Acta Optica Sinica, Volume. 45, Issue 7, 0728006(2025)

Signal‑to‑Noise Ratio Optimization for Distributed Fiber Temperature Sensing System Based on Blind Denoising Convolutional Autoencoder

Jiamu Ling1, Zhuangwei Xu2, Wei Ye1,2, Zhengguo Xu1,2、*, and Kejiang Zhou2
Author Affiliations
  • 1College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China
  • 2Huzhou Institute of Zhejiang University, Huzhou 313000, Zhejiang, China
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    References(17)

    [2] Cao K Y, Li J, Zhang M J. Research progress on improving the temperature measurement accuracy of Raman distributed fiber sensing[J]. Laser & Optoelectronics Progress, 61, 1700005(2024).

    [8] Ma D Y, Liu X Y, Li Y Z et al. Advances in machine-learning techniques for distributed fiber-optic sensing performance enhancement[J]. Laser & Optoelectronics Progress, 62, 0300002(2025).

    [9] Pan J. Research and system integration of distributed optical fiber Raman temperature sensing system[D](2022).

    [12] Wan R Q, Zhang C, Jiang H Q et al. A blind denoising method of vibration signals based on a deep autoencoder[J]. Journal of Vibration and Shock, 42, 118-125(2023).

    [17] Chen X X, Wang Y J, Liu L. Deep study on wavelet threshold method for image noise removing[J]. Laser & Infrared, 42, 105-110(2012).

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    Jiamu Ling, Zhuangwei Xu, Wei Ye, Zhengguo Xu, Kejiang Zhou. Signal‑to‑Noise Ratio Optimization for Distributed Fiber Temperature Sensing System Based on Blind Denoising Convolutional Autoencoder[J]. Acta Optica Sinica, 2025, 45(7): 0728006

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Dec. 5, 2024

    Accepted: Feb. 21, 2025

    Published Online: Apr. 27, 2025

    The Author Email: Zhengguo Xu (xzg@zju.edu.cn)

    DOI:10.3788/AOS241837

    CSTR:32393.14.AOS241837

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