Gene

Quantum mechanics

Wireless sensor network

Engineering

Statistics

Materials science

Optical fiber

Robustness (evolution)

Telecommunications

Biochemistry

Calibration

Computer science

Geology

Computer network

Physics

Mathematics

Temperature measurement

Optics

Electronic engineering

Environmental science

Attenuation

Remote sensing

Chemistry

IEEE Sensors Journal

Distributed Temperature Sensing (DTS) is a technique that uses the interaction of laser pulses with silica to continuously sense temperature along the length of fiber-optic cables. The temporal and spatial resolution of DTS makes it an excellent technique for monitoring the performance of district-scale geothermal exchange borefields. A dynamic, double-ended calibration routine developed in response to site-specific challenges and constraints (i.e., more than 5 km, many splices, different fiber segments, and extended observation periods) is systematically presented and analyzed to provide novel insight on calibration considerations. Results show that different combinations of calibration baths may change calibration accuracy, and over determination in the calculation of calibration parameters provides greater accuracy. Fixing the null null null $\gamma $ null null null calibration parameter does not appreciably change accuracy but does provide a buffer against error from variations in calibration bath temperatures. Differential attenuation varied by up to 25% between discrete fiber sections and should be calculated for each array section to prevent errors generated from applying just one attenuation coefficient value for the entire fiber array. Furthermore, dynamically calculated differential attenuation may vary systematically with time and space. In a double-ended configuration, the consideration of whether the forward, reverse, or some combination of all light data is used will affect the robustness of the calibration over time. Each of these results may assist in thoughtful consideration of calibration design at future DTS installations facing similar challenges.

Dynamic Calibration for Permanent Distributed Temperature Sensing Networks