Error correction of a coriolis mass flow meter in two-phase flow measurment using Neuro-Fuzzy

Coriolis mass flow meters despite proper performance and precision when faced with two-phased fluids will show a remarkable attenuation in performance and accuracy depending on the condition and the amount of variation of the density of passing fluid. In these situations Neuro-Fuzzy Algorithm helps determination of the error and improves performance and also looks a better choice compared to specific transmitters according to reduction in cost. Design and simulation have been made through MATLAB software. Previous measures made in this area encompassed using Neural Network [1] that this work was based on laboratory data and evidences in that research.