Section
Biological Sciences
Abstract
In measuring component fraction in multiphase flows using tomographic techniques, it is desirable to use a high speed tomography system capable of generating 100 tomograms per second. The electrical capacitance tomography system in this regard is considered to be the best among the available tomographic techniques. However, due to its inherent limitations the system generates distorted reconstructed tomograms necessitating the use of extra signal processing techniques such as thresholding to minimize these distortions. Whilst thresholding technique has been effective in minimizing distortions, the additional computation associated with the process limits the speed of tomogram generation desired from the system. Further, the accuracy of the techniques is limited to higher ranges of the full component fraction range. However, since its performance can be influenced by the nature of the quantization process required a priori, optimal quantization parameters can be found and used to improve performance. In this article the influence of quantization resolution and its rate on the performance of global entropic thresholding algorithms have been investigated. Measurement of gas volume component fraction in a multiphase flow of gas/liquid mixture using electrical capacitance tomography system has been used for evaluation using simulated and online capacitance measurement data. Results show that an optimal quantizer resolution is flow regime dependent. Higher resolutions are optimal for annular flow and vice versa for stratified flow regimes. Also, higher resolution significantly minimizes the dependency of the thresholding algorithm on the object to be searched, thereby reducing complexity of designing a thresholder. Overall, the optimal quantization resolution is 256.
Recommended Citation
Mwambela, A. J.
(2005)
"The influence of quantization process on the performance of global entropic thresholding algorithms using electrical capacitance tomography data,"
Tanzania Journal of Science: Vol. 31:
Iss.
2, Article 31.
Available at:https://doi.org/10.65085/2507-7961.2020