Shield tunnel online monitoring system

Abstract

The present invention relates to the field of performance monitoring technology, specifically to an online monitoring system for shield tunnels, the system comprising: a real-time data acquisition module collects data on shield machine cutter disc wear and geological conditions in real time based on the cutter disc wear state and geological data, analyzes the wear mode of the contact between the cutter disc and the rock and soil, identifies the current construction environment, and obtains real-time geotechnical mechanical parameters and construction conditions. In the present invention, through real-time monitoring and refined geological condition analysis, it is possible to accurately grasp the key parameters in the tunnel excavation process, optimize the construction strategy, and enhance the adaptability to complex geological changes. The risk assessment and early warning mechanism can timely discover and respond to possible safety issues, thereby reducing the accident rate and ensuring the safety of construction personnel and equipment. By analyzing the predicted geological conditions, the excavation path is adjusted to adapt to the geological difficulties that may be encountered in the future, thereby achieving greater flexibility in project management and reducing potential economic losses.

Description

Technical Field

[0001] The invention relates to the technical field of performance monitoring, and in particular to an online monitoring system for a shield tunnel. Background Art

[0002] The field of performance monitoring technology involves the use of various sensors, instruments and software tools to collect and analyze the operating data of machines, equipment or systems in real time. The core goal of this technology is to ensure the efficiency, safety and reliability of equipment operation. Through the continuous monitoring of key performance indicators, potential failures and performance degradation can be discovered in time, so that preventive measures can be taken or necessary maintenance can be performed. In addition, performance monitoring technology also supports the optimization of operating processes and the improvement of production efficiency. It is widely used in many fields such as manufacturing, energy management, transportation infrastructure and construction engineering.

[0003] Among them, the shield tunnel online monitoring system refers to a real-time monitoring and data analysis system specifically used in the shield tunnel construction process. The system collects key information such as geological conditions, machine status, construction parameters, etc. during tunneling in real time by installing a variety of sensors on the shield machine. Its uses include monitoring the operating status of the shield machine, predicting and preventing potential structural problems, and optimizing the speed and safety of tunneling. This system greatly improves the safety and efficiency of tunnel construction and is an indispensable technical tool for modern urban underground construction.

[0004] Although existing technologies can provide basic equipment performance monitoring, their adaptability and predictive capabilities for complex geological conditions are still insufficient in specific applications such as shield tunnel construction. Existing systems may face delays in real-time processing and analysis of large-scale geological and mechanical data, affecting timely responses to geological mutations. Such technologies lack in-depth analysis of stress distribution and geological risks during construction, making it difficult to adjust the excavation path in time to cope with unpredicted geological conditions, which may lead to a significant decrease in construction safety and efficiency. In addition, traditional monitoring technologies often cannot provide sufficient data support to accurately predict structural problems, which limits project risk management capabilities and increases project uncertainty and potential risks. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and to propose an online monitoring system for a shield tunnel.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: The shield tunnel online monitoring system comprises:

[0007] The real-time data acquisition module collects the cutterhead wear and geological condition data of the shield machine in real time based on the cutterhead wear status and geological data collection, analyzes the wear mode of the contact between the cutterhead and the rock and soil, identifies the current construction environment, obtains the real-time geotechnical mechanical parameters and construction conditions, and integrates them into real-time monitoring synthetic data;

[0008] The data analysis and optimization module calculates the stress distribution under the current geological conditions based on the real-time monitoring synthetic data, simulates the influence of differentiated geotechnical parameters and construction conditions on the stress field, determines the geotechnical parameters matching the current geological environment by evaluating the stability of the stress field and the parameter fitting, and establishes the optimal geotechnical parameters;

[0009] The path adjustment module calculates the feasibility and geological risk of the tunneling path based on the optimal geotechnical parameters, predicts the geological conditions that the shield machine will encounter in the future, and establishes an adjusted tunneling path;

[0010] Based on the adjusted excavation path, the risk management module monitors the stratum hardness, water level and geological fracture distribution along the path, and compares the risk safety standard threshold. If it is found that the data exceeds the safety range, the degree of excess is calculated and the risk level is re-evaluated to obtain the risk assessment result.

