Summary

Optimizing Brillouin Optical Time-Domain Analyzers Based on Gain Spectrum Engineering

Published: May 11, 2020
doi:

Summary

A protocol for Brillouin optical time-domain analyzers based on gain spectrum engineering is presented. Enhancements in the sensing performance, including sensing range and measurand resolution are achieved and the excess Brillouin intensity noise is studied. The protocol introduces a new way to enhance distributed Brillouin sensing performance.

Abstract

Demonstrated is a unique method for sensing performance enhancement in Brillouin optical time-domain analyzers (BOTDA). A Brillouin gain spectrum (BGS) is superimposed with two symmetric Brillouin loss spectra (BLS). This leads to a complex engineered spectrum shape that is more resistant to the sensing system noise. Instead of only one pump and probe interaction as in the conventional BOTDA setup, three optical probe waves are exploited, with one probe located in the BGS and the other two symmetrically in the BLS. Due to the resistance and insensitivity of the engineered spectrum shape to the noise, the sensing performance is enhanced by 60% and the measurand resolution is doubled.

Introduction

Distributed fiber sensing (DFS) is a unique mechanism that employs a whole fiber as a sensing medium. It has attracted a lot of interest due to the low fiber loss; small size; and the ability to be easily embedded in various structures, such as dams, bridges, and buildings, to perform environment surveillance as an artificial nerve system. In comparison to applying numerous traditional point sensors, such as fiber Bragg gratings (FBG), it provides a more efficient and cost-effective solution in a wide range of large-scale sensing tasks, such as infrastructure and structural health monitoring1.

Current distributed sensors exploit different scattering mechanisms inside the fiber to measure temperature and strain distribution. Among them, DFS based on Brillouin scattering is the most attractive due to the striking advantages of the stimulated Brillouin scattering (SBS), such as high signal-to-noise ratio (SNR), low threshold, and the sensitivity to both temperature2 and strain3. SBS can be classically described as an interaction between the incident optical continuous waves (CW), i.e., the pump, and the counter-propagating CW probe wave via an acoustic wave. According to the conservation of energy and momentum, the probe wave is frequency downshifted to the pump. This shift is called Brillouin frequency shift (BFS). Considering the finite lifetime of a 10 ns acoustic wave, there is a finite spectral distribution of the refracted wave, also called Brillouin gain spectrum (BGS), in which the BFS is the frequency difference between the pump wave and the peak center frequency. The interaction between the waves leads to a frequency down-shifted gain region and a frequency up-shifted loss region where the probe wave gets amplified and attenuated, respectively. For a standard single mode fiber (SSMF) in C-Band, the BFS is approximately 11 GHz and the BGS has a Lorentzian shape with an ultra-narrow full-width at half maximum (FWHM) of 10-30 MHz, which can be further reduced to 3.4 MHz with specific techniques4,5,6,7. Based on these characteristics, SBS can also be applied in microwave photonics filters8,9,10, optical filters11, slow and fast light12,13,14, and high resolution optical spectroscopy7,15.

One of the most promising SBS applications is distributed Brillouin sensing. These sensors exploit the BFS dependence on temperature and strain. The first to be demonstrated was the Brillouin optical time-domain analyzer (BOTDA)16, which is the most consolidated time-domain distributed Brillouin sensing technique. It differs from the conventional CW-SBS interaction in that it exploits the SBS interaction between a pulsed pump wave and a probe CW so that the environmental information is locally interrogated on every fiber section. The pump or probe frequency is usually fixed while the probe or the pump frequency is scanned in the vicinity of the BFS. The probe power is recorded for BGS reconstruction and the BFS is ideally the peak frequency of the local BGS at each fiber section. However, due to the inevitable system noise, the BGS peak is usually ambiguous and a fitting algorithm has to be applied17, which leads to a certain estimation error in frequency18 and influences the measurand resolution.

Statistically, the BFS estimation error is inversely proportional to the system signal-to-noise ratio (SNR). The most straightforward way to enhance the SNR is to increase the pump and probe power. However, these are limited by modulation instability (MI)19 and non-local effects (NLE)20,21 to ~20 dBm and -14 dBm, respectively. Numerous techniques, such as coding22 and Raman based inline-amplification23 have been proposed to break these limits. Recently, it has been reported that this frequency error can be minimized by choosing a proper fitting algorithm24. Relatedly, measurements exploiting the Brillouin phase and a linear fitting algorithm are also reported to have a reduced frequency error25, which indicates the potential of a well-engineered BGS to sensing performance enhancement. Another option to enhance SNR is noise reduction. However, according to the traditional point of view, the sensing system noise comes mainly from the detector (i.e., common-mode noise, including dark noise, shot noise, etc.)26,27 and improvement is less likely.

