Brillouin gain spectrum manipulation using multifrequency pump and probe for slope-assisted BOTDA with wider dynamic range

We propose slope assisted Brillouin optical time domain analysis (SA-BOTDA) with virtual Brillouin gain spectrum (BGS) generated by multifrequency pump and probe. The virtual BGS having a wide linear slope region of 100 MHz is easily generated by employing time-to-space spectral shaping technique that has been originally developed for generating short optical pulses. We demonstrate the distribution of virtual BGS realized by using five spectral components of pump and probe.

Improvement of Performance for Raman Assisted BOTDR by Analyzing Brillouin Gain Spectrum

We propose a simplified partitioned Brillouin gain spectrum (BGS) analysis method to enhance the spatial resolution and measurement accuracy of a Brillouin optical time-domain reflectometer (BOTDR) assisted by a first-order Raman pump. We theoretically derive the mathematical model of the partitioned BGS and analyze the superposition process of sub-Brillouin signals within a theoretical spatial resolution range. We unified all the unknown constant parameters of the calculation process to simplify the partitioned BGS analysis method and the value of the uniform parameter is attained through the system test data and numerical analysis. Moreover, to automate data processing, the starting point of the temperature/strain change is determined by the first occurrence of the maximum Brillouin frequency shift (BFS), then the position where the partitioned BGS analysis method calculation begins is obtained. Using a 100 ns probe pulse and partitioned BGS analysis method, we obtain a spatial resolution of 0.4 m in the 78.45-km-long Raman-assisted BOTDR system, and the measurement accuracy is significantly improved. In addition, we achieve a strain accuracy of 5.6 με and a spatial resolution of 0.4 m in the 28.5-km-long BOTDR without Raman amplification.

Stimulated Brillouin scattering in a sub-wavelength anisotropic waveguide with slightly-misaligned material and structural axes: Misalignment-sensitive behaviors and underlying physics

The stimulated Brillouin scatterings (SBSs) in the sub-wavelength rutile waveguides with slightly misaligned material and structural axes are numerically studied. The misalignment is introduced between the extraordinary material axis and longitudinal axis of the waveguide only. Four nanowire waveguides with different cross-sectional geometries are considered. They consist of a circular waveguide, two elliptical waveguides with different cross-sectional orientation angles, and a trapezoidal waveguide with a completely unsymmetrical cross-sectional shape. As reported earlier, the resonant peaks emerging rapidly in response to the introduced small misalignment angle can also be observed in the calculated Brillouin gain spectra of the considered waveguides. But these misalignment-sensitive resonant peaks further exhibit some extraordinary behaviors, which may not be intuitively understandable. For instance, despite a plausible absence of symmetry breaking, many misalignment-sensitive resonant peaks can still be observed in the forward SBS gain spectrum of the trapezoidal waveguide. Based on the symmetry properties of the considered waveguides, the physics underlying the observed extraordinary phenomena are revealed. The obtained results highlight the effectiveness of introducing symmetry breakings for activating/harnessing opto-mechanical couplings in photonic-phononic micro structures, which would enable us to gain some deeper insights into the sub-wavelength opto-mechanics in anisotropic media.

Fast Measurement of Brillouin Frequency Shift in Optical Fiber Based on a Novel Feedforward Neural Network

Brillouin scattering-based distributed optical fiber sensors have been successfully employed in various applications in recent decades, because of benefits such as small size, light weight, electromagnetic immunity, and continuous monitoring of temperature and strain. However, the data processing requirements for the Brillouin Gain Spectrum (BGS) restrict further improvement of monitoring performance and limit the application of real-time measurements. Studies using Feedforward Neural Network (FNN) to measure Brillouin Frequency Shift (BFS) have been performed in recent years to validate the possibility of improving measurement performance. In this work, a novel FNN that is 3 times faster than previous FNNs is proposed to improve BFS measurement performance. More specifically, after the original Brillouin Gain Spectrum (BGS) is preprocessed by Principal Component Analysis (PCA), the data are fed into the Feedforward Neural Network (FNN) to predict BFS.