Optical Frequency Domain Reflectometry Based on Multilayer Perceptron

Yin, Guolu; Zhu, Zhaohao; Liu, Min; Wang, Yu; Liu, Kaijun; Yu, Kuanglu; Zhu, Tao

doi:10.3390/s23063165

Open AccessArticle

Optical Frequency Domain Reflectometry Based on Multilayer Perceptron

by

Guolu Yin

^1,2,*,

Zhaohao Zhu

³,

Min Liu

³,

Yu Wang

¹,

Kaijun Liu

¹,

Kuanglu Yu

^4,5 and

Tao Zhu

^1,2

¹

Key Laboratory of Optoelectronic Technology & Systems (Ministry of Education), Chongqing University, Chongqing 400044, China

²

State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China

³

School of Microelectronics & Communication Engineering, Chongqing University, Chongqing 400044, China

⁴

Institute of Information Science, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China

⁵

Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China

^*

Author to whom correspondence should be addressed.

Sensors 2023, 23(6), 3165; https://doi.org/10.3390/s23063165

Submission received: 20 February 2023 / Revised: 11 March 2023 / Accepted: 14 March 2023 / Published: 16 March 2023

(This article belongs to the Special Issue Advanced Research of Optical Fiber Sensing Technology)

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Abstract

We proposed an optical frequency domain reflectometry based on a multilayer perceptron. A classification multilayer perceptron was applied to train and grasp the fingerprint features of Rayleigh scattering spectrum in the optical fiber. The training set was constructed by moving the reference spectrum and adding the supplementary spectrum. Strain measurement was employed to verify the feasibility of the method. Compared with the traditional cross-correlation algorithm, the multilayer perceptron achieves a larger measurement range, better measurement accuracy, and is less time-consuming. To our knowledge, this is the first time that machine learning has been introduced into an optical frequency domain reflectometry system. Such thoughts and results would bring new knowledge and optimization to the optical frequency domain reflectometer system.

Keywords: optical frequency domain reflectometry; machine learning; strain measurement; multilayer perceptron

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MDPI and ACS Style

Yin, G.; Zhu, Z.; Liu, M.; Wang, Y.; Liu, K.; Yu, K.; Zhu, T. Optical Frequency Domain Reflectometry Based on Multilayer Perceptron. Sensors 2023, 23, 3165. https://doi.org/10.3390/s23063165

AMA Style

Yin G, Zhu Z, Liu M, Wang Y, Liu K, Yu K, Zhu T. Optical Frequency Domain Reflectometry Based on Multilayer Perceptron. Sensors. 2023; 23(6):3165. https://doi.org/10.3390/s23063165

Chicago/Turabian Style

Yin, Guolu, Zhaohao Zhu, Min Liu, Yu Wang, Kaijun Liu, Kuanglu Yu, and Tao Zhu. 2023. "Optical Frequency Domain Reflectometry Based on Multilayer Perceptron" Sensors 23, no. 6: 3165. https://doi.org/10.3390/s23063165

APA Style

Yin, G., Zhu, Z., Liu, M., Wang, Y., Liu, K., Yu, K., & Zhu, T. (2023). Optical Frequency Domain Reflectometry Based on Multilayer Perceptron. Sensors, 23(6), 3165. https://doi.org/10.3390/s23063165

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Optical Frequency Domain Reflectometry Based on Multilayer Perceptron

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