Abstract

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 °C at the sensing distance of 10.4 km.

Highlights

  • Since temperature was demodulated successfully by Raman backscattering over an optical fiber in 1985 [1], the Raman distributed temperature system (RDTS) has attracted interest for decades

  • 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]

  • The two demodulation ways are called as dual-demodulation method, and both need two avalanche photodiodes (APD) and two amplifiers, which means higher cost and larger measurement error caused by the modal dispersion between the two different backscattering lights

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Summary

Introduction

Since temperature was demodulated successfully by Raman backscattering over an optical fiber in 1985 [1], the Raman distributed temperature system (RDTS) has attracted interest for decades. Self-demodulation avoids a way of noise compared with the dual-demodulation and improves the signal to noise ratio, so the method attracts lots of attention This auto-correction method utilizes reflected anti-Stokes Raman scattering [10] and a double-ended distributed temperature sensor [11]. By combining the dynamic noise difference algorithm with the WTMM method in self-demodulation RDTS, the influence of modal dispersion for temperature accuracy is eliminated, and the sensing distance and temperature accuracy are improved in the experiment. It will not affect the system measurement time

Self-demodulation method
Dynamic difference noise algorithm
Wavelet transform and modulus maximum de-noising
C da a2
Experimental setup
Sensing distance lengthened by using dynamic noise difference algorithm
Temperature fluctuation decreased by WTMM de-noising
Measurement results
Conclusions

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