Frequency-comb-based BOTDA sensors for high-spatial-resolution/long-distance sensing.

A Brillouin optical time-domain analysis (BOTDA) sensor that combines the conventional complementary coding with the pulse prepump technique for high-accuracy and long-range distributed sensing is implemented and analyzed. The employment of the complementary coding provides an enhanced signal-to-noise ratio (SNR) of the sensing system and an extended sensing distance, and the measurement time is also reduced compared with a BOTDA sensor using linear coding. The combination of pulse prepump technique enables the establishment of a preactivated acoustic field in each pump pulse of the complementary codeword, which ensures measurements of high spatial resolution and high frequency accuracy. The feasibility of the prepumped complementary coding is analyzed theoretically and experimentally. The experiments are carried out beyond 50-km single-mode fiber, and experimental results show the capabilities of the proposed scheme to achieve 1-m spatial resolution with temperature and strain resolutions equal to ∼1.6°C and ∼32 μϵ, and 2-m spatial resolution with temperature and strain resolutions equal to ∼0.3°C and ∼6 μϵ, respectively. A longer sensing distance with the same spatial resolution and measurement accuracy can be achieved through increasing the code length of the prepumped complementary code.

We propose and experimentally demonstrate the use of principal component analysis (PCA) based pattern recognition to extract temperature distribution from the measured Brillouin gain spectra (BGSs) along the fiber under test (FUT) obtained by Brillouin optical time domain analysis (BOTDA) system. The proposed scheme employs a reference database consisting of relevant ideal BGSs with known temperature attributes. PCA is then applied to the BGSs in the reference database as well as to the measured BGSs so as to reduce their size by extracting their most significant features. Now, for each feature vector of the measured BGS, we determine its best match in the reference database comprised of numerous reduced-size feature vectors of the ideal BGSs. The known temperature attribute corresponding to the best-matched BGS in the reference database is then taken as the extracted temperature of the measured BGS. We analyzed the performance of PCA-based pattern recognition algorithm in detail and compared it with that of curve fitting method. The experimental results validate that the proposed technique can provide better accuracy, faster processing speed and larger noise tolerance for the measured BGSs. Therefore, the proposed PCA-based pattern recognition algorithm can be considered as an attractive method for extracting temperature distributions along the fiber in BOTDA sensors.

This study explores the effectiveness of various noise reduction filters in accurately measuring temperature distributions over a 38.2 km single-mode fiber (SMF). Brillouin optical time-domain analysis (BOTDA) sensor is utilized to gather Brillouin gain spectra (BGSs), which are denoised using bilateral filter (BF), guided filter (GF), adaptive Wiener filter (AWF), non-local means filter (NLMF), average filter (AF) and disc filter (DF). The temperature distributions over the SMF are then determined by applying least-squares curve fitting (LSCF). The study assesses the efficacy of noise reduction filters considering signal-to-noise ratio (SNR), uncertainty in temperature measurement (UTM), experimental spatial resolution (ESR) and signal processing speed (SPS). Among six different filters, NLMF outperforms other filters which can provide SNR improvement of 10.22 dB for which the UTM can be improved by 58.93% without deteriorating the ESR of the sensor. The noise reduction using such filter can also provide 6.2% faster SPS. Therefore, NLMF can be considered as an effective noise reduction filter for the precise temperature measurement using BOTDA sensors. DUJASE Vol. 8 (1) 42-50, 2023 (January)

Distributed fiber-optic sensors employ the conventional fiber as the sensing medium and allow all locations along the optical fiber to be measured simultaneously. Thus the sensing scheme provides an efficient way of simultaneously achieving multi-points sensing with a convenient and low-cost configuration. One of the most popular technologies that enables distributed sensing is based on Brillouin scattering. Characteristics of Brillouin scattering are determined mostly by the material properties of the optical fiber and the Brillouin Frequency Shift (BFS) has linear dependence on both the temperature and strain of the fiber under test (FUT). Based on this principle, intensive research efforts have been made in distributed Brillouin fiber sensors during the past two decades. Among them, Brillouin Optical Time-Domain Analysis (BOTDA) has attracted intensive research interest due to its promising properties for temperature and strain monitoring. In BOTDA the local Brillouin Gain Spectrum (BGS) is reconstructed by scanning the frequency offset of a continuous wave and an optical pulse around BFS when they are counter-propagating inside FUT, and the local BFS and hence the temperature and/ or strain information are retrieved accordingly. Usually curve fitting techniques are employed in determining the BFSs of the measured BGSs along the FUT, in which the measured BGS is fitted using an ideal curve and the BFS is found to be the frequency with the peak gain on the fitted curve. Fitting techniques using different lineshape for ideal curves, e.g. Lorentzian curve fitting (LCF), Gaussian curve fitting (GCF), pseudo-Voigt curve fitting (pVCF), and quadratic curve fitting (QCF) have been used to find the BFS distribution along FUT. However, the curve fitting techniques require careful initialization of model parameters and as many data points as possible collected on the measured BGS to ensure the fitting accuracy, otherwise the accuracy in BFS determination will degrade significantly. In addition, long processing time is needed for the iteration of fitting algorithms to find the BFS, especially when the sensing distance is long with a large number of BGSs collected and processed. Recently we have utilized the nonlinear mapping capability of Artificial Neural Network (ANN) in a BOTDA system and has successfully extracted temperature distribution from the measured BGSs along the FUT. Before temperature extraction ANN is trained to acquire the knowledge about the BGS patterns under different temperatures, thus it allows better accuracy even if the data points on the collected BGS become fewer when large frequency scanning step is adopted during the acquisition of BGSs. Moreover, the processing speed of ANN for temperature extraction is much faster than that of curving fitting techniques. In this presentation, we will review our work on using ANN for temperature extraction in a BOTDA system. Different idea spectrum profiles are used for training ANN, and the corresponding performances are compared with those using conventional curve fitting techniques. Some potential applications using ANN in BOTDA are also discussed. We believe that ANN can be an attractive tool for direct temperature or strain extraction in BOTDA system at high accuracy and fast speed.

