Design and optimisation of electromagnetic flowmeter for conductive liquids and its calibration based on neural networks

Abstract

Using Faraday's Law of electromagnetic induction, electromagnetic flowmeters are used to measure the industrial process flow rate of fluids. In these devices, the windings around the pipe are designed to produce the required magnetic field, and electrodes that are mounted on two sides of the pipe wall are used to measure the induced voltage in proportion to the liquid flow rate. The design and optimisation of an electromagnetic flowmeter for conductive liquids are presented. In this respect, a two-dimensional mathematical model with a finite difference (FD) numerical solution approach is used for calculation of the electric potential difference between the electrodes. The basic concepts of the electromagnetic flowmeter design and simulation are presented using m-file programming in Matlab software. Then, with respect to the fact that fluid flow depends on two variables, liquid level and the conductivity coefficient of the liquid and pipe bed, a three-layer neural network is used for accurate calibration of the electromagnetic flowmeter. In this new approach, for a circular cross-section pipe, the correction factor used for the calibration is accurately estimated. Finally, simulation results are provided to show the accuracy of the applied technique.