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 capability of a technique to reconstruct a tomographic image of flaws existence on gas pipeline via reverse ultrasonic tomography is presented. The ultrasonic tomography system is developed to monitor flaws circumferentially on pipeline with contactless measurement of distance from sensors to the pipe. In oil and gas industry, the applications of ultrasonic tomography technique for flaw detection in pipeline are limited as this technology is still in its infancy. The design of the ultrasonic tomography system consists of ultrasonic sensing system, data acquisition and image reconstruction system. A reflection mode of ultrasonic sensor is used where the output ultrasonic signal reflected from the pipe to the sensor is acquired. The collected data will be used in image reconstruction system to visualize the image. In image reconstruction process, a linear back projection algorithm is used in order to reconstruct the image of the pipe profile with flaws existence. The back projection algorithm is derived by the mathematical relationship of forward and inverse problem. This reconstruction algorithm is implemented in Matlab software to analyze the performance of the technique for different projection and arrays. Through the simulated result, the reconstructed image based on four projections is found to be less smeared compared to the image based on two projections. The effect of aliasing on the image is also reduced as the number of projection is increased. Several images of pipe with flaws existence are reconstructed based on four projections, with 7 x 7 arrays of pixels and twenty-eight of ultrasonic sensors.
Currently, an extractive green palm oil-based emulsion liquid membrane (ELM) has been used for simultaneous extraction and enrichment of Reactive Red 3BS from simulated synthetic dye wastewater. The ELM consists of two main phases, which are organic liquid membrane (LM) and stripping solution. During the extraction process, the ELM was dispersed into the simulated synthetic dye wastewater containing the Reactive Red 3BS complexes. The organic LM contains tridodecylamine (TDA), Sorbitan Monooleate (Span 80) and palm oil as a carrier, surfactant and diluent, respectively. The sodium bicarbonate (NaHCO) was used as stripping solution for the enrichment process. Several important parameters that affected the simultaneous extraction and enrichment of Reactive Red 3BS, such as carrier and stripping agent concentrations, extraction time and treat ratio, were investigated. The results showed that almost 90% of Reactive Red 3BS ions were successfully extracted with 10 times enrichment in the stripping phase at the optimum conditions of 0.2 M TDA, 0.1 M NaHCO, 5 min of extraction time and 1:5 of treat ratio. Hence, it can be concluded that palm oil possesses a high potential as green diluent in future technology, especially in ELM process for the removal and recovery of Reactive Red 3BS from synthetic dye wastewater.
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