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Demodulation of Vernier-effect-based optical fiber strain sensor by using improved cross-correlation algorithm

LIU Bin CAO Zhi-gang WANG Xing-yun LIN Zi-han CHENG Rui LIU Jun SUN Yu-han ZHENG Shu-jun ZUO Cheng LIN Ji-ping

刘斌, 曹志刚, 王幸运, 蔺子翰, 程瑞, 刘俊, 孙宇寒, 郑述军, 左铖, 林继平. 基于改进互相关算法的游标效应光纤应变传感器解调方法[J]. 中国光学(中英文). doi: 10.37188/CO.EN-2025-0024
引用本文: 刘斌, 曹志刚, 王幸运, 蔺子翰, 程瑞, 刘俊, 孙宇寒, 郑述军, 左铖, 林继平. 基于改进互相关算法的游标效应光纤应变传感器解调方法[J]. 中国光学(中英文). doi: 10.37188/CO.EN-2025-0024
LIU Bin, CAO Zhi-gang, WANG Xing-yun, LIN Zi-han, CHENG Rui, LIU Jun, SUN Yu-han, ZHENG Shu-jun, ZUO Cheng, LIN Ji-ping. Demodulation of Vernier-effect-based optical fiber strain sensor by using improved cross-correlation algorithm[J]. Chinese Optics. doi: 10.37188/CO.EN-2025-0024
Citation: LIU Bin, CAO Zhi-gang, WANG Xing-yun, LIN Zi-han, CHENG Rui, LIU Jun, SUN Yu-han, ZHENG Shu-jun, ZUO Cheng, LIN Ji-ping. Demodulation of Vernier-effect-based optical fiber strain sensor by using improved cross-correlation algorithm[J]. Chinese Optics. doi: 10.37188/CO.EN-2025-0024

基于改进互相关算法的游标效应光纤应变传感器解调方法

Demodulation of Vernier-effect-based optical fiber strain sensor by using improved cross-correlation algorithm

doi: 10.37188/CO.EN-2025-0024
Funds: This work is supported by National Natural Science Foundation of China (No. 61605001); National Key R & D Program of China under Grant (No. 2016YFC0301900 and No. 2016YFC0301901); The Young Core Teacher Foundation of Anhui University and Anhui Provincial Natural Science Foundation (No. 1408085QF135)
More Information
    Author Bio:

    LIU Bin (1996—) received the B.S. degree in optoelectronic information science and engineering from Anhui University, Hefei, China, in 2020. His current research interests include optic fiber sensing. E-mail: 2940271455@qq.com

    CAO Zhi-gang (1981—) received his Ph.D. in Physics and Electronics from Anhui University in 2015. Currently mainly engaged in research related to fiber sensors and fiber lasers. E-mail: caozhigang@ahu.edu.cn

    Corresponding author: caozhigang@ahu.edu.cn
  • 摘要:

    为了解决基于光学游标效应的光纤应变传感器中传统光谱跟踪解调方式测量精度不足、测量范围小的问题,本文提出了一种改进型互相关算法并将其应用于游标型光纤应变传感器信号解调。该算法通过互相关操作从采集的光谱数据中识别出与待测光谱最为相似的光谱,然后通过加权计算得到预测应变值。由于该算法使用了被测量光谱中包含的全部信息,因此可以得到更准确的结果和更大的测量范围,经过实验验证,获得了0.1038$ \mu \varepsilon $的低平均绝对误差,并且消除了光谱范围对测量范围的限制。此外,与光谱跟踪技术相比,由于其可以使用低分辨率光谱进行解调,该改进互相关算法还具有提高测量速度的能力,因此该算法进一步提高了基于游标效应的光纤应变传感器解调性能。

     

  • Figure 1.  Experimental setup including a VE-OFS based on two reflective Lyot interferometers.

    Figure 2.  The spectrum of the VE-OFS from the OSA.

    Figure 3.  (a) Measured spectra of the VE-OFS and (b) linear fitting curve for different strains applied to the sensing interferometer.

    Figure 4.  The flowchart of improved cross-correlation algorithm.

    Figure 5.  The distribution of cross-correlation difference values.

    Figure 6.  (a) Scatter plot of the predicted strains vs. the ground truth (b) Scatter plot of the predicted strains vs. the ground truth with another size of the Vernier envelope.

    Figure 7.  The impact of (a) spectral number downsampling and (b) spectral points downsampling on the MAE.

    Figure 8.  (a) The single Vernier envelope within different strains (b) The demodulation of the single Vernier envelope.

    Figure 9.  The light source intensity fluctuations at 1550 nm within different currents.

    Table  1.   Comparison of the predicted results.

    Algorithm MAE_0 MAE_1 MAE_2
    Improved cross-correlation
    algorithm
    0.1038 $ \mu \varepsilon $ 80.1957 $ \mu \varepsilon $ 0.1361 $ \mu \varepsilon $
    GPR 4.2784 $ \mu \varepsilon $ 512.909 $ \mu \varepsilon $ 4.5726 $ \mu \varepsilon $
    CNN 8.3923 $ \mu \varepsilon $ 579.633 $ \mu \varepsilon $ 8.9753 $ \mu \varepsilon $
    LSTM 6.9757 $ \mu \varepsilon $ 346.147 $ \mu \varepsilon $ 6.1725 $ \mu \varepsilon $
    FNN 12.9246 $ \mu \varepsilon $ 512.358 $ \mu \varepsilon $ 13.5166 $ \mu \varepsilon $
    Linear curve fitting 26.7467 $ \mu \varepsilon $ / /
    下载: 导出CSV

    Table  2.   Demodulation on different intensity fluctuations.

    MAE/drive current 600 mA 100 mA 50 mA
    MAEmax 0.4016 $ \mu \varepsilon $ 0.2306 $ \mu \varepsilon $ 0.6835 $ \mu \varepsilon $
    MAEmin 0.0898 $ \mu \varepsilon $ 0.1137 $ \mu \varepsilon $ 0.5037 $ \mu \varepsilon $
    MAEave 0.1038 $ \mu \varepsilon $ 0.18 $ \mu \varepsilon $ 0.59 $ \mu \varepsilon $
    下载: 导出CSV
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出版历程
  • 收稿日期:  2025-03-27
  • 录用日期:  2025-05-19
  • 网络出版日期:  2025-07-01

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