We have proposed and demonstrated a novel flexible optical fiber Fabry-Perot interferometer (FPI) based vibration sensor with broadband frequency response. The sensor consists of a flexible FP cavity formed by soft splicing using polydimethylsiloxane (PDMS) material with low Young's Modulus and a compact fiber cantilever of low moment inertia as the vibration receiver. Acoustic or mechanical waves experienced by the fiber cantilever can result in obvious change of the FPI cavity length and finally be transduced to the intensity variation of the sensor signal, which makes the sensor highly sensitive to external acoustic or mechanical vibrations. Taking advantage of the superior elasticity of PDMS and compact structure of cantilever, a broadband frequency response for vibration detection has been achieved together with high sensitivity without extra external vibration receiver. The vibration detection is theoretically analyzed, and acoustic vibrations up to 20 kHz and damped mechanical vibrations from tens of hertz to tens of kilohertz, covering both the sound and part of ultrasound range, have been experimentally detected. Moreover, each event of the ball hitting and rebounding has been accurately identified by our sensor, showing excellent vibration sensing only by a thin optical fiber. We believe such a broadband, compact and cost-effective sensor would be a promising candidate for monitoring both acoustic and mechanical vibrations.

We have experimentally analyzed and compared the performance of Brillouin optical time-domain analyzer (BOTDA) sensors assisted by non-local means (NLM) and wavelet denoising (WD) techniques in terms of measurement accuracy and experimental spatial resolution, respectively. Degradation of the measurement accuracy and experimental spatial resolution after denoising by NLM and WD are observed, which originate from the fact that higher signal-to-noise ratio (SNR) improvement is achieved at the expense of sacrificing the details of BOTDA data, and smaller data sampling point number (SPN) gives rise to insufficient redundant information for denoising. The two parameters degrade to different extents depending on the amount of SNR improvement and SPN adopted in data acquisition. Compared with WD, NLM relies more on the features of the raw data, which makes its performance highly dependent on the level of neighbouring data similarity. Also, for the first time we propose and demonstrate a BOTDA assisted by advanced Block-Matching and 3D filtering (BM3D) denoising technique, which minimizes the degradation of the two parameters even under higher SNR improvement and smaller SPN. BM3D takes the advantage of NLM and WD and utilizes the spatial-domain non-local principle to enhance the denoising in the transform domain, thus it shows the least degradation of measurement accuracy/experimental spatial resolution after denoising. Thus the BOTDA assisted by BM3D maintains the best measurement accuracy/experimental spatial resolution compared with those by NLM and WD. We also show that BM3D has the advantage of temperature independent performance, unlike NLM where the accuracy is affected by the temperature value. We believe BM3D would be an excellent denoising technique for state-of-the-art BOTDA sensors. In addition, this work is also valuable for practical applications of image denoising techniques in BOTDA sensors with respect to the appropriate choice of image denoising techniques, design of SNR improvement and the adoption of SPN to maintain optimal measurement accuracy/experimental spatial resolution/data acquisition speed.

Simultaneous temperature and strain measurement with enhanced accuracy by using Deep Neural Networks (DNN) assisted Brillouin optical time domain analyzer (BOTDA) has been demonstrated. After trained by using combined ideal clean and noisy BGSs, the DNN is applied to extract both the temperature and strain directly from the measured double-peak BGS in large-effective-area fiber (LEAF). Both simulated and experimental data under different temperature and strain conditions have been used to verify the reliability of DNN-based simultaneous temperature and strain measurement, and demonstrate its advantages over BOTDA with the conventional equations solving method. Avoiding the small matrix determinant-induced large error, our DNN approach significantly improves the measurement accuracy. For a 24-km LEAF sensing fiber with a spatial resolution of 2m, the root mean square error (RMSE) and standard deviation (SD) of the measured temperature/strain by using DNN are improved to be 4.2°C/134.2με and 2.4°C/66.2με, respectively, which are much lower than the RMSE of 30.1°C/710.2με and SD of 19.4°C/529.1με for the conventional equations solving method. Moreover, the temperature and strain extraction by DNN from 600,000 BGSs along 24-km LEAF requires only 1.6s, which is much shorter than that of 5656.3s by the conventional equations solving method. The enhanced accuracy and fast processing speed make the DNN approach a practical way of achieving simultaneous temperature and strain measurement by the conventional BOTDA system without adding system complexity.

Brillouin optical time-domain analyzer (BOTDA) assisted by support vector machine (SVM) for ultrafast temperature extraction is proposed and experimentally demonstrated. The temperature extraction is treated as a supervised classification problem and the Brillouin gain spectrum (BGS) is classified into each temperature class according to the support vectors and hyperplane of the SVM model after training. Ideal pseudo-Voigt curve-based BGS is used to train the SVM to get the support vectors and hyperplane. The performance of SVM is investigated in both simulation and experiment under various conditions for BGS collection. Both simulation and experiment results show that SVM is more robust to a wide range of signal-to-noise ratios, averaging times, pump pulse widths, frequency scanning steps, and temperatures. In addition to better accuracy, the processing speed for temperature extraction using SVM is 100 times faster than that using conventional Lorentzian curve and pseudo-Voigt curve fitting techniques in our experiment. The fast processing speed together with good accuracy and robustness makes SVM a highly competitive candidate for future high-speed BOTDA sensors.

The maximum detectable vibration frequency by phase-sensitive optical time-domain reflectometer ( $\Phi$ -OTDR) is limited by the repetition rate of the pump pulse. Additionally, the intensity-demodulation based $\Phi$ -OTDR sensor suffers from the generally nonlinear dependency of the backscattered optical intensity on vibration. This makes quantitative measurement of vibration frequency difficult. In order to mitigate these limitations, we propose and demonstrate a multicore fiber (MCF) based space-division multiplexed (SDM) $\Phi$ -OTDR and Mach-Zehnder interferometer (MZI) hybrid sensor, enabling truly uninterrupted distributed vibration sensing with broad vibration frequency response range and high spatial resolution. By taking advantage of highly integrated multiple spatial cores offered by a MCF, $\Phi$ -OTDR implemented in one of the cores is used to locate the vibration. Meanwhile, a MZI is constructed using another two parallel spatial cores with sufficient continuous-wave (CW) optical power from a coherent narrow linewidth laser, which is used to retrieve the vibration frequency by processing the acquired interference signal. Compared with the single mode fiber based hybrid systems, the proposed SDM configuration allows implementation of $\Phi$ -OTDR and MZI independently without any crosstalk between them. Consequently it offers many unique advantages, such as simple data processing procedure, good signal-to-noise ratio (SNR) of the demodulated vibration frequency spectrum, no frequency dead zone, and single-end access. This cost-effective SDM hybrid sensor provides significant potential for distributed and accurate monitoring of vibrations.

A single-measurement sweep-free distributed Brillouin optical time domain analyzer (BOTDA) sensor based on phase detection is proposed and experimentally demonstrated employing digital optical frequency comb (DOFC) probe signal. Brillouin Phase Spectrum (BPS) of DOFC probe induced by Brillouin interaction is measured using coherent detection in a single acquisition, without any frequency scanning and data averaging. Single-measurement BOTDA sensor based on BPS in 10km long fiber is demonstrated with a response time of 100 $\mu s$, which is limited only by the fiber length. The spatial resolution is 51.2m, determined by the duration of DOFC. And the Brillouin frequency shift (BFS) uncertainty is estimated to be~1.5 MHz at the end of fiber under test (FUT). Benefiting from the fast response time, dynamic measurement up to 1 kHz vibration frequency has been demonstrated.