Tunnel full-section deformation monitoring and early warning method integrating optical fiber and analog technology

Abstract

The present invention discloses a tunnel full-section deformation monitoring and early warning method that integrates optical fiber and simulation technology, and relates to the technical field of tunnel deformation monitoring. First, geological data of the tunnel area is obtained, a numerical model is established, and then the FLac3D geotechnical numerical simulation software is imported to obtain a corresponding three-dimensional numerical simulation model. After the physical parameters of the geotechnical body of the tunnel stratum are substituted into the corresponding model and an initial equilibrium calculation is performed, tunnel simulation excavation is performed in the model, and the initial equilibrium calculation is performed again. Distributed optical fiber / grating sensors are evenly arranged in the tunnel to acquire data on the deformation in the tunnel. After periodically acquiring actual deformation increments corresponding to the distributed optical fiber / grating sensors, the data are inserted into the established model to calculate relevant parameters, and the risk level of the target area is judged according to the calculation results. The present invention integrates optical fiber monitoring and simulation technology to monitor tunnel deformation, avoiding the defects of manual monitoring or artificially setting the deformation upper limit.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel safety monitoring, and in particular to a tunnel deformation monitoring method based on the combination of optical fiber and simulation technology. Technical Background

[0002] With the continuous increase in the mileage of subways, high-speed railways, and highways in my country, the number of mountain and underground tunnels has also increased rapidly. Unfavorable geological conditions and other external factors pose significant risks to the safe operation of tunnels, and tunnel deformation monitoring is receiving increasing attention. Traditional tunnel deformation monitoring requires manual monitoring of tunnel monitoring points during tunnel operation. Even with some methods, such as 3D laser scanning, these methods lack timeliness and safety, and cannot effectively capture micro-deformations within the tunnel. This makes it impossible to assess the risks posed by micro-deformations, and lacks timely and accurate early warning methods for the safety of the entire tunnel cross-section structure, posing certain risks to the safe operation of tunnels.

[0003] Although some technologies exist that use fiber optic / grating sensors to monitor tunnel deformation, these technologies require manual judgment on whether there is a deformation risk, resulting in a low level of intelligence. Alternatively, these technologies make autonomous judgments by manually setting an upper limit on deformation, but do not take into account conditions such as the tunnel's terrain, leading to a high risk of misjudgment. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a tunnel full-section deformation monitoring and early warning method that integrates optical fiber and simulation technology to solve the problems of low intelligence level and high risk of misjudgment in tunnel underground space deformation monitoring in the existing technology.

[0005] The technical solution is as follows:

[0006] The present invention provides a tunnel full-section deformation monitoring and early warning method integrating optical fiber and simulation technology, characterized in that the method comprises:

[0007] Step 1: Collect geological and hydrological data of the tunnel area and tunnel structure data to establish a numerical model;

[0008] Step 2: The established numerical model is meshed and imported into FLac3D geotechnical numerical simulation software to establish a three-dimensional numerical simulation model, wherein: the Mohr-Coulomb model is used as the stratum strength criterion, and the shell structure model is used as the lining structure;

[0009] Step 3: Obtain the geophysical parameters of each stratum in the tunnel area and assign them to the three-dimensional numerical simulation model obtained in Step 2. Take appropriate boundary conditions and perform initial equilibrium calculations.

[0010] Step 4: Excavate the three-dimensional numerical simulation model obtained in step 3 according to the actual working conditions of the tunnel to obtain a tunnel model. Use shell elements to simulate the lining structure on the surface of the obtained tunnel model to obtain a lining structure model. Obtain the physical parameters of the tunnel lining structure based on the engineering data and assign parameters to the lining structure model. Then, perform the initial equilibrium calculation again.

[0011] Step 5: Evenly distribute distributed fiber / grating sensors in the tunnel to obtain tunnel deformation values, and periodically obtain the tunnel deformation increment measured data corresponding to each distributed fiber / grating sensor and the total strain ε corresponding to the target area. i ;

[0012] Step 6: Determine the ultimate strain ε of the surrounding rock corresponding to the target area in the tunnel based on the three-dimensional numerical simulation model obtained in step 4. m , surrounding rock original rock stress σ in 、Original damage extension distance l in ; Assign all the measured data of tunnel deformation increments obtained for the i-th time in step 5 as the boundary conditions of the inner wall of the tunnel model obtained in step 4 to the three-dimensional numerical simulation model obtained in step 4, and calculate the equilibrium to obtain the stress σ in the target area i , damage extension distance l i ;

[0013] Step 7: Establish tunnel risk level warning standards:

[0014]

[0015] Among them, the stress concentration factor Incremental coefficient of surrounding rock failure extension distance strain rate ΔT is the acquisition period of the measured data of tunnel deformation increment.

