Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Deep-learning-assisted fiber Bragg grating interrogation by random speckles

Not Accessible

Your library or personal account may give you access

Abstract

Fiber Bragg gratings (FBGs) have been widely employed as a sensor for temperature, vibration, strain, etc. measurements. However, extant methods for FBG interrogation still face challenges in the aspects of sensitivity, measurement speed, and cost. In this Letter, we introduced random speckles as the FBG’s reflection spectrum information carrier for demodulation. Instead of the commonly used InGaAs cameras, a quadrant detector (QD) was first utilized to record the speckle patterns in the experiments. Although the speckle images were severely compressed into four channel signals by the QD, the spectral features of the FBGs can still be precisely extracted with the assistance of a deep convolution neural network (CNN). The temperature and vibration experiments were demonstrated with a resolution of 1.2 pm. These results show that the new, to the best of our knowledge, speckle-based demodulation scheme can satisfy the requirements of both high-resolution and high-speed measurements, which should pave a new way for the optical fiber sensors.

© 2021 Optica Publishing Group

Full Article  |  PDF Article
More Like This
Demodulation of Fabry–Perot sensors using random speckles

Qin Liang, Jinchao Tao, Xu Wang, Tianliang Wang, Xinyu Gao, Pengwei Zhou, Ben Xu, Chunliu Zhao, Juan Kang, Le Wang, Changyu Shen, Dongning Wang, and Yi Li
Opt. Lett. 47(18) 4806-4809 (2022)

Radio-frequency unbalanced M–Z interferometer for wavelength interrogation of fiber Bragg grating sensors

Jiaao Zhou, Li Xia, Rui Cheng, Yongqiang Wen, and Jalal Rohollahnejad
Opt. Lett. 41(2) 313-316 (2016)

Holographic and speckle encryption using deep learning

Xiaogang Wang, Wenqi Wang, Haoyu Wei, Bijun Xu, and Chaoqing Dai
Opt. Lett. 46(23) 5794-5797 (2021)

Data Availability

Data underlying the results presented in this Letter are not publicly available at this time but may be obtained from the authors upon reasonable request.

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (4)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (1)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.