Abstract

Anisotropic diffusion (AD) is employed to enhance the signal-to-noise ratio (SNR) of Brillouin distributed optical fiber sensor. A Brillouin optical time-domain analyzer (BOTDA) with 99-km-long fiber under test is set up, where a section of 2.3 m and another 182 m section at the end of the fiber are heated for experimental verification. The SNR of experimental data sets with different sampling point numbers are enhanced to several improvement levels by AD and three other methods for comparison. Results show that the 2.3 m section and the temperature transition region of the 182 m section are better preserved by AD than other methods for the same SNR improvement. Objective criteria analysis shows that AD achieves the best measured spatial resolution and temperature accuracy among the four methods, the location of temperature transition can be detected more accurately for data with low SPNs after AD denoising. In addition, the processing time of AD is 1/3 that of non-local means (NLM) and 6‰ that of block-matching and 3D filtering (BM3D). The edge-preserving quality and fast processing speed allow the proposed algorithm to be a competitive denoising alternative for sensors based on Brillouin scattering.

SNR enhancement for Brillouin distributed optical fiber sensors based on asynchronous control

Peixuan Zhang, Biwei Wang, Yanan Yang, Abul Kalam Azad, Kuo Luo, Kuanglu Yu, Changyuan Yu, and Chao Lu
Opt. Express 30(3) 4231-4248 (2022)

Brillouin optical time domain analyzer sensors assisted by advanced image denoising techniques

Huan Wu, Liang Wang, Zhiyong Zhao, Nan Guo, Chester Shu, and Chao Lu
Opt. Express 26(5) 5126-5139 (2018)

Noise reduction in a Brillouin optical time-domain sensor by a frequency-domain feature filter

Pei Yuan, Yuangang Lu, Yuyang Zhang, and Zelin Zhang
Appl. Opt. 61(10) 2667-2674 (2022)

Distributed Brillouin fiber laser sensor

Joseph B. Murray, Alex Cerjan, and Brandon Redding
Optica 9(1) 80-87 (2022)

Hybrid aperiodic coding for SNR improvement in a BOTDA fiber sensor

Yin Zhou, Lianshan Yan, Can Liu, Haijun He, Zonglei Li, Heng Qian, Jia Ye, Wei Pan, and Bin Luo
Opt. Express 29(21) 33926-33936 (2021)