[0011] As a further solution of the present invention, the step of acquiring the real-time monitoring synthetic data is specifically as follows:

[0012] Based on the cutterhead wear status and geological data collection, the cutterhead wear and geological condition data of the shield machine are collected in real time, and the average geological hardness and wear index are calculated using the formula:

[0013]

[0014] Obtain preliminary geological hardness data;

[0015] Among them, P represents the average geological hardness, N represents the number of monitoring points, and p i represents the geological hardness of the i-th monitoring point, and γ is the hardness adjustment coefficient;

[0016] Integrate the wear data with the geological hardness data using the formula:

[0017]

[0018] Computationally generate geotechnical wear models;

[0019] Where H represents the rock wear model, w i represents the i-th wear monitoring point, δ is the wear adjustment coefficient, and θ is the offset coefficient;

[0020] Based on the rock and soil wear model, combined with construction conditions and rock and soil mechanics parameters, the formula is adopted:

[0021]

[0022] Obtain real-time monitoring synthetic data;

[0023] Among them, S represents real-time monitoring synthetic data, and α and β are adjustment parameters.

[0024] As a further solution of the present invention, the step of obtaining the stress distribution is specifically as follows:

[0025] The geotechnical properties and cutterhead wear status are extracted from the real-time monitoring synthetic data using the formula:

[0026]

[0027] Calculate the weighted average stress distribution of N monitoring points and generate preliminary stress distribution data;

[0028] Among them, σ ij represents the stress distribution in the i, j direction, ω k represents the weight of the kth monitoring point, x kij represents the geotechnical properties of the kth monitoring point in the i, j direction, λ is the attenuation coefficient, and N represents the number of monitoring points;

[0029] Based on the preliminary stress distribution data, the stress distribution is adjusted through the variability analysis of geotechnical parameters, using the formula:

[0030]

[0031] Calculate and generate adjusted stress distribution data;

[0032] Among them, τ ij represents the adjusted stress distribution, μ is the geotechnical property adjustment factor, D represents the geotechnical heterogeneity measure, and θ' is the constant threshold;

[0033] Based on the adjusted stress distribution data and combined with the construction conditions, the formula is adopted:

[0034]

[0035] Calculate the adaptability of the adjusted stress distribution data under the current geological environment and generate stress distribution;

[0036] Where Φ represents the stress distribution, ρ ij is the density factor of geological conditions, and M is the total number of reference directions.

[0037] As a further solution of the present invention, the steps for obtaining the optimal geotechnical parameters are specifically as follows:

[0038] Extract geotechnical properties from real-time monitoring synthetic data using the formula:

[0039]

[0040] Differentiated geotechnical parameters are calculated;

[0041] Among them, Γ is the differentiated geotechnical parameter, γ k is the weight of the kth monitoring point, x k is the geotechnical property of the kth monitoring point, f(x k ) represents the k Standardized operations;

[0042] Using the differentiated geotechnical parameters, the formula is adopted:

[0043]

[0044] Evaluate the stability and parameter fit of the stress field and generate calibrated geotechnical parameters;

[0045] Among them, Ψ is the calibrated geotechnical parameter, ξ is the bias adjustment parameter, β' and α' are the calibration coefficient and sensitivity parameter respectively;

[0046] Combining the construction conditions and the calibrated geotechnical parameters, the formula is adopted:

[0047]

[0048] Determine the geotechnical parameters that match the current geological environment and establish the optimal geotechnical parameters;

[0049] Among them, Ω is the optimal geotechnical parameter.

