The development and application of a real-time electrical resistance tomography system.
This dissertation focuses on the application of tomography in the sugar milling process, specifically within the vacuum pan. The research aims to improve the efficiency and throughput of a sugar mill by producing real-time images of the boiling dynamic in the pan and hence can be used as a diagnostic tool. The real-time tomography system is a combination of ruggedized data collecting hardware, a switching circuit and software algorithms. The system described in this dissertation uses 16 electrodes and estimates images based on the distinct differences in conductivities to be found in the vacuum pan, i.e. a conductive syrup-like fluid (massecuite) and bubbles. There is a direct correlation between the bubbles produced during the boiling process and heat transfer in the pan. From this correlation one can determine how well the pan is operating. The system has been developed in order to monitor specific parts of a pan for optimal boiling. A binary reconstructed image identifies either massecuite or water vapour. Each image is reconstructed using a modified neighbourhood data collection method and a back projection algorithm. The data collection and image reconstruction take place simultaneously, making it possible to generate images in real-time. Each image frame is reconstructed at approximately 1.1 frames per second. Most of the system was developed in LabVIEW, with some added external drive electronics, and functions seamlessly. The tomography system is LAN enabled hence measurements are initiated through a remote PC on the same network and the reconstructed images are streamed to the user. The laboratory results demonstrate that it is possible to generate tomographic images from bubbles vs massecuite, tap water and deionized water in real-time.