[0016] The beneficial effects of the present invention are:

[0017] By using fiber optic sensors to obtain real data on tunnel deformation and then bringing it into the three-dimensional numerical model of the tunnel to calculate boundary conditions, we can effectively obtain data such as the strain limit corresponding to the target area, providing an efficient and accurate basis for determining whether there is a deformation risk. This makes it easier to determine the risk level based on the simulated data and the collected real data, and facilitate the subsequent formulation of corresponding emergency measures based on the risk level. DETAILED DESCRIPTION

[0018] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process. However, the protection scope of the present invention is not limited to the following embodiment.

[0019] Example

[0020] This embodiment provides a tunnel full-section deformation monitoring and early warning method that integrates optical fiber and simulation technologies. This method aims to integrate optical fiber monitoring technology with simulation technology to achieve the purpose of efficiently and accurately determining the deformation risk level in the tunnel. Specifically, the method includes:

[0021] Step 1: Collect geological and hydrological data of the tunnel area and tunnel structure data to establish a numerical model;

[0022] That is, as much geological data, hydrological data, and design data of the tunnel area as possible are collected to establish a numerical model corresponding to the tunnel area. At this time, the obtained numerical model does not include tunnel excavation settings, and then proceed to step 2.

[0023] Step 2: The established numerical model is meshed and imported into FLac3D geotechnical numerical simulation software to establish a three-dimensional numerical simulation model, wherein: the Mohr-Coulomb model is used as the stratum strength criterion, and the shell structure model is used as the lining structure;

[0024] The numerical model established by collecting data in step 1 is meshed according to the requirements of Flac3D geotechnical numerical simulation software and then imported into FLac3D geotechnical numerical simulation software to form a three-dimensional numerical simulation model. At this time, in the three-dimensional numerical simulation model formed, the Mohr-Coulomb model is selected as the bottom layer strength criterion, and the shell structure model is selected as the lining structure. After the establishment is completed, step 3 is performed.

[0025] Step 3: Obtain the geophysical parameters of each stratum in the tunnel area and assign them to the three-dimensional numerical simulation model obtained in Step 2. Take appropriate boundary conditions and perform initial equilibrium calculations.

[0026] That is, according to the requirements of the FLac3D geotechnical numerical simulation software, the geotechnical physical parameters (density, elastic modulus, Poisson's ratio, tensile strength, cohesion, and internal friction angle) of each stratum in the tunnel area are obtained and imported into the obtained three-dimensional numerical simulation model for assignment. After selecting appropriate boundary conditions in the software, the initial equilibrium calculation is performed, and then step 4 is performed.

[0027] Step 4: Excavate the three-dimensional numerical simulation model obtained in step 3 according to the actual working conditions of the tunnel to obtain a tunnel model. Use shell elements to simulate the lining structure on the surface of the obtained tunnel model to obtain a lining structure model. Obtain the physical parameters of the tunnel lining structure based on the engineering data and assign parameters to the lining structure model. Then, perform the initial equilibrium calculation again.

[0028] That is, according to the actual excavation conditions of the tunnel (including its specific dimensions, direction, etc.), the tunnel model is excavated in the three-dimensional numerical simulation model, that is, a complete tunnel model (including the tunnel itself and the corresponding external geological and topographical environment) is established. After the excavation is completed, the lining structure is simulated on the surface of the obtained tunnel model using shell elements to obtain a lining structure model. According to the engineering data, the physical parameters of the tunnel lining structure (density, elastic modulus, Poisson's ratio, thickness) are obtained and the lining structure model is parameterized. Then, the initial equilibrium calculation is performed again. At this time, the corresponding simulation of the tunnel and its surrounding environment is completed, and a complete tunnel model is established. Then, step 5 is performed.

