High-temperature static strain langasite SAWR sensor: Temperature compensation and numerical calibration for direct strain reading

Strain sensing for extreme environments such as aerospace, power generation, and industrial applications require robust sensors capable of sustaining the targeted high-temperatures, while maintaining a stable sensor response. Current technologies face challenges regarding device or system size, complexity, operational temperature, or dynamic range. Surface acoustic wave resonator (SAWR) sensors fabricated on langasite (LGS) using Pt-alloy based electrodes are capable of withstanding temperatures up to 1000 degrees C, have a small footprint, are battery-free, and can be wirelessly interrogated, thus presenting themselves as a promising technology for harsh-environment strain sensing. This paper presents direct SAWR strain sensor readings up to 114 mu epsilon on a constant stress beam between 24 degrees C and 400 degrees C. In order to obtain the direct strain reading at high-temperature, a finite element method (FEM) numerical model was developed. The FEM model was compared to measurements performed using a room temperature commercial sensor, and revealed correlation between the measured and modeled strain data close to unity. At elevated temperatures, the SAWR frequency measurements were calibrated using the developed FEM model adapted for operation at high-temperatures, due to the absence of a reliable high -temperature static strain sensor. A temperature compensation scheme was employed to mitigate temperature-strain cross-sensitivity, and Savitzky-Golay signal processing filtering employed to improve signal detection. Ceramic Al2O3-based epoxy was used to attach the sensor to the targeted constant stress beam fixture, and -41 Hz/mu epsilon sensitivity was obtained at 400 degrees C. The sensor fabrication, calibration and measurements reported in this work illustrates the capability of LGS based SAW resonators to perform as high -temperature harsh-environment static strain sensors. (C) 2017 Elsevier B.V. All rights reserved.