Fast and Accurate Brillouin Optical Time-Domain Sensing by Sparse Frequency Sampling and ANN-Based Recover Method

被引:5
|
作者
Zhang, Yuyang [1 ,2 ]
Lu, Yuangang [1 ,2 ]
Peng, Jianqin [1 ,2 ]
He, Chongjun [1 ,2 ]
Zhang, Zelin [3 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Key Lab Space Photoelectr Detect & Percept, Minist Ind & Informat Technol, Coll Astronaut, Nanjing 211106, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Coll Phys, Nanjing 211106, Peoples R China
[3] Zhongtian Technol Adv Mat Co Ltd, Zhongtian Technol Grp, Nantong 226000, Peoples R China
基金
中国国家自然科学基金;
关键词
Brillouin sensor; deep learning; DEEP NEURAL-NETWORKS; SIMULTANEOUS TEMPERATURE; STRAIN-MEASUREMENT; ASSISTED BOTDA; GAIN SPECTRUM; SHIFT; PERFORMANCE; EXTRACTION; SBS;
D O I
10.1109/JSEN.2023.3244845
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We propose a novel sparse frequency sampling and Brillouin scattering spectrum (BSS) recover method to greatly reduce the acquisition time of the frequency-sweep-based Brillouin optical time-domain sensor (BOTDS) without increasing hardware complexity. In the proposed method, the acquired BSSs only contain a few frequency points and thus show low resolution due to the sparse frequency sampling strategy. Then, an artificial neural network (ANN) is used to accurately recover the BSSs with sparse frequency sampling to that with normal frequency sampling and thus achieve fast and accurate temperature/strain measurement. In a proof-of-concept experiment, we measured the BSS of a 3-km sensing fiber and achieved 3-m spatial resolution by using a Brillouin optical time-domain reflectometry (BOTDR) sensor. Through sparse frequency sampling, the data acquisition time is 5.5% with respect to that of the normal sampling. When the average (AVG) time of BSS is higher than 1000, the temperature measurement uncertainty is 0.2 degrees C.
引用
收藏
页码:6892 / 6900
页数:9
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