[0050] As a further solution of the present invention, the step of obtaining the adjusted excavation path is specifically as follows:

[0051] Based on the optimal geotechnical parameters, the feasibility of the excavation path is calculated using the formula:

[0052]

[0053] Generate a feasibility score for the excavation path;

[0054] Among them, F is the feasibility score of the excavation path, k' and C are the sensitivity coefficient and the excavation condition threshold, respectively, and Ω i represents the optimal geotechnical parameters of the i-th segment, M1 represents the number of segments on the path;

[0055] Using the feasibility score of the tunneling path described, the future geological conditions are predicted using the formula:

[0056]

[0057] Calculate and generate geological risk assessment results;

[0058] Among them, G is the result of geological risk assessment, F i is the feasibility score of the i-th segment, Ω i is the geotechnical parameter of the i-th section;

[0059] Based on the geological risk assessment results, the adjusted excavation path is determined using the formula:

[0060]

[0061] Calculate and establish adjusted excavation paths;

[0062] Among them, P new is the comprehensive score of the adjusted excavation path, G i is the geological risk of the i-th section.

[0063] As a further solution of the present invention, the steps of obtaining the risk assessment results are specifically as follows:

[0064] Based on the adjusted excavation path, the ground hardness, water level and geological fracture distribution along the path are monitored, using the formula:

[0065]

[0066] Calculate the overall geological state and generate a comprehensive geological state score;

[0067] Among them, h, w, d i are the monitoring data of formation hardness, water level and geological fracture distribution, X is the comprehensive score of geological status, a, b, c, d, l and f are adjustment factors, which enhance the influence and nonlinear effect of hardness, water level and fracture data;

[0068] The comprehensive geological status score is used to compare the safety standard threshold T of the risk, using the formula:

[0069]

[0070] If x i >t, the degree to which each monitoring point exceeds the safety range is calculated to generate a metric that exceeds the safety range;

[0071] Where Y is the measure beyond the safety range, g and h' are the nonlinear and regularization effects that enhance the measure beyond the safety range;

[0072] Based on the measure of exceeding the safety range, the risk level is re-evaluated using the formula:

[0073]

[0074] Calculate and obtain risk assessment results;

[0075] Among them, R is the risk assessment result and s is the risk sensitivity coefficient.

[0076] Compared with the prior art, the advantages and positive effects of the present invention are:

[0077] In the present invention, the safety and efficiency of the shield tunnel construction process are significantly improved through real-time data-driven analysis and differentiated geotechnical parameter simulation. Real-time monitoring and refined geological condition analysis enable accurate grasp of key parameters in the tunnel excavation process, optimization of construction strategies, and enhanced adaptability to complex geological changes. Risk assessment and early warning mechanisms can promptly detect and respond to possible safety issues, thereby reducing the accident rate and ensuring the safety of construction personnel and equipment. By analyzing the predicted geological conditions, the excavation path is adjusted to adapt to the geological difficulties that may be encountered in the future, thereby achieving greater flexibility in project management and reducing potential economic losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 is a system flow chart of the present invention;

[0079] Figure 2 A flowchart of the steps for obtaining the synthetic data for real-time monitoring of the present invention;

[0080] Figure 3 A flow chart of the steps for obtaining stress distribution of the present invention;

[0081] Figure 4 Flow chart of the steps for obtaining the optimal geotechnical parameters of the present invention;

[0082] Figure 5 A flow chart of the steps for obtaining the adjusted excavation path of the present invention;

[0083] Figure 6 The figure is a flow chart of the steps for obtaining the risk assessment results of the present invention. DETAILED DESCRIPTION

[0084] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0085] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0086] Embodiment 1

[0087] See also Figure 1 , the shield tunnel online monitoring system includes:

[0088] The real-time data acquisition module collects the cutterhead wear and geological condition data of the shield machine in real time based on the cutterhead wear status and geological data collection, analyzes the wear mode of the contact between the cutterhead and the rock and soil, identifies the current construction environment, obtains the real-time geotechnical mechanical parameters and construction conditions, and integrates them into real-time monitoring synthetic data;

[0089] The data analysis and optimization module calculates the stress distribution under the current geological conditions based on real-time monitoring synthetic data, simulates the influence of differentiated geotechnical parameters and construction conditions on the stress field, determines the geotechnical parameters that match the current geological environment by evaluating the stability of the stress field and the degree of parameter fit, and establishes the optimal geotechnical parameters;

