Abstract

The technology of pattern recognition for vibration events based on the phase-sensitive optical time domain reflectometer ($\mathrm{\Phi }$-OTDR) has been significantly improved, thanks to plenty of valuable research in recent years. However, it remains challenging to develop an efficient algorithm for it with computing resources that are simpler to achieve at lower cost. To the best of our knowledge, this paper, for the first time, analyzes the superiority of using graphics processing unit (GPU) parallel computing to improve time-consuming performance in pattern recognition for vibration events based on $\mathrm{\Phi }$-OTDR. And the pattern-recognition algorithm, including spectral subtraction and artificial neural networks, is implemented by CPU and GPU, respectively. Then, the time consumption of the CPU-based method and the time consumption of the GPU-based method are, respectively, recorded and compared. As a result of our experiments, we concluded that using GPU parallel computing can develop an efficient algorithm with a computing resource that is simpler to achieve at a lower cost.

© 2019 Optical Society of America

Phase-sensitive optical time domain reflectometer with ultrafast data processing based on GPU parallel computation

Zhou Sha, Hao Feng, Yi Shi, and Zhoumo Zeng
Appl. Opt. 57(10) 2679-2685 (2018)

Space-frequency analysis with parallel computing in a phase-sensitive optical time-domain reflectometer distributed sensor

Xiaonan Hui, Taihang Ye, Shilie Zheng, Jinhai Zhou, Hao Chi, Xiaofeng Jin, and Xianmin Zhang
Appl. Opt. 53(28) 6586-6590 (2014)

Pattern recognition algorithm and software design of an optical fiber vibration signal based on Φ-optical time-domain reflectometry

Tabi Fouda Bernard Marie, Dezhi Han, and Bowen An
Appl. Opt. 58(31) 8423-8432 (2019)

Pattern recognition using self-reference feature extraction for φ-OTDR

Yingzhe Huang, Hongmin Zhao, Xiaoting Zhao, Bo Lin, Fanchao Meng, Jinmin Ding, Shuqin Lou, Xin Wang, Jingwen He, Xinzhi Sheng, and Sheng Liang
Appl. Opt. 61(35) 10507-10518 (2022)

Fast single fringe-pattern processing with graphics processing unit

Haixia Wang, Hongxiang Zeng, Peng Chen, Ronghua Liang, and Li Jiang
Appl. Opt. 58(25) 6854-6864 (2019)