Measurement accuracy enhancement with multi-event detection using the deep learning approach in Raman distributed temperature sensors

Datta, A and Raj, V and Sankar, V and Kalyani, S and Srinivasan, B (2021) Measurement accuracy enhancement with multi-event detection using the deep learning approach in Raman distributed temperature sensors. Optics Express, 29 (17). pp. 26745-26764. ISSN 10944087

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Abstract

In this work, we present a novel deep learning framework for multi-event detection with enhanced measurement accuracy from the measured data of a Raman Optical Time Domain Reflectometer (Raman-OTDR). We demonstrate the utility of a deep learning-based approach by comparing the results from three popular neural networks, i.e. vanilla recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU). Before feeding the experimentally obtained data to the neural network, we sanitize our data through a correlation filtering operation to suppress outlier noise spikes. Based on experiments with Raman-OTDR traces consisting of single temperature event, we show that the GRU is able to provide better performance compared to RNN and LSTM models. Specifically, a bidirectional-GRU (bi-GRU) architecture is found to outperform other architectures owing to its use of data from both previous as well as later time steps. Although this feature is similar to that used recently in one dimension convolutional neural network (1D-CNN), the bi-GRU is found to be more effective in providing enhanced measurement accuracy while maintaining good spatial resolution. We also propose and demonstrate a threshold-based algorithm for accurate and fast estimation of multiple events. We demonstrate a 4x improvement in the spatial resolution compared to post-processing using conventional total variational denoising (TVD) filters, while the temperature accuracy is maintained within ± 0.5 oC of the set temperature.

Item Type:	Article
Uncontrolled Keywords:	Measurement accuracy, Raman Optical Time Domain Reflectometer (Raman-OTDR), Recurrent neural network (RNN), Long short-term memory (LSTM), Gated recurrent unit (GRU)
Subjects:	PHYSICS > Optics PHYSICS > Physics of Elementary Particles and Fields
Depositing User:	Mrs. Usha Kumari
Date Deposited:	18 May 2022 14:01
Last Modified:	18 May 2022 14:01
URI:	http://nal-ir.nal.res.in/id/eprint/13558

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