Improving the Metrological Characteristics of a Fiber-Optic Temperature Sensor by Effective Signal Processing Methods

Abstract

Signal processing in a fiber optic temperature sensor has a major impact on the metrological performance of the instrument. Therefore, continuous improvement of the signal processing algorithm is an important aspect of remaining competitive. Using a fiber-optic temperature sensor based on the Raman effect manufactured by Keepline LLC, it is shown how the application of effective signal processing methods can significantly reduce the instrument error. A fiber 8258 m long was used as a sensitive element, the spatial resolution of the instrument was 2 m. It is found that the noise in the signal is distributed according to the normal law. Measurements were made at instrument temperatures of 25.95 and 44.73 °C. Using linear regression analysis, it was found that heating the instrument causes a slope of the thermogram, which needs to be corrected. A logarithmic function was used to correct the thermogram. Thus, it was possible to reduce the range of temperature values along the length of the fiber from 3.47 to 2.35 °C, and RMS from 0.579 to 0.392 °C. In addition, the dependence of the transient process on the heating of the instrument is given and recommendations for adjusting the calibration coefficients are provided

This work was supported by the Russian Foundation for Basic Research, project no. 20-08-00321

Please cite this article in English as:

Ershov I.A. Improving the metrological characteristics of a fiber-optic temperature sensor by effective signal processing methods. Herald of the Bauman Moscow State Technical University, Series Instrument Engineering, 2022, no. 2 (139), pp. 112--125 (in Russ.). DOI: https://doi.org/10.18698/0236-3933-2022-2-112-125

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