Sensor Temperature Compensation Technique Simulation Based on BP Neural Network

Abstract

Innovatively, neural network function programming in the BPNN (BP neural network) tool boxes from MATLAB are applied, and data processing is done about CYJ-101 pressure sensor, and the problem of the sensor temperature compensation is solved. The paper has made the pressure sensors major sensors and temperature sensor assistant sensors, input the voltage signal from the two sensors into the established BP neural network model, and done the simulation under the NN Toolbox environment of MATLAB. From the compensation result, it has be found that the temperature interference variable effects on the pressure output identity has dropped from 22% to 1.1%,greatly improved the pressure sensor measurement precision and anti-interference ability. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2687