Multiple Compensation and Linear Fitting Demodulation for Raman Distributed Temperature Sensors

Improving the measurement accuracy of Raman distributed temperature sensors (RDTSs) in a simplified and efficient manner has always been of paramount importance. Based on the characteristics of Raman backscattered light, this article proposes a new demodulation optimization method based on multiple compensations and linear fitting, which effectively improves the measurement accuracy of RDTS. Merely describing the relationship between temperature and Raman light intensity ratio through a linearly fit relational expression does not result in high measurement accuracy. Moreover, when the system operates for a long time, the sensing curve may shift as the reference temperature rises due to the structure of the calibration module. To address these issues, we have added two techniques based on linear fitting: proportional coefficients adjustment algorithm and reference temperature offset compensation. First, we use the proportional coefficients adjustment algorithm to solve the problem of insufficient temperature response in the linear model. Then, we address the issue of sensing curve shifts through the reference temperature offset compensation model. Finally, this method has achieved great results, improving the measurement accuracy of the sensing system from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pm 7.8 \; ^{\circ }$ </tex-math></inline-formula>C to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\pm 0.8 \; ^{\circ }$ </tex-math></inline-formula>C within a 2.4 km measurement range.