Research on temperature drift mechanism and compensation method of silicon piezoresistive pressure sensors

Abstract

Silicon piezoresistive pressure sensors have played a key role in the detection field due to their small size, high sensitivity, and high integration. However, the factors such as its material particularity, the temperature dependence of the piezoresistive coefficient, the variation of carrier motion in the material caused by heat-induced stress, doping concentration, and resistance mismatch may cause the sensor to generate temperature drift. In this paper, the mechanism of temperature drift of silicon-based pressure sensor is analyzed initially, and then a comparison between BP neural network and wavelet neural network is done, which shows the root mean square error of the wavelet neural network is much smaller than that of the BP neural network and better linearity.