A Dynamic Calibration of Optical Fiber DTS Measurements Using PEST and Reference Thermometers

Abstract

Temperature measurements are widely used in structural health monitoring. Optical fiber distributed temperature sensors (DTS) are developed, based on Raman spectroscopy, to measure temperature with relatively high accuracy and short temporal and spatial resolutions. DTS systems provide an extensive number of temperature measurements along the entire length of an optical fiber that can be extended to tens of kilometers. The efficiency of the temperature measurement strongly depends on the calibration of the DTS data. Although DTS systems internally calibrate the data, manual calibration techniques were developed to achieve more accurate results. Manual calibration employs reference sections or points with known temperatures and the DTS scattering data to estimate the calibration parameters and calculate temperature along the optical fiber. In some applications, manual calibration is subjected to some shortages, based on the proposed fiber installation configuration and continuity of calibration. In this article, the manual calibration approach was developed using the model-independent Parameters Estimation (PEST), together with the external temperature sensors as references for the DTS system. The proposed method improved manual calibration in terms of installation configuration, continuity of dynamic calibration, and estimation of the calibration parameters.

Calibration and Uncertainty Quantification for Single-Ended Raman-Based Distributed Temperature Sensing: Case Study in a 800 m Deep Coaxial Borehole Heat Exchanger

“…The authors conclude that explicit calculation of calibration parameters leads to the best precision and accuracy. They also admit that this is challenging to achieve for field installations since at least two baths must be maintained at different temperature levels, which is especially demanding for longterm installations [46]. For the best calibration method, Hausner et al report mean RMSEs of 0.131 K and 0.108 K for a lab and a field case study, respectively.…”

“…In particular, changing ambient temperature may lead to some disturbances in the internal oven of the DTS instrument used for the manufacturer's calibration. Hence, the need for dynamic calibration is highlighted in the literature [46].…”

“…a dynamic calibration with at least three different calibrated sections as suggested in [39] -e.g. for logistics constraints [37,40,46].…”

Calibration and Uncertainty Quantification for Single-Ended Raman-Based Distributed Temperature Sensing: Case Study in a 800 m Deep Coaxial Borehole Heat Exchanger

“…The authors conclude that explicit calculation of calibration parameters leads to the best precision and accuracy. They also admit that this is challenging to achieve for field installations since at least two baths must be maintained at different temperature levels, which is especially demanding for long-term installations [ 53 ]. For the best calibration method, Hausner et al report mean RMSEs of 0.131 K and 0.108 K for a laboratory and a field case study, respectively.…”

“…In particular, changing ambient temperature may lead to some disturbances in the internal oven of the DTS instrument used for the manufacturer’s calibration. Hence, the need for dynamic calibration is highlighted in the literature [ 53 ].…”