A Resonant Pressure Sensor Capable of Temperature Compensation with Least Squares Support Vector Machine

Abstract

Resonant pressure sensors are widely used in pressure monitoring due to high accuracies, long-term stabilities and quasi-digital outputs, which, however, suffers from the key issue of temperature drifts. This paper presents a resonant pressure sensor capable of temperature compensation leveraging the compensation algorithm of least squares support vector machine. Double “H” type resonators were arranged in a differential output pressure sensor where the pressure under measurement was translated to resonant frequency output. In comparison to two conventional algorithms which are support vector machine and polynomial fitting, the new algorithm based on least squares support vector machine can effectively improve the precision of temperature compensation for the developed micro sensors. Experimental results showed that the maximum temperature drift was reduced from 8901.4 Pa (without compensation) to 2.0 Pa (with compensation) in the full temperature and pressure scale (temperature range of −40°C to 70°C and pressure range of 20 kPa to 260 kPa), validating the effectiveness of the new algorithm in temperature compensation.