Iliya Tizhe Thuku

Determination of Concentration Profile for Flowing Solid Particles in Pipeline Using Electric Charge Tomography System

Tomography aims to present an image of a cross-sectional distribution of materials in some regions of interest such as cross-section of a pipeline or process vessel. This paper presents the concentration profiles of solid particles across a conveying pipeline obtained using tomographic imaging. In the paper, 16 electrodynamic sensors were installed around the circumference of a pipeline to capture electric charges carried by the particles moving through the pipeline under gravity. The Cartesian coordinate system used to derive the system equation gave an accurate charge distribution while the meshing technique of the finite element method applied miniaturized the pixel sizes within the sensing zone. The problem of unstable matrix and weak signal response around the center of the pipe cross-section, normally associated with the electric charge tomography system, was addressed using matrix compression through transposition and filtering. The pro rata distribution method mostly applied in the financial accounting analysis was used in the final stage. An algorithm for realization of the concepts was developed using MATLAB. The qualities of the resulting images for four different flow regimes provide good quality images representing the distribution of the particles across the pipeline cross-section.

Particles flow identification in pipeline using adaptive network-based fuzzy inference system and electrodynamic sensors

Purpose – An identification model for materials flow through a pipeline is presented in this paper. The development of the model involves fuzzy C-means clustering, in which different flow regimes can be identified by every adaptive network-based fuzzy inference system (ANFIS). The paper aims to discuss these issues. Design/methodology/approach – For experimentation, 16 electrodynamic sensors were used to monitor and measure the charge carried by dense particles flow through a pipeline in a vertical gravity flow rig system. Four ANFIS models were also used simultaneously to provide the expected output on thresh-holding and were evaluated for ten different flow regimes, which produced satisfactory results at high flow rate. Findings – The observations made on the four ANFIS models in the flow identification experimentation (in ten different flow regimes) have shown convincing and satisfactory results at high-flow rate of the particles. Originality/value – Electrodynamic sensors have shown strong sensing cap...

Sensitivity characteristics of electrostatic sensor using finite element modeling

Electrostatic sensor detects the electric charge carried by dry particle in a pneumatic conveyor. Sensitivity characteristics of the Electrostatic sensor play an important role to design a flow measurement system. In this study, the sensitivity features of the ring shape electrodes are simulated to find the effect of electrode geometry on sensor sensitivity. Ansys Maxwell 14.0 is utilized as an electric field simulator to measure the amount of induced electrical charge from a particle to the sensor electrode in a 3D environment using finite-element analysis. The results precisely show the sensitivity characteristics between electrodes with different thickness, axial length and diameter.