Distributed temperature sensing inside a 19-rod bundle

Lomperski, S.; Bremer, Nathan; Gerardi, C.

doi:10.1016/j.nucengdes.2017.05.008

Cited by 9 publications

(1 citation statement)

References 31 publications

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“…OFDR is attractive for applications that require high spatial resolution (on the order of millimeters to centimeters) over distances on the order of meters to tens of meters. For example, OFDR-based distributed sensing has been explored for monitoring strain during welding [ 2 ] and solidification [ 3 ]; temperature distributions for cryogenic applications [ 4 ] and inside catalytic reactors [ 5 ], flowing coolant loops [ 6 , 7 , 8 ], and energized transformer cores [ 9 ]; local power deposition in nuclear reactors [ 10 , 11 ]; and liquid level [ 12 , 13 ]. More recently, fiber optic sensors have been embedded into metals [ 14 , 15 , 16 , 17 ] and ceramics [ 18 , 19 ] using additive manufacturing technologies to directly monitor spatially distributed strain in harsh environments, such as those found in nuclear reactors, where fiber could be exposed to high temperatures, radiation, or chemically aggressive media.…”

Section: Introductionmentioning

confidence: 99%

Graphical Optimization of Spectral Shift Reconstructions for Optical Backscatter Reflectometry

Sweeney

Petrie

2021

Sensors

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Optical backscatter reflectometry (OBR) is an interferometric technique that can be used to measure local changes in temperature and mechanical strain based on spectral analyses of backscattered light from a singlemode optical fiber. The technique uses Fourier analyses to resolve spectra resulting from reflections occurring over a discrete region along the fiber. These spectra are cross-correlated with reference spectra to calculate the relative spectral shifts between measurements. The maximum of the cross-correlated spectra—termed quality—is a metric that quantifies the degree of correlation between the two measurements. Recently, this quality metric was incorporated into an adaptive algorithm to (1) selectively vary the reference measurement until the quality exceeds a predefined threshold and (2) calculate incremental spectral shifts that can be summed to determine the spectral shift relative to the initial reference. Using a graphical (network) framework, this effort demonstrated the optimal reconstruction of distributed OBR measurements for all sensing locations using a maximum spanning tree (MST). By allowing the reference to vary as a function of both time and sensing location, the MST and other adaptive algorithms could resolve spectral shifts at some locations, even if others can no longer be resolved.

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