Graphical Optimization of Spectral Shift Reconstructions for Optical Backscatter Reflectometry

Sweeney, Daniel C.; Sweeney, Dennis M.; Petrie, Christian M.

doi:10.3390/s21186154

Graphical Optimization of Spectral Shift Reconstructions for Optical Backscatter Reflectometry

Journal Article · Tue Sep 14 00:00:00 EDT 2021 · Sensors

DOI:https://doi.org/10.3390/s21186154· OSTI ID:1819989

; Sweeney, Dennis M.;

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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Sponsoring Organization:: USDOE Office of Nuclear Energy (NE)

OSTI ID:: 1819989

Alternate ID(s):: OSTI ID: 1820805

Journal Information:: Sensors, Journal Name: Sensors Journal Issue: 18 Vol. 21; ISSN SENSC9; ISSN 1424-8220

Publisher:: MDPI AGCopyright Statement

Country of Publication:: Switzerland

Language:: English

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