The basic idea of this paper is to engineer the BGS by the superposition of a conventional BGS with two symmetric Brillouin loss spectra (BLS) (see Figure 1). In comparison to a conventional BGS spectrum, which follows a Lorentzian shape, the engineered spectrum is sharper and more robust with the same level of system noise. Thus, the noise has less influence on the determination of the peak frequency. This can be verified by collecting and fitting the BGS measurement data a statistically significant number of times. Because of this better resistance to the noise, sensing performance enhancements are achieved, including the sensing range by 60% and doubled measurand resolution, i.e., a 50% reduced frequency error. Due to the involvement of the measurement with Brillouin loss interaction in part of the engineered BGS, a direct comparison of the trace noise with and without Brillouin interaction is made. Owing to the circumvention of the excess Brillouin noise, the trace with the engineered BGS is much clearer.

Figure 1
Figure 1: Schematic of an engineered BGS by the superposition of one Brillouin gain and two symmetric Brillouin loss spectra. Please click here to view a larger version of this figure.

Protocol

1. Selecting optimized parameters for the spectrum engineering via simulation Model the engineered BGS gSBS(ν,z) with the equations28,29 as implemented by, for example, the supplemental MATLAB script. NOTE: Here, G(ν) is the complex gain coefficient, calculated in the script as G_complex within the SB…

Representative Results

Figure 3 shows the simulation results. Points with η < 1 in Figure 3A indicate a smaller frequency error (higher measurand resolution) with the engineered BGS. The lower the value was, the bigger the advantage. The minimum ratio was at m = 1, indicating that a multiprobe instead of multipump scheme can be carried out (see Discussion). Figure 3B</str…

Discussion

The most critical step during the experiment is the equalization of the three probe powers so that m = 1 and symmetry between the two Brillouin loss spectra is achieved. Besides the separate power check using the power meter at Cir port 2, as presented in steps 4.9 and 4.10, the power equalization can be more precisely checked in the digitizer. By setting the RF 1 frequency to ~11 GHz (the fiber BFS) and switching off EDFA 3, the conventional trace with the peak gain can be recorded in the digitizer (trace I). T…

Disclosures

The authors have nothing to disclose.

Acknowledgements

Cheng Feng wishes to acknowledge the financial support from German Research Foundation (SCHN 716/13-1, 716/15-2, 716/18-1, 716/26-1) and Niedersächsisches Vorab (NL-4 Project "QUANOMET").

Materials

Current controller for laser diode ILX Lightwave LDX3220
Digitizer Acqiris SA U5309A-1039
Erbium doped fiber amplifier 1 Photop PTEDFA-A-PA-C-SCH-15
Erbium doped fiber amplifier 2 LiComm OFA-TCH
Erbium doped fiber amplifier 3 Calmar Optcom AMP-ST30
Erbium doped fiber amplifier 4 Photop PTEDFA-A-PA-C-SCH-15
Fiber Bragg grating 1 Advanced Optics Solutions T-FBG
Fiber Bragg grating 2 Advanced Optics Solutions T-FBG
Fiber under test ofs
Isolator General Photonics S-15-NTSS
Laser diode 3SP Group A1905 LMI
Mach-Zehnder modulator 1 Avanex IM10
Mach-Zehnder modulator 2 Avanex IM10
Mach-Zehnder modulator 3 Avanex IM10
Nanosecond driving board for semiconductor optical amplifier Highland Technology T160-9 (28A160-9C)
Optical coupler 10:90 Newport Benchtop coupler/WDM
Optical coupler 50:50 Newport Benchtop coupler/WDM
Optical spectrum analyzer Hewlett Packard 86145A
Optical switch 1 JDSU SN12-1075NC
Photodiode Thorlabs D400FC
Polarization scrambler General Photonics PSY-101
Pulase generator Hewlett Packard 8082A
Radio function generator 1 Anritsu MG3692C
Radio function generator 2 Agilent Technology E8257D
Radio function generator 3 HTM T2100
Semiconductor optical amplifier Thorlabs SOA1013SXS
Temperature controller for laser diode ILX Lightwave LDT5948
Temperature controller for semiconductor optical amplifier Tektronix TED200
Variable optical attenuator JDSU mVOA-A1 With optical switch function

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Cite This Article
Feng, C., Schneider, T. Optimizing Brillouin Optical Time-Domain Analyzers Based on Gain Spectrum Engineering. J. Vis. Exp. (159), e61115, doi:10.3791/61115 (2020).

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