Optical tomography provides a means for the determination of the spatial distribution of materials with different optical density in a volume by non-intrusive means. This paper presents results of concentration measurements of gas bubbles in a water column using an optical tomography system. A hydraulic flow rig is used to generate vertical air-water two-phase flows with controllable bubble flow rate. Two approaches are investigated. The first aims to obtain an average gas concentration at the measurement section, the second aims to obtain a gas distribution profile by using tomographic imaging. A hybrid back-projection algorithm is used to calculate concentration profiles from measured sensor values to provide a tomographic image of the measurement cross-section. The algorithm combines the characteristic of an optical sensor as a hard field sensor and the linear back projection algorithm.
This research investigates the use of charge coupled device (abbreviated as CCD) linear image sensors in an optical tomographic instrumentation system used for sizing particles. The measurement system, consisting of four CCD linear image sensors are configured around an octagonal shaped flow pipe for a four projections system is explained. The four linear image sensors provide 2,048 pixel imaging with a pixel size of 14 micron × 14 micron, hence constituting a high-resolution system. Image reconstruction for a four-projection optical tomography system is also discussed, where a simple optical model is used to relate attenuation due to variations in optical density, [R], within the measurement section. Expressed in matrix form this represents the forward problem in tomography [S] [R] = [M]. In practice, measurements [M] are used to estimate the optical density distribution by solving the inverse problem [R] = [S](-1)[M]. Direct inversion of the sensitivity matrix, [S], is not possible and two approximations are considered and compared-the transpose and the pseudo inverse sensitivity matrices.
The data distribution system of this project is divided into two types, which are a Two-PC Image Reconstruction System and a Two-PC Velocity Measurement System. Each data distribution system is investigated to see whether the results' refreshing rate of the corresponding measurement can be greater than the rate obtained by using a single computer in the same measurement system for each application. Each system has its own flow control protocol for controlling how data is distributed within the system in order to speed up the data processing time. This can be done if two PCs work in parallel. The challenge of this project is to define the data flow process and critical timing during data packaging, transferring and extracting in between PCs. If a single computer is used as a data processing unit, a longer time is needed to produce a measurement result. This insufficient real-time result will cause problems in a feedback control process when applying the system in industrial plants. To increase the refreshing rate of the measurement result, an investigation on a data distribution system is performed to replace the existing data processing unit.