Deep Learning Enhanced Long-Range Fast BOTDA for Vibration Measurement

In this paper, we propose and experimentally demonstrate a scheme of deep learning enhanced long-range fast Brillouin optical time-domain analysis (BOTDA). The volumetric data from BOTDA is denoised demodulated by using video denoising network neural network, respectively. Benefitting the advanced algorithms, sensing range extended to 10 km successfully. experiment, vibration signal measured with sampling rate 23 Hz, 2 m spatial resolution, 1.19 MHz accuracy over single-mode fiber only 4 averages. Due low computational complexity GPU acceleration, takes less than 0.04 s process 100 × 21800 data, which much faster conventional algorithms. This method provides potential for real-time measurement in long range.