Intelligent quadrant-cavity-integrated FBG strain sensor: a multifunctional composite tube for real-time monitoring of vertical deformation in slope geohazard early warning systems

In response to the problems of uplift and settlement of underground soil layer in slope areas caused by urbanization and intensified resource extraction activities, this study proposes an intelligent composite strain sensing tube based on fiber Bragg grating (FBG) with four-quadrant cavity segmentation. This device is designed to monitor the deformation and displacement evolution processes of soil, and obtain data by real-time monitoring of the wavelength changes of Bragg gratings. In the experimental setup, external forces are applied to vary the pulling displacement under different overburden thicknesses (0, 1, 3, and 5 cm), thereby simulating slope uplift and settlement at various soil depths. The results show that under different overburden thicknesses, the strain (displacement) transfer law of the FBG strain tube shows a trend of gradually decreasing from the fixed end to both ends of the pulling device. To improve the measurement accuracy, temperature compensation measures (adding a loosely installed grating near the sensing grating) were introduced in the experiment. In addition, to improve the accuracy of strain-displacement data, this study proposes a strain-displacement conversion method based on a sequence-to-sequence (Seq2Seq) model to predict the uplift and settlement displacements of pipelines, and uses a random forest algorithm to classify and verify the prediction results. The average error between the model prediction value and the actual value is about 0.22 mm. The success rate of regression prediction for soil uplift and settlement displacement reaches 97.88%, and the prediction accuracy is as high as 99.23%. This FBG Haversian strain tube has the advantages of convenient operation and high displacement sensitivity, and is expected to be applied to the actual deep displacement monitoring of slopes in the future to prevent road uplift and settlement disasters.

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Publication Details

Journal
Optics Express
Published
2025-10-13
DOI
https://doi.org/10.1364/oe.576065
Primary Topic
Advanced Fiber Optic Sensors
Type
article
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article

Intelligent quadrant-cavity-integrated FBG strain sensor: a multifunctional composite tube for real-time monitoring of vertical deformation in slope geohazard early warning systems

Jie Ma, Lidong Gong, Hong Yan, S. Y. Zhang et al.
Optics Express
Advanced Fiber Optic Sensors
article

Intelligent quadrant-cavity-integrated FBG strain sensor: a multifunctional composite tube for real-time monitoring of vertical deformation in slope geohazard early warning systems

Jie Ma, Lidong Gong, Hong Yan, S. Y. Zhang, Zejia Zhao, Peng Chen, Dandan Sun, Yongming Fu, Yu Yuejiang
article en

Abstract

In response to the problems of uplift and settlement of underground soil layer in slope areas caused by urbanization and intensified resource extraction activities, this study proposes an intelligent composite strain sensing tube based on fiber Bragg grating (FBG) with four-quadrant cavity segmentation. This device is designed to monitor the deformation and displacement evolution processes of soil, and obtain data by real-time monitoring of the wavelength changes of Bragg gratings. In the experimental setup, external forces are applied to vary the pulling displacement under different overburden thicknesses (0, 1, 3, and 5 cm), thereby simulating slope uplift and settlement at various soil depths. The results show that under different overburden thicknesses, the strain (displacement) transfer law of the FBG strain tube shows a trend of gradually decreasing from the fixed end to both ends of the pulling device. To improve the measurement accuracy, temperature compensation measures (adding a loosely installed grating near the sensing grating) were introduced in the experiment. In addition, to improve the accuracy of strain-displacement data, this study proposes a strain-displacement conversion method based on a sequence-to-sequence (Seq2Seq) model to predict the uplift and settlement displacements of pipelines, and uses a random forest algorithm to classify and verify the prediction results. The average error between the model prediction value and the actual value is about 0.22 mm. The success rate of regression prediction for soil uplift and settlement displacement reaches 97.88%, and the prediction accuracy is as high as 99.23%. This FBG Haversian strain tube has the advantages of convenient operation and high displacement sensitivity, and is expected to be applied to the actual deep displacement monitoring of slopes in the future to prevent road uplift and settlement disasters.

Optics ExpressVol. 33(22)
Shanxi University of Traditional Chinese Medicine (CN)
Openalex Percentile: Top 72%
Advanced Fiber Optic Sensors
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