Single-channel distributed Raman temperature sensing based on a 1-dimensional convolutional neural network

Renner E, Mampilli JS, Amer N, Schmauß B (2024)


Publication Language: English

Publication Type: Journal article

Publication year: 2024

Journal

Book Volume: 88

Pages Range: 104000

Article Number: 104000

DOI: 10.1016/j.yofte.2024.104000

Abstract

We present a simple and cost-efficient single-channel Raman distributed temperature sensing (DTS) system based on temperature prediction by a 1-dimensional convolutional neural network (1D-CNN) from the Raman anti-Stokes backscatter trace. The proposed Raman DTS system is based on incoherent optical frequency domain reflectometry with homodyne down-conversion with excitation of spontaneous Raman backscattering by an L-band laser diode and detection of the Raman anti-Stokes in the optical C-band. A 1D-CNN is employed to predict the spatially resolved temperature profile along the fiber from the obtained anti-Stokes backscatter trace only and thus, solves the problem of temperature referencing for single-channel Raman DTS systems. The network was trained on three different scenarios, consisting of uniform and non-uniform temperature profiles along the fiber in a temperature range from 0 °C to 60 °C. The obtained results show that the measurement and signal processing pipeline presented here is capable of predicting the temperature distribution to an accuracy of approximately 1 K in the tested scenarios.

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APA:

Renner, E., Mampilli, J.S., Amer, N., & Schmauß, B. (2024). Single-channel distributed Raman temperature sensing based on a 1-dimensional convolutional neural network. Optical Fiber Technology, 88, 104000. https://doi.org/10.1016/j.yofte.2024.104000

MLA:

Renner, Esther, et al. "Single-channel distributed Raman temperature sensing based on a 1-dimensional convolutional neural network." Optical Fiber Technology 88 (2024): 104000.

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