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...

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Bibliographic Details
Published inThe 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP 2012) pp. 611 - 616
Main Authors Lari, V. A., Shabaninia, F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2012
Subjects
Electron tubes
Fluid flow measurement
Fluids
Measurement uncertainty
Software
Training
Vibrations
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Summary: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.
ISBN:9781467314787
1467314781
DOI:10.1109/AISP.2012.6313818