Impact of Loss Variations on Double-Ended Distributed Temperature Sensors Based on Raman Anti-Stokes Signal Only

Soto, Marcelo A.; Signorini, Alessandro; Nannipieri, Tiziano; Faralli, S.; Bolognini, G.; Pasquale, F. Di

doi:10.1109/jlt.2011.2174966

Cited by 45 publications

(20 citation statements)

References 15 publications

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“…Besides, the Brillouin optical time domain reflectometry (B-OTDR), measuring frequency shift of Brillouin backscattering, has recently been highly concerned for determining distributed temperature and strain over long distances [10][11][12][13]. The Raman optical time domain reflectometry (R-OTDR) or Raman distributed temperature sensor (RDTS) [14][15][16][17], exploiting avalanche photodetectors (APDs) to detect the different of Raman anti-Stokes (AS) and Stokes (S) signal induced by temperature, is widely used to measure distributed temperature with meter-scale spatial resolutions.…”

Section: Introductionmentioning

confidence: 99%

High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses

et al. 2016

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We demonstrate a cost-effective distributed fiber sensing system for the multi-parameter detection of the vibration, the temperature, and the strain by integrating phase-sensitive optical time domain reflectometry (φ-OTDR) and Brillouin optical time domain reflectometry (B-OTDR). Taking advantage of the fast changing property of the vibration and the static properties of the temperature and the strain, both the width and intensity of the laser pulses are modulated and injected into the single-mode sensing fiber proportionally, so that three concerned parameters can be extracted simultaneously by only one photo-detector and one data acquisition channel. A data processing method based on Gaussian window short time Fourier transform (G-STFT) is capable of achieving high spatial resolution in B-OTDR. The experimental results show that up to 4.8kHz vibration sensing with 3m spatial resolution at 10km standard single-mode fiber can be realized, as well as the distributed temperature and stress profiles along the same fiber with 80cm spatial resolution.

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Section: Introductionmentioning

confidence: 99%

High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses

et al. 2016

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“…Many authors have proposed different solutions in order to improve the performance of DTS systems [10][11][12][13][14][15]. However, the presented solutions generally improve either the spatial resolution or the temperature resolution, being scarce solutions to improve both simultaneously.…”

Section: Introductionmentioning

confidence: 99%

NARX neural network model for strong resolution improvement in a distributed temperature sensor

et al. 2018

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This paper proposes an approach to process the response of a distributed temperature sensor using a nonlinear autoregressive with external input neural network. The developed model is composed of three steps: extraction of characteristics, regression, and reconstruction of the signal. Such an approach is robust because it does not require knowledge of the characteristics of the signal; it has a reduction of data to be processed, resulting in a low processing time, besides the simultaneous improvement of spatial resolution and temperature. We obtain total correction of the temperature resolution and spatial resolution of 5 cm of the sensor.

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“…And the system has been widely used in the online monitoring system of underground gas pipes [2], fault diagnosis of smart grid [3], and large nuclear infrastructures [4]. There are three demodulation methods in RDTS at present: (1) Rayleigh scattering demodulates Raman anti-Stokes scattering [5], (2) Raman Stokes scattering demodulates Raman anti-Stokes scattering [6][7], and (3) Raman anti-Stokes scattering demodulates itself [8]. In the method based on Rayleigh scattering demodulating Raman anti-Stokes scattering, the ratio of the intensity of Rayleigh scattering and Raman anti-Stokes scattering is used to demodulate the temperature.…”

Section: Introductionmentioning

confidence: 99%

Performance Improvement of Raman Distributed Temperature System by Using Noise Suppression

Zhang

Liu

et al. 2017

Photonic Sens

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In Raman distributed temperature system, the key factor for performance improvement is noise suppression, which seriously affects the sensing distance and temperature accuracy. Therefore, we propose and experimentally demonstrate dynamic noise difference algorithm and wavelet transform modulus maximum (WTMM) to de-noising Raman anti-Stokes signal. Experimental results show that the sensing distance can increase from 3 km to 11.5 km and the temperature accuracy increases to 1.58 ℃ at the sensing distance of 10.4 km.

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Impact of Loss Variations on Double-Ended Distributed Temperature Sensors Based on Raman Anti-Stokes Signal Only

Cited by 45 publications

References 15 publications

High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses

High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses

NARX neural network model for strong resolution improvement in a distributed temperature sensor

Performance Improvement of Raman Distributed Temperature System by Using Noise Suppression

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