Separating method for multi-source vibration signals in ultra-weak fiber Bragg grating distributed acoustic sensors

Luo, Zhihui; Yang, Zhen; Chen, Xiaoan; Ran, Changyan; Huang, Jianglou; Ye, Yong

doi:10.1016/j.yofte.2023.103501

Optical Fiber Technology

2023

DOI: 10.1016/j.yofte.2023.103501

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Separating method for multi-source vibration signals in ultra-weak fiber Bragg grating distributed acoustic sensors

Zhihui Luo,

Zhen Yang,

Xiaoan Chen

et al.

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Cited by 3 publications

References 19 publications

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A review on the application of blind source separation in vibration analysis of mechanical systems

Yang,

Xie,

et al. 2024

Measurement

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A review on the application of blind source separation in vibration analysis of mechanical systems

Yang,

Xie,

et al. 2024

Measurement

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Apart and A Part: Overlapped vibration recognition for distributed optical fiber sensing based on deep learning separation

Yan,

Wei,

Lin

et al. 2025

Optics & Laser Technology

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Research on gas pipeline leakage identification based on SE-2DCNN with ultra-weak fiber Bragg grating distributed acoustic sensing system

Luo,

Yang,

Chen

et al. 2024

Meas. Sci. Technol.

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A new method for identifying gas pipeline leaks using an ultra-weak fiber Bragg grating (UWFBG) distributed acoustic sensing (DAS) system is proposed. To enhance the accuracy of gas leakage detection, an improved convolutional neural network (CNN) incorporating a two-dimensional structure based on the squeeze-and-excitation (SE) attention mechanism was introduced. The principle of acoustic leakage sensing using this technology is explained in detail, and an experimental setup simulating gas pipeline leaks is constructed. During this process, 9,340 DAS data points across varying leakage volumes and pipeline pressures were collected to create ten distinct datasets. The Mel-frequency cepstral coefficients (MFCC) are employed as the feature input for the optimized SE-2DCNN model, which performs identification tasks. The results show that this optimized model achieves an average leakage identification accuracy of 95.33%, demonstrating superior performance over other methods. This approach offers a robust reference for accurately detecting gas pipeline leakages.

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Separating method for multi-source vibration signals in ultra-weak fiber Bragg grating distributed acoustic sensors

Cited by 3 publications

References 19 publications

A review on the application of blind source separation in vibration analysis of mechanical systems

A review on the application of blind source separation in vibration analysis of mechanical systems

Apart and A Part: Overlapped vibration recognition for distributed optical fiber sensing based on deep learning separation

Research on gas pipeline leakage identification based on SE-2DCNN with ultra-weak fiber Bragg grating distributed acoustic sensing system

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