[0090] The path adjustment module calculates the feasibility and geological risks of the tunneling path based on the optimal geotechnical parameters, predicts the geological conditions that the shield machine will encounter in the future, and establishes the adjusted tunneling path;

[0091] Based on the adjusted excavation path, the risk management module monitors the stratum hardness, water level and geological fracture distribution along the path and compares the risk safety standard threshold. If it is found that the data exceeds the safety range, the degree of excess is calculated and the risk level is re-evaluated to obtain the risk assessment result.

[0092] Real-time monitoring synthetic data include geotechnical mechanical parameters and construction conditions. The optimal geotechnical parameters include stress distribution, geotechnical parameter fitting degree, and stress field stability. The adjusted excavation path includes the feasibility of the excavation path and geological risks. The risk assessment results specifically include the re-evaluated risk level and analysis of the degree of exceeding the standard.

[0093] See also Figure 2 ,The specific steps for obtaining real-time monitoring synthetic data are:

[0094] Based on the cutterhead wear status and geological data collection, the cutterhead wear and geological condition data of the shield machine are collected in real time, and the average geological hardness and wear index are calculated using the formula:

[0095]

[0096] Obtain preliminary geological hardness data;

[0097] Among them, P represents the average geological hardness, N represents the number of monitoring points, and p i represents the geological hardness of the i-th monitoring point, and γ is the hardness adjustment coefficient;

[0098] Integrate wear data with geological hardness data using the formula:

[0099]

[0100] Computationally generate geotechnical wear models;

[0101] Where H represents the rock wear model, w i represents the i-th wear monitoring point, δ is the wear adjustment coefficient, and θ is the offset coefficient;

[0102] Based on the rock and soil wear model, combined with construction conditions and rock and soil mechanics parameters, the formula is adopted:

[0103]

[0104] Obtain real-time monitoring synthetic data;

[0105] Among them, S represents real-time monitoring synthetic data, and α and β are adjustment parameters.

[0106] Step 1: Calculation of average geological hardness P

[0107] formula:

[0108]

[0109] Parameter Description:

[0110] N: number of monitoring points, indicating the number of geological hardness samples collected.

[0111] p i : The geological hardness of the ith monitoring point.

[0112] γ: Hardness adjustment factor, used to adjust the calculation of geological hardness to better reflect the actual wear effects.

[0113] Assume the following example:

[0114] Assume that there are three geological hardness monitoring points: p1 = 50, p2 = 60, p3 = 70. Assume that the adjustment coefficient γ = 1.2.

[0115] Calculation process:

[0116] Calculate the adjustment value for each geological hardness monitoring point:

[0117] 50 1.5 ×1.2=424.26

[0118] 60 1.5 ×1.2=659.75

[0119] 70 1.5 ×1.2=946.32

[0120] Sum:

[0121] 424.26+659.75+946.32=2030.33

[0122] Calculate the average:

[0123]

[0124] Result interpretation:

[0125] The average geological hardness obtained, P = 676.78, represents the average effect of the actual construction environment on wear after adjustment.

[0126] Step 2: Calculation of geotechnical wear model H

[0127] formula:

[0128]

[0129] Parameter Description:

[0130] w i : The i-th wear monitoring point.

[0131] P: Average geological hardness obtained from step 1.

[0132] δ: Wear adjustment factor.

[0133] θ: Offset factor, used to balance wear data.

[0134] Assume the following example:

[0135] Assume the wear monitoring points are w1 = 0.8, w2 = 0.9, w3 = 1.0. From step 1, P = 676.78. Assume δ = 0.95, θ = 2.

