Abstract

A novel frequency-domain image processing method is proposed, to the best of our knowledge, to filter the noise from data collected by distributed optical fiber sensors based on Brillouin optical time-domain sensing (BOTDS). In the proposed method, we first divide a data image into subimages, and then we filter the noisy subimages by retaining the useful frequency information corresponding to the Lorentz-shape frequency spectrum and Brillouin frequency shift (BFS) transitions. The denoising performance improvements are verified by simulation and experiment. The performances in terms of temperature/strain measurement uncertainty, spatial resolution, and processing time achieved by the proposed filter are then compared with those by using a Gaussian filter and a nonlocal means (NLM) filter. In a proof-of-concept experiment with a 5.2 km length G657 sensing fiber, we achieve a temperature measurement uncertainty improvement of 27% compared with the results obtained by using the Gaussian filtering method. Furthermore, the processing speed of the proposed method is 22 times faster than that of the NLM filter under the same temperature measurement uncertainty.

© 2022 Optica Publishing Group

Rapid noise removal based dual adversarial network for the Brillouin optical time domain analyzer

Jingyang Liu, Tao Wang, Qian Zhang, Huan Chen, Jianzhong Zhang, Lijun Qiao, Shaohua Gao, and Mingjiang Zhang
Opt. Express 29(21) 34002-34014 (2021)

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)

Distributed strain and temperature fast measurement in Brillouin optical time-domain reflectometry based on double-sideband modulation

Jianqin Peng, Yuangang Lu, Yuyang Zhang, and Zelin Zhang
Opt. Express 30(2) 1511-1520 (2022)

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)

Dynamic strain measurement in Brillouin optical correlation-domain sensing facilitated by dimensionality reduction and support vector machine

Yuguo Yao and Yosuke Mizuno
Opt. Express 30(9) 15616-15633 (2022)