Back propagation neutral network based signal acquisition for Brillouin distributed optical fiber sensors

被引:42
作者
Cao, Zhiyuan [1 ]
Guo, Nan [2 ]
Li, Meihong [1 ]
Yu, Kuanglu [1 ]
Gao, Kaiqiang [3 ]
机构
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
[2] Hong Kong Polytech Univ, Dept Elect & Informat Engn, Kowloon, Hong Kong, Peoples R China
[3] China Elect Power Res Inst, Dept Informat & Commun, Beijing 100085, Peoples R China
基金
中国国家自然科学基金;
关键词
SPATIAL-RESOLUTION; RECENT PROGRESS; FREQUENCY-SHIFT; PHI-OTDR; BOTDA; DESIGN;
D O I
10.1364/OE.27.004549
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This manuscript proposes a method based on back propagation (BP) neural network and the spectral subtraction method to quickly obtain sensing information in Brillouin fiber optics sensors. BP neural network's characteristics which can realize any complex nonlinear mapping help to determine the frequency shift section(s) information. The training function, transfer function and number of hidden layer nodes of BP neural network are determined with experimental data. The experimental results show that comparing with traditional Lorentz fitting algorithm and edge detection with Sobel operator, the BP neural network is about 1/12 in terms of time complexity with the Lorentz algorithm, about 1/9 with the edge detection based on Sobel operator; while the respective accuracy on determine the frequency shifted section(s) has improved by 79.4% and 27.9%. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
引用
收藏
页码:4549 / 4561
页数:13
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