[0136] Calculation process:

[0137] Calculate the adjustment value for each wear monitoring point:

[0138] 0.8·(676.78+1) 0.5 -2|×0.95=20.84

[0139] 0.9·(676.78+1) 0.5 -2|×0.95=23.44

[0140] 1.0·(676.78+1) 0.5 -2|×0.95=26.05

[0141] Sum:

[0142] 20.84+23.44+26.05=70.33

[0143] Calculate the average:

[0144]

[0145] Result interpretation:

[0146] The obtained rock and soil wear model H = 23.44 represents the average wear degree after adjustment and balance.

[0147] Step 3: Real-time monitoring of the computation of synthetic data S

[0148] formula:

[0149]

[0150] Parameter Description:

[0151] H: Geotechnical wear model obtained from step 2.

[0152] α and β: Adjustment parameters used to adjust the final output according to the construction conditions.

[0153] Assume the following example:

[0154] H = 23.44 from step 2. Assume α = 3.5, β = 5.

[0155] Calculation process:

[0156] Calculate the value of S:

[0157]

[0158] Result interpretation:

[0159] The obtained real-time monitoring synthetic data S = 21.94 represents the monitoring result after comprehensive consideration of geological hardness and wear data, and is used for actual construction monitoring and adjustment.

[0160] See also Figure 3 , the specific steps for obtaining stress distribution are:

[0161] The geotechnical properties and cutterhead wear status are extracted from the real-time monitoring synthetic data using the formula:

[0162]

[0163] Calculate the weighted average stress distribution of N monitoring points and generate preliminary stress distribution data;

[0164] Among them, σ ij represents the stress distribution in the i, j directions, ω k represents the weight of the kth monitoring point, x kij represents the geotechnical properties of the kth monitoring point in the i, j direction, λ is the attenuation coefficient, and N represents the number of monitoring points;

[0165] Based on the preliminary stress distribution data, the stress distribution is adjusted through the variability analysis of geotechnical parameters, using the formula:

[0166]

[0167] Calculate and generate adjusted stress distribution data;

[0168] Among them, τ ij represents the adjusted stress distribution, μ is the geotechnical property adjustment factor, D represents the geotechnical heterogeneity measure, and θ' is the constant threshold;

[0169] Based on the adjusted stress distribution data and combined with the construction conditions, the formula is adopted:

[0170]

[0171] Calculate the adaptability of the adjusted stress distribution data under the current geological environment and generate stress distribution;

[0172] Where Φ represents the stress distribution, ρ ij is the density factor of geological conditions, and M is the total number of reference directions.

[0173] Detailed explanation of formula and calculation process

[0174] Step 1 formula:

[0175]

[0176] Parameter details:

[0177] σ ij : Stress distribution in i, j directions.

[0178] N: number of monitoring points.

[0179] ω k: The weight of the kth monitoring point is assigned according to the accuracy of the monitoring equipment or the importance of the monitoring point.

[0180] λ: Attenuation coefficient, which controls the influence of geotechnical properties on stress distribution.

[0181] x kij : Geotechnical characteristic parameters of the kth monitoring point in the i, j direction, including rock hardness, density, etc.

[0182] Calculation process and examples:

[0183] Assumptions:

[0184] N=3 (three monitoring points)

[0185] ω1=0.3, ω2=0.5, ω3=0.2

[0186] λ=0.1

[0187] x 1ij =2,x 2ij =1.5,x 3ij =3

[0188] Calculate σ ij :

[0189] Calculate the contribution of each monitoring point:

[0190] Contribution 1: 0.3 e -0.1 · 22 =0.3·e -0.4 ≈0.3·0.67032=0.201096

[0191] Contribution 2: 0.5 e -0.1 · 1.52 =0.5·e -0.225 ≈0.5·0.798516=0.399258

[0192] Contribution 3: 0.2 e -0.1 · 32 =0.2·e -0.9 ≈0.2·0.40657=0.081314

[0193] Summarize and calculate the mean stress distribution:

[0194] Result interpretation:

[0195] The obtained σ ij ≈0.227 represents the average stress distribution in the i, j direction. This value takes into account the influence of geotechnical properties and their spatial distribution.

