Spectral Demodulation of Fiber Bragg Grating Sensor Based on Deep Convolutional Neural Networks-Reference-Cited by-同舟云学术

Spectral Demodulation of Fiber Bragg Grating Sensor Based on Deep Convolutional Neural Networks

Published:2022-07-01 Issue:13 Volume:40 Page:4429-4435
ISSN:0733-8724
Container-title:Journal of Lightwave Technology
language:
Short-container-title:J. Lightwave Technol.

Author:

Cao Zihan¹,Zhang Shengqi¹,Xia Titi¹,Liu Zhengyong¹^ORCID,Li Zhaohui¹^ORCID

Affiliation:

1. Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China

Funder

National Key R&D Program of China

Ministry of Science and Technology

National Natural Science Foundation of China

Science and Technology Planning Project of Guangzhou

Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/50/9809956/09723626.pdf?arnumber=9723626

Reference20 articles.

1. Recognition and classification of FBG reflection spectrum under non-uniform field based on support vector machine

2. A CNN-based FBG demodulation method adopting the GAF-assisted ascending dimension of complicated signal

3. Wavelength detection in FBG sensor networks using least squares support vector regression

4. Machine Learning Methods for Discriminating Strain and Temperature Effects on FBG-Based Sensors

5. Fiber grating spectra

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