to detect the inherent charge on dry, moving solids. Models are developed to predict the sensitivity of circular and rectangular electrodes. The spatial filtering effect of these sensors is investigated. Cross correlation is briefly reviewed and a software program is presented and tested. For tomographic imaging the forward problem for the individual sensors is modelled, used to solve the inverse problem and derive the linear back projection and filtered back projection algorithms.The design of the electronic circuitry which forms the transducer is presented. The gravity drop flow rig is described and the relationship between sand flow and plastic bead flow relative to the flow indicator setting determined. The dual 16-channel sensor array measurement section is described. Flow models are developed and used to predict the relative output voltage profiles expected from the sensor arrays.The linearity and frequency bandwidth of the sensor electronics is measured. The effect of sensor size on sensitivity and spatial filtering are investigated for circular and rectangular electrodes.Estimates of the solid concentration of flowing particles are made using individual sensors. Concentration profiles are generated and compared with predicted values. Peripheral velocities of the flowing material are determined from transit times calculated by cross correlation of upstream and downstream sensor signals.Concentration profiles are calculated using linear back projection and filtered back projection algorithms from data measured by the sensor arrays. Velocity profiles are obtained by cross correlation of upstream and downstream pixel concentration values. Estimates of the mass flow rate are obtained by combining concentration and velocity profiles.Suggestions for further work on electrodynamic sensors and tomographic measurements are made.
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