Neuro-fuzzy based compensation technique for capacitive pressure sensors

Abstract

A novel Neuro-fuzzy based technique is proposed for enabling capacitive differential pressure sensors to operate in harsh environment. In the modeling, fuzzy rules are employed to create a look-up table. The ambient temperature has adverse effects on CPS output characteristic, by using this look-up table we have access to compensated value of differential pressure, Δp. A test bench is designed and implemented to data acquisition in a real environment. The experimental results are being used to verify the performance of Neuro-fuzzy based CPS model to readout differential pressure accurately in addition to compensate for the adverse effects of environmental temperature intelligently.