Non-local effects have been traditionally identified as one of the most limiting factors of the performance of Brillouin optical time-domain analyzers. These phenomena, directly linked with the energy gained/lost by the pump pulse, limit the probe power and ultimately the SNR of the system. Severa l solutions have been proposed, although none offers the possibility to increase the probe power until its limit, the onset of amplified spontaneous Brillouin scattering. In this work, we propose a technique th at avoids non-local effects and permits to set the probe power at its maximum, reaching a 100 km sensing distance with 2 meter resolution. Keywords: Brillouin distributed sensors, Brillouin scattering, nonlinear optics, fiber optic sensors. 1. INTRODUCTION Brillouin Optical Time Domain Analysis (BOTDA), a consolidated long-range distributed fiber optic sensing technique, traditionally uses a Dual-Probe-Sideband (DSB) modulation scheme 1 , which turns the system to be highly robust against pump depletion and non-local effects compared to a Single Sideband (SSB) probe wave configuration

We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy.

We have used distributed Raman amplification to extend the measurement distance of a Brillouin Optical Time-Domain Analysis (BOTDA) sensor. We successfully demonstrate a dynamic range of 75 km with 2 meter spatial resolution.

We propose and demonstrate the use of spatial multiplexing as a means to reduce the costs of distributed sensing networks. We propose a new scheme in which remote power-by-light switching is deployed to scan multiple branches of a distributed sensing network based on Brillouin Optical Time Domain Analysis (BOTDA) sensors. A proof-of-concept system is assembled with two 5-km sensor fiber branches that are alternatively monitored using a fast remotely controlled and optically powered optical switch. The multiplexed distributed sensor fibers were located 10 km away from the interrogation unit and a Raman pump is used to remotely power the switch. Furthermore, the deployed BOTDA unit uses an alternative configuration that can lead to simplified setups.

We propose and experimentally demonstrate a Brillouin Optical Time Domain Analysis sensor combining adaptive linear prediction with cyclic pulse coding for fast and accurate strain measurement over 10km standard singlemode fiber with meter-scale spatial resolution.

We demonstrate a technique to compensate the nonlocal effects that appear in Brillouin optical time-domain analysis sensors when pump pulses with limited extinction ratio are deployed. These recently discovered nonlocal effects are originated in the interaction between the probe wave and the pulse pedestal. Hence, their compensation method is based on deploying a modulation (dithering) of the optical frequency of the probe and pulse pedestal waves that provides a reduction of the effective interaction length between them. This is implemented by taking advantage of the chirp associated to the direct current modulation of a semiconductor laser used as common source for both waves. The net effect of this procedure is that the probe and pulse pedestal waves display efficient Brillouin interaction just at correlation peaks along the fiber where the frequency difference between both waves remains constant. Proof-of-concept experiments in a 25-km sensing link demonstrate the performance of the technique, where large errors of more than 10 MHz in the measurement of the Brillouin frequency shift are completely compensated by introducing a sinusoidal dithering to the laser source.

The robustness of a recently proposed Brillouin optical time-domain analysis sensor based on dual-tone probe wave with fixed frequency separation is deeply studied. It is discovered that when the distribution of Brillouin frequency shift (BFS) along the sensing fiber is not entirely uniform, non-local effect might be imposed at the middle of sensing fiber, which gives rise to systematic frequency error on the local estimated BFS. Aiming at solving this problem, we propose an approach that acquires both the upper and lower probe sidebands simultaneously using two photodiodes, and the average between the Brillouin gain and loss spectral is calculated to eliminate the detrimental impact of the non-local effect. Moreover, the impact of probe power on the distortions of both pump pulse and Brillouin gain/loss spectrum is experimentally investigated, thus the maximum allowable power of the injection probe wave is determined.