[0029] Step 5: Evenly distribute distributed fiber / grating sensors in the tunnel to obtain tunnel deformation values, and periodically obtain the tunnel deformation increment measured data corresponding to each distributed fiber / grating sensor and the total strain ε corresponding to the target area. i ;

[0030] That is, distributed fiber optic / grating sensors are evenly arranged in the tunnel to obtain the real deformation value of the tunnel. The distributed fiber optic sensors can be evenly arranged in the extension direction of the tunnel, or can be arranged sequentially on the cross section of the tunnel, or a combination of the above two methods, that is, to ensure that the deformation data of the tunnel can be collected in all directions; secondly, distributed grating sensors can be arranged in key areas to perform corresponding detection; after the distributed fiber optic / grating sensors are arranged, data is acquired periodically, and each acquired data is compared with the previous acquired data to obtain the corresponding strain change rate, and is also compared with the initial data to obtain the total strain ε i , which makes it easier to perform strain simulation later, i.e., proceed to step 6.

[0031] Step 6: Determine the ultimate strain ε of the surrounding rock corresponding to the target area in the tunnel based on the three-dimensional numerical simulation model obtained in step 4. m , surrounding rock original rock stress σ in 、Original damage extension distance l in , that is, according to the obtained model, the corresponding value is determined by the model; all the tunnel deformation increment measured data (total strain) obtained in step 5 for the i-th time are assigned as the boundary conditions of the inner wall of the tunnel model obtained in step 4 to the three-dimensional numerical simulation model obtained in step 4, and the equilibrium is calculated to obtain the stress σ of the target area i , damage extension distance l i , obtained by substituting the obtained data into the model;

[0032] Step 7: Establish tunnel risk level warning standards:

[0033]

[0034] Among them, the stress concentration factor Incremental coefficient of surrounding rock failure extension distance strain rate ΔT is the acquisition period of the measured data of tunnel deformation increment.

[0035] In this method, each sensor can be powered by a combination of solar energy, mains electricity, preset batteries, etc. At the same time, each sensor is also connected to a data transceiver platform, and the data transceiver platform transmits wireless data with external devices, thereby facilitating remote viewing and reception of relevant data.

[0036] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A tunnel full-section deformation monitoring and early warning method integrating optical fiber and simulation technology, characterized in that: The method includes: Step 1: Collect geological and hydrological data of the tunnel area and tunnel structure data to establish a numerical model; Step 2: The established numerical model is meshed and imported into FLac3D geotechnical numerical simulation software to establish a three-dimensional numerical simulation model, wherein: the Mohr-Coulomb model is used as the stratum strength criterion, and the shell structure model is used as the lining structure; Step 3: Obtain the geophysical parameters of each stratum in the tunnel area and assign them to the three-dimensional numerical simulation model obtained in Step 2. Take the boundary conditions and perform initial equilibrium calculations. Step 4: Excavate the three-dimensional numerical simulation model obtained in step 3 according to the actual working conditions of the tunnel to obtain a tunnel model. Use shell elements to simulate the lining structure on the surface of the obtained tunnel model to obtain a lining structure model. Obtain the physical parameters of the tunnel lining structure based on the engineering data and assign parameters to the lining structure model. Then, perform the initial equilibrium calculation again. Step 5: Evenly distribute distributed fiber / grating sensors in the tunnel to obtain tunnel deformation values, and periodically obtain the tunnel deformation increment measured data corresponding to each distributed fiber / grating sensor and the total strain ε corresponding to the target area. i ; Step 6: Determine the ultimate strain ε of the surrounding rock corresponding to the target area in the tunnel based on the three-dimensional numerical simulation model obtained in step 4. m , surrounding rock original rock stress σ in , original damage extension distance l in ; Assign all the measured data of tunnel deformation increments obtained for the i-th time in step 5 as the boundary conditions of the inner wall of the tunnel model obtained in step 4 to the three-dimensional numerical simulation model obtained in step 4, and calculate the equilibrium to obtain the stress σ in the target area i , damage extension distance l i ; Step 7: Establish tunnel risk level warning standards: in: ε i <0.4ε m , ε v <0.2ε m , α i <2 and Δ i When it is less than 1.2, it is risk-free; 0.4ε m ≤ε i <0.6ε m , 0.2ε m ≤ε v <0.3ε m , 2≤α i <4 and 1.2≤Δ i When it is less than 1.6, it is level 3 risk; 0.6ε m ≤ε i <0.8ε m , 0.3ε m ≤ε v <0.4ε m 、4≤α i <6 and 1.6≤Δ i When it is less than 2.0, it is a level 2 risk; ε i ≥ε m , ε v ≥0.4ε m , α i ≥6 and Δ i When ≥2, it is risky; Among them, the stress concentration factor Incremental coefficient of surrounding rock failure extension distance strain rate ΔT is the acquisition period of the measured data of tunnel deformation increment.

Images