Cost-effective and lightweight FBG demodulation system based on edge AI

被引：0

作者：

Zhou, Rui ^{[1
]}

Peng, Xin ^{[1
]}

Wang, Xu ^{[1
]}

Zhang, Haojie ^{[1
]}

Zhai, Tong ^{[1
]}

Li, Guangxin ^{[1
]}

Gu, Xueliang ^{[1
]}

Zhang, Zhiguo ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China

来源：

OPTICS EXPRESS | 2025年 / 33卷 / 08期

基金：

中国国家自然科学基金;

关键词：

ALGORITHM;

D O I：

10.1364/OE.558223

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Fiber Bragg grating (FBG) sensors are extensively employed for structural health and condition monitoring. However, the high cost and large size of conventional FBG demodulation methods have hindered the widespread adoption of FBG-based sensing technologies. To overcome these challenges, this study proposes what we believe to be a novel demodulation system leveraging a tunable laser. The system utilizes a gated recurrent unit (GRU) peak-finding algorithm, implemented on an STM32 microcontroller with edge AI capabilities, all integrated onto a compact 100x100x10 mm circuit board. This approach enables demodulation across the entire C-band, achieving a monitoring range of 70 km, a demodulation frequency of 100 Hz, and a mean absolute error (MAE) of 9.6 pm.

引用

页码：17446 / 17461

页数：16

共 28 条

[1] Sequential interrogation of multiple FBG sensors using LPG modulation and an artificial neural network [J].

Basu, Mainak ;

Ghorai, S. K. .

MEASUREMENT SCIENCE AND TECHNOLOGY, 2015, 26 (04)

[2] Spectral Demodulation of Fiber Bragg Grating Sensor Based on Deep Convolutional Neural Networks [J].

Cao, Zihan ;

Zhang, Shengqi ;

Xia, Titi ;

Liu, Zhengyong ;

Li, Zhaohui .

JOURNAL OF LIGHTWAVE TECHNOLOGY, 2022, 40 (13) :4429-4435

[3] Improving measurement accuracy of fiber Bragg grating sensor using digital matched filter [J].

Chan, CC ;

Gong, JM ;

Shi, CZ ;

Jin, W ;

Zhang, M ;

Zhou, LM ;

Demokan, MS .

SENSORS AND ACTUATORS A-PHYSICAL, 2003, 104 (01) :19-24

[4] Multiple fiber Bragg grating interrogation based on a spectrum-limited Fourier domain mode-locking fiber laser [J].

Chen, Daru ;

Shu, Chester ;

He, Sailing .

OPTICS LETTERS, 2008, 33 (13) :1395-1397

[5] Cost-effective improvement of the performance of AWG-based FBG wavelength interrogation via a cascaded neural network [J].

Chen, Shengchao ;

Yao, Feifan ;

Ren, Sufen ;

Wang, Guanjun ;

Huang, Mengxing .

OPTICS EXPRESS, 2022, 30 (05) :7647-7663

[6] Accurate demodulation algorithm for multi-peak FBG sensor based on invariant moments retrieval [J].

Guo, Yu ;

Yu, Chao ;

Ni, Yi ;

Wu, Haodong .

OPTICAL FIBER TECHNOLOGY, 2020, 54

[7] A novel fiber Bragg grating interrogating sensor system based on AWG demultiplexing [J].

Hui Su ;

Xu Guang Huang .

OPTICS COMMUNICATIONS, 2007, 275 (01) :196-200

[8] SIMPLE MULTIPLEXING SCHEME FOR A FIBEROPTIC GRATING SENSOR NETWORK [J].

JACKSON, DA ;

RIBEIRO, ABL ;

REEKIE, L ;

ARCHAMBAULT, JL .

OPTICS LETTERS, 1993, 18 (14) :1192-1194

[9]

Jeong S.-Y., 2018, Optical Sensors, pJTu2A

[10] An optimized strain demodulation method based on dynamic double matched fiber Bragg grating filtering [J].

Jiang, Biqiang ;

Zhao, Jianlin ;

Qin, Chuan ;

Huang, Zhao ;

Fan, Fan .

OPTICS AND LASERS IN ENGINEERING, 2011, 49 (03) :415-418

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