Support vector machine (SVM) based differential pulse-width pair Brillouin optical time domain analyzer (DPP-BOTDA) has been proposed and experimentally demonstrated. With only one SVM model, temperature distribution along 5 km fiber under test has been successfully extracted from differential Brillouin gain spectrum (BGS) measured under different spatial resolution in DPP-BOTDA. The temperature accuracy by SVM is better than that by Lorentzian curve fitting (LCF), especially when the pump pulse width difference and the number of trace averaging used in the measurement are small, indicating larger tolerance of SVM to high spatial resolution and low signal-to-noise ratio. SVM is also more robust to a wide range of frequency scanning steps and has less accuracy degradation under large frequency scanning step. To extract temperature from 50 000 differential BGSs, 133.17 and 1.12 s are consumed by SVM-0.1 and SVM-1 °C, respectively, both of which are much shorter than that by LCF. The data processing time of SVM is further shortened with the help of principle component analysis for data dimension reduction. SVM for measurand extraction would be especially helpful in the scenario of DPP-BOTDA where high data sampling rate is required to resolve plenty of submeter scale sensing points.

The key operation of traditional Brillouin optical time-domain analysis (BOTDA) is the frequency-sweeping process to get the distributed Brillouin gain spectrum (BGS) whose central frequency (i.e. Brillouin frequency shift, BFS) has a linear relationship with the environmental information (e.g. temperature or strain) over the sensing fiber. However, this time-consuming process has limited the sampling rate of BOTDA. In this paper, we summarize several fast BOTDA systems for dynamic strain measurement which is developed by our team and refers to frequency-agile technique, slope-assisted methods and optical chirp chain technique.

Appearance of micrometer size surface cracks is common in structural elements such as welded connections, beams, and gusset plates in bridges. Brillouin scattering-based sensors are capable of making distributed strain measurements. Pre-pump-pulse Brillouin optical time domain analysis (PPP-BOTDA) provides a centimeter-level spatial resolution, which facilitates detection and monitoring of the cracks. In the work described here, in addition to the shift in Brillouin frequency (distributed strains), change in the Brillouin gain spectrum (BGS) width is investigated for the detection and monitoring of surface micro-cracks. A theoretical analysis was undertaken in order to verify the rationality of the proposed method. The theoretical approach involved simulation of strain within a segment of the optical fiber traversing a crack and use of the simulated strain distribution in the opto-mechanical relations in order to numerically obtain the change in the BGS. Simulations revealed that the increase in crack opening displacements is associated with increase in BGS width and decrease in its peak power. Experimental results also indicated that the increases in crack opening displacements are accompanied with increases in BGS widths. However, it will be difficult to use the decrease in BGS power peak as another indicator due to practical difficulties in establishing generalized power amplitude in all the experiments. The study indicated that, in combination with the shift in Brillouin frequency, the increase in BGS width will provide a strong tool for detection and monitoring of surface micro-crack growths.

The dependence of Brillouin linewidth and peak frequency on lightwave state of polarization (SOP) due to fiber inhomogeneity in single mode fiber (SMF) is investigated by using Brillouin optical time domain analysis (BOTDA) system. Theoretical analysis shows fiber inhomogeneity leads to fiber birefringence and sound velocity variation, both of which can cause the broadening and asymmetry of the Brillouin gain spectrum (BGS) and thus contribute to the variation of Brillouin linewidth and peak frequency with lightwave SOP. Due to fiber inhomogeneity both in lateral profile and longitudinal direction, the measured BGS is the superposition of several spectrum components with different peak frequencies within the interaction length. When pump or probe SOP changes, both the peak Brillouin gain and the overlapping area of the optical and acoustic mode profile that determine the peak efficiency of each spectrum component vary within the interaction length, which further changes the linewidth and peak frequency of the superimposed BGS. The SOP dependence of Brillouin linewidth and peak frequency was experimentally demonstrated and quantified by measuring the spectrum asymmetric factor and fitting obtained effective peak frequency respectively via BOTDA system on standard step-index SMF-28 fiber. Experimental results show that on this fiber the Brillouin spectrum asymmetric factor and effective peak frequency vary in the range of 2% and 0.06MHz respectively over distance with orthogonal probe input SOPs. Experimental results also show that in distributed fiber Brillouin sensing, polarization scrambler (PS) can be used to reduce the SOP dependence of Brillouin linewidth and peak frequency caused by fiber inhomogeneity in lateral profile, however it maintains the effects caused by fiber inhomogeneity in longitudinal direction. In the case of non-ideal polarization scrambling using practical PS, the fluctuation of effective Brillouin peak frequency caused by fiber inhomogeneity provides another limit of sensing frequency resolution of distributed fiber Brillouin sensor.