Abstract
The modeling of a vibration based electromechanical mass flow sensor using an adaptive neuro-fuzzy inference system (ANFIS) has been presented to study the influence of tube material. The input parameters taken into consideration are tube material, sensor location, drive frequency, height of tube. The results show that a well trained and well tested ANFIS model has the capability to predict the performance of mass flow sensor under varying operational conditions depending on the availability of the data and can be used as an alternative to the physical models in the sense that the results can be produced in a fast and cost effective way. The performance of the model in regions where deficiency of data exists has been discussed.
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