Wavelet denoising of fiber optic monitoring signals in permafrost regions

Abstract To address the noise issue in fiber optic monitoring signals in frozen soil areas, this study employs wavelet denoising techniques to process the fiber optic signals. Since existing parameter choices for wavelets are typically based on conventional environments, selecting suitable parameter...

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Bibliographic Details
Published in:Scientific Reports
Main Authors: Bowen Ni, Fei Song, Liguo Zhao, Zhipeng Fu, Yongyi Huang
Format: Article in Journal/Newspaper
Language:English
Published: Nature Portfolio 2024
Subjects:
Geotechnical engineering
Optical fiber monitoring
Wavelet denoising
Medicine
R
Science
Q
permafrost
Online Access:https://doi.org/10.1038/s41598-024-59941-4
https://doaj.org/article/cb55091657be4f8eb6960524d1bf97a6
Description
Summary:Abstract To address the noise issue in fiber optic monitoring signals in frozen soil areas, this study employs wavelet denoising techniques to process the fiber optic signals. Since existing parameter choices for wavelets are typically based on conventional environments, selecting suitable parameters for frozen soil regions becomes crucial. In this work, an index library is constructed based on commonly used wavelet basis functions in civil engineering. An optimal wavelet basis function is objectively selected through specific criteria. Considering the characteristic of small root mean square error in fiber optic signals in frozen soil areas, a multi-index fusion approach is applied to determine the optimal decomposition level. Field observations validate that denoised signals, with parameters set appropriately, can more accurately identify locations where settlement occurs.

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