Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning

Miaofeng Fu; Jun Zheng; Shenyi Liu; Yunxu Sun; Wei Liu

doi:10.1109/ICOCN59242.2023.10236362

Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning

Miaofeng Fu
, Jun Zheng
, Shenyi Liu
, Yunxu Sun^*
, Wei Liu^*

^*Corresponding author for this work

Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

A multimode fiber (MMF) speckle sensor based on deep learning is demonstrated for sensing multi-physical quantity at different position. The mode fields at the end of MMF compose speckle patterns, which are sensitive to the various types of disturbing with different manners. Further, the MMF also carry numerous information, which make it possible sensing different physical quantity at different points in just one MMF. Here, it is demonstrated to sense stretching, bending, and temperature in a MMF of 0.5m by the deep learning methods. Its stretching precision is up to 0.005mm with the U-Net.

Original language	English
Title of host publication	2023 21st International Conference on Optical Communications and Networks, ICOCN 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350343502
DOIs	https://doi.org/10.1109/ICOCN59242.2023.10236362
State	Published - 2023
Externally published	Yes
Event	21st International Conference on Optical Communications and Networks, ICOCN 2023 - Qufu, China Duration: 31 Jul 2023 → 3 Aug 2023

Publication series

Name	2023 21st International Conference on Optical Communications and Networks, ICOCN 2023

Conference

Conference	21st International Conference on Optical Communications and Networks, ICOCN 2023
Country/Territory	China
City	Qufu
Period	31/07/23 → 3/08/23

Keywords

Fiber speckle sensor
deep Learning
micrometer sensor
speckle

Access to Document

10.1109/ICOCN59242.2023.10236362

Cite this

Fu, M., Zheng, J., Liu, S., Sun, Y., & Liu, W. (2023). Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning. In 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023 (2023 21st International Conference on Optical Communications and Networks, ICOCN 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICOCN59242.2023.10236362

Fu, Miaofeng ; Zheng, Jun ; Liu, Shenyi et al. / Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning. 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 21st International Conference on Optical Communications and Networks, ICOCN 2023).

@inproceedings{141e3f81a59c473b957a558ec87636a2,

title = "Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning",

abstract = "A multimode fiber (MMF) speckle sensor based on deep learning is demonstrated for sensing multi-physical quantity at different position. The mode fields at the end of MMF compose speckle patterns, which are sensitive to the various types of disturbing with different manners. Further, the MMF also carry numerous information, which make it possible sensing different physical quantity at different points in just one MMF. Here, it is demonstrated to sense stretching, bending, and temperature in a MMF of 0.5m by the deep learning methods. Its stretching precision is up to 0.005mm with the U-Net.",

keywords = "Fiber speckle sensor, deep Learning, micrometer sensor, speckle",

author = "Miaofeng Fu and Jun Zheng and Shenyi Liu and Yunxu Sun and Wei Liu",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 21st International Conference on Optical Communications and Networks, ICOCN 2023 ; Conference date: 31-07-2023 Through 03-08-2023",

year = "2023",

doi = "10.1109/ICOCN59242.2023.10236362",

language = "英语",

series = "2023 21st International Conference on Optical Communications and Networks, ICOCN 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 21st International Conference on Optical Communications and Networks, ICOCN 2023",

address = "美国",

}

Fu, M, Zheng, J, Liu, S, Sun, Y & Liu, W 2023, Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning. in 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023. 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023, Institute of Electrical and Electronics Engineers Inc., 21st International Conference on Optical Communications and Networks, ICOCN 2023, Qufu, China, 31/07/23. https://doi.org/10.1109/ICOCN59242.2023.10236362

Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning. / Fu, Miaofeng; Zheng, Jun; Liu, Shenyi et al.
2023 21st International Conference on Optical Communications and Networks, ICOCN 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 21st International Conference on Optical Communications and Networks, ICOCN 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning

AU - Fu, Miaofeng

AU - Zheng, Jun

AU - Liu, Shenyi

AU - Sun, Yunxu

AU - Liu, Wei

PY - 2023

Y1 - 2023

N2 - A multimode fiber (MMF) speckle sensor based on deep learning is demonstrated for sensing multi-physical quantity at different position. The mode fields at the end of MMF compose speckle patterns, which are sensitive to the various types of disturbing with different manners. Further, the MMF also carry numerous information, which make it possible sensing different physical quantity at different points in just one MMF. Here, it is demonstrated to sense stretching, bending, and temperature in a MMF of 0.5m by the deep learning methods. Its stretching precision is up to 0.005mm with the U-Net.

AB - A multimode fiber (MMF) speckle sensor based on deep learning is demonstrated for sensing multi-physical quantity at different position. The mode fields at the end of MMF compose speckle patterns, which are sensitive to the various types of disturbing with different manners. Further, the MMF also carry numerous information, which make it possible sensing different physical quantity at different points in just one MMF. Here, it is demonstrated to sense stretching, bending, and temperature in a MMF of 0.5m by the deep learning methods. Its stretching precision is up to 0.005mm with the U-Net.

KW - Fiber speckle sensor

KW - deep Learning

KW - micrometer sensor

KW - speckle

UR - https://www.scopus.com/pages/publications/85173092314

U2 - 10.1109/ICOCN59242.2023.10236362

DO - 10.1109/ICOCN59242.2023.10236362

M3 - 会议稿件

AN - SCOPUS:85173092314

T3 - 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023

BT - 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 21st International Conference on Optical Communications and Networks, ICOCN 2023

Y2 - 31 July 2023 through 3 August 2023

ER -

Fu M, Zheng J, Liu S, Sun Y, Liu W. Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning. In 2023 21st International Conference on Optical Communications and Networks, ICOCN 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 21st International Conference on Optical Communications and Networks, ICOCN 2023). doi: 10.1109/ICOCN59242.2023.10236362

Multipoint and Multi-physical Quantity Sensing by Multimode Fiber with Demodulation of Deep Learning

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