[0196] Step 2 formula:

[0197]

[0198] Parameter details:

[0199] τ ij : Adjusted stress distribution.

[0200] σ ij : Original stress distribution.

[0201] μ: Geotechnical property adjustment coefficient, which takes into account the additional impact of geotechnical parameters on stress distribution.

[0202] D: Measurement of the heterogeneity of rock and soil.

[0203] θ': A small constant to prevent division by zero errors.

[0204] Calculation process and examples:

[0205] Assumptions:

[0206] μ=0.05

[0207] D=0.8

[0208] θ'=0.01

[0209] Use the σ calculated in step 1 ij =0.227

[0210] Calculate the adjusted stress distribution: Result interpretation:

[0211] The obtained τ ij ≈0.486 represents the adjusted stress distribution after considering the heterogeneity of geotechnical properties.

[0212] Step 3 formula:

[0213]

[0214] Parameter details:

[0215] Φ: Final stress distribution, taking into account the adjusted stress distribution in multiple directions τ ij .

[0216] τ ij : Adjusted stress distribution, obtained from step 2.

[0217] ρ ij : Density factor of geological conditions, which affects the calculation of stress distribution.

[0218] M: Total number of directions, indicating how many directions the stress distribution calculation is performed in.

[0219] Calculation process and examples:

[0220] Assumptions:

[0221] M = 3 (consider three directions, assuming that the stress distribution calculation in each direction is the same)

[0222] ρ ij =0.1 (assuming the geological density factor is the same in all directions)

[0223] Use the τ calculated in step 2 ij =0.486

[0224] Calculate the adjusted stress distribution in each direction:

[0225] Direction 1:

[0226] Direction 2: (same direction 1)

[0227] Direction 3: (same direction 1)

[0228] Sum and calculate the average:

[0229]

[0230] Result interpretation:

[0231] The obtained Φ = 0.442 represents the average adjusted stress distribution after integrating all considered directions. This value reflects the overall influence of geological conditions and balances the stress data in different directions.

[0232] See also Figure 4 , the steps to obtain the optimal geotechnical parameters are as follows:

[0233] Extract the geotechnical properties and cutterhead wear status from the real-time monitoring synthetic data using the formula:

[0234]

[0235] Differentiated geotechnical parameters are calculated;

[0236] Among them, Γ is the differentiated geotechnical parameter, γ k is the weight of the kth monitoring point, x k is the geotechnical characteristics of the kth monitoring point;

[0237] Using differentiated geotechnical parameters, the formula is adopted:

[0238]

[0239] Evaluate the stability and parameter fit of the stress field and generate calibrated geotechnical parameters;

[0240] Among them, Ψ is the calibrated geotechnical parameter, ξ is the bias adjustment parameter, β' and α' are the calibration coefficient and sensitivity parameter respectively;

[0241] Combining the construction conditions and calibrated geotechnical parameters, the formula is adopted:

[0242]

[0243] Determine the geotechnical parameters that match the current geological environment and establish the optimal geotechnical parameters;

[0244] Among them, Ω is the optimal geotechnical parameter.

[0245] Step 1: Calculate the differentiated geotechnical parameter Γ

[0246] formula

[0247]

[0248] Parameters

[0249] Γ: Differentiated geotechnical parameter, representing the weighted average of geotechnical properties extracted from real-time data.

[0250] N: the number of monitoring points.

[0251] γ k : The weight of the kth monitoring point, representing the importance of the data at this point.

[0252] x k : Geotechnical properties of the kth monitoring point, including rock hardness, humidity, etc.

[0253] f(x k ): a function that processes x k The data is simply normalized or subjected to other mathematical operations.

[0254] Calculation example

[0255] Assume there are 3 monitoring points, where:

[0256] x1=100,γ1=0.3

[0257] x2=150,γ2=0.4

[0258] x3=200,γ3=0.3

[0259] Assume that f(x k )=x k / 100, then:

[0260]

[0261]

[0262]

[0263]

[0264] This result indicates that the average geotechnical characteristic parameter of each point is Γ = 0.5, which is calculated by weighted average.

[0265] Step 2: Calibrated geotechnical parameters Ψ

[0266] formula

[0267]

[0268] Parameters

[0269] Ψ: calibrated geotechnical parameter used to adjust the preliminary parameters to better match the actual conditions.

[0270] β': Calibration coefficient used to adjust the influence of the parameter.

[0271] α', ξ: sensitivity and bias of adjustment parameters.

[0272] Calculation example

[0273] Assumptions:

[0274] β'=2, α'=0.1, ξ=120

[0275] Using the previous value of Γ and x k .

[0276]

[0277] For x1=100:

[0278]

[0279] For x2=150:

[0280]

[0281] For x3=200:

[0282]

[0283] These calculations illustrate how the geotechnical parameters at each point can be adjusted by nonlinear functions to better reflect the variability of actual geological conditions.

[0284] Step 3: Final geotechnical parameters Ω

[0285] formula

[0286]

[0287] Parameters

[0288] Ω: The final determined geotechnical parameter, which is the average value of the calibrated parameter.

[0289] Calculation example

[0290] Combining the previous steps k value:

[0291]

[0292]

[0293] This Ω value represents the average geotechnical parameter obtained after comprehensive consideration of the data from all monitoring points, and is applicable to the current geological environment.

[0294] See also Figure 5 , the specific steps for obtaining the adjusted excavation path are:

[0295] Based on the optimal geotechnical parameters, the feasibility of the excavation path is calculated using the formula:

[0296]

[0297] Generate a feasibility score for the excavation path;

[0298] Among them, F is the feasibility score of the excavation path, k' and C are the sensitivity coefficient and the excavation condition threshold respectively;

[0299] Use the tunneling path feasibility score to predict future geological conditions using the formula:

[0300]

[0301] Calculate and generate geological risk assessment results;

[0302] Among them, G is the result of geological risk assessment, F i is the feasibility score of the i-th segment, Ω i is the geotechnical parameter of the i-th section;

[0303] Based on the geological risk assessment results, the adjusted excavation path is determined using the formula:

[0304]

[0305] Calculate and establish adjusted excavation paths;

[0306] Among them, P newis the comprehensive score of the adjusted excavation path, G i is the geological risk of the i-th section.

[0307] Detailed explanation of the formula for step 1

[0308] formula:

[0309]

[0310] Parameter explanation:

[0311] F: Excavation path feasibility score, indicating the average feasibility of the entire path.

[0312] M1: Indicates the number of segments on the path.

[0313] Ω i : Optimal geotechnical parameters of the ith section.

[0314] k': sensitivity coefficient, which affects the sensitivity of the score to differences in geotechnical parameters.

[0315] C: Excavation condition threshold, which is the key geotechnical parameter threshold that determines the feasibility of the path.

[0316] Calculation example:

[0317] Assume that there are 5 sections of excavation path, and the geotechnical parameters of each section are Ω=[2,3,5,4,2], k'=

[0318] 0.5, C = 3. The calculation process is as follows:

[0319] Calculate the feasibility score for each segment:

[0320] When Ω1=2:

[0321] When Ω2=3:

[0322] When Ω3=5:

[0323] When Ω4=4:

[0324] When Ω5=2:

[0325] Average Feasibility Rating:

[0326]

[0327] This result F=0.5217 represents the average feasibility score of the entire excavation path, which is closer to the threshold, indicating that the path is feasible as a whole, but there are certain risks.

[0328] Detailed explanation of the formula for step 2

[0329] formula:

[0330]

[0331] Parameter explanation:

[0332] G: Geological risk assessment results, reflecting the risk level of predicted future geological conditions.

[0333] F i : The feasibility score of the i-th segment, obtained from step 1.

[0334] Ω i : Geotechnical parameters of the ith section.

[0335] Calculation example:

[0336] Calculate G using the feasibility score and geotechnical parameters from step 1:

[0337]

[0338] This G = 1.231 represents the result of geological risk