Teimour Tajdari

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.

Inhomogeneous mass flow rate measurement of solid particles using a single electrostatic sensor

The development of reliable, cost effective and high accuracy instrument to mass flow rate measurement is becoming increasingly important in many industries. Appropriate measurement method and design leads to improvement of pneumatic conveyors operation and process efficiency. This paper present an instrument design based on passive charge detection using a single electrostatic sensor. A time domain signal processing algorithm is developed to measurement of mass flow rate from acquired electrical charge signal. The findings is led to a low cost and high accuracy design, the experimental test results of the design shows less than ±5% error between measured mass flow rate and reference reading acquired from the manual weighing.