Deformation reconstruction of a smart Geogrid embedded with fiber Bragg grating sensors

Abstract

Due to the disadvantages of the current smart Geogrid for geotechnical use only being able measure strain and evaluate load location, a smart Geogrid embedded with fiber Bragg grating (FBG) sensors has been developed. Also, a deformation reconstruction technique has been investigated, which enables the newly designed smart Geogrid to evaluate the deformation fields of the key areas in geotechnical structures. After the fabricating process of the FBG embedded smart Geogrid was briefly introduced, a curvature information based deformation reconstruction method for the smart Geogrid was detailed. In order to optimize the distribution of the FBG nodes in the smart Geogrid, the finite element (FE) simulation data of the three possible causes of deformation were extracted, and the reconstruction results of the four distributions were compared. The results indicated that equidistantly distributed FBG sensors at the ribs of the smart Geogrid were the optimal distribution for the newly designed smart Geogrid. In addition, a modified deformation reconstruction technique was proposed to reduce reconstruction errors due to the stress concentration on the junctions of the smart Geogrid. The modified method, which employs FBG measured strains for calculating the deformation of the ribs and weighted strains to compute the coordinates of the two junctions, was validated by FE simulations. The simulation results illustrated that the modified method can improve the deformation reconstruction accuracy for both a Geogrid embedded with one fiber optic cable into one warp thread and a Geogrid embedded with multiple fiber optic cables in different warp threads. For the purpose of verifying the feasibility of the deformation measurements for the designed smart Geogrid using the proposed reconstruction techniques, experiments for the smart Geogrid embedded with one fiber optic cable were conducted in constant temperature environments. The curvatures of the smart Geogrid were calibrated prior to the deformation experiments in order to remove the errors induced by the strain measurement. The experimental results demonstrated that the reconstruction technique for the newly designed smart Geogrid was capable of evaluating the deformation field, and the modified reconstruction technique was able to effectively improve the reconstruction accuracy in order to fulfill the requirements of geotechnical usages. The newly developed smart Geogrid with deformation reconstruction techniques can be a promising smart Geosynthetic for the reinforcement as well as the monitoring of geotechnical engineering-related applications.

FBG-Based Monitoring of Geohazards: Current Status and Trends

“…The geotextile was not only capable of detecting minute deformation, but also provided a large resisting force against the landslide. Wang et al developed a smart geogrid embedded with FBG strain sensors [38,39]. The sensor features were evaluated through finite element simulation and lab model tests.…”

Development and Test of Geogrid with Distributed Deformation Monitoring Function

“…They conducted a series of experiments to verify that the smart geogrids exhibit good consistency in strain measurement and can accurately measure the local strain of geotechnical structures with small dimensions. Additionally, a deformation reconstruction technique has been investigated [17] which enables the smart geogrid to evaluate the deformation fields of the key areas in geotechnical structures. However, silica-based fiber sensors are limited in application due to their low break-down strain of only 1%, and they are fragile, requiring stricter packaging methods and installation procedures.…”

Design, Optimization and Improvement of FBG Flexible Sensor for Slope Displacement Profiles Measurement

“…In the field of geotechnical engineering, researchers have studied shape sensing methods for measuring displacement profiles in critical areas based on the FBG-embedded flexible sensors. Wang et al [21] fabricated an intelligent geogrid embedded with FBG sensors and employed a curvature-based reconstruction method to estimate the displacements related to geotechnical engineering. Kim et al [22] utilized a regression analysis method to measure the deflection curves, and subsequently adopted the method for the evaluation of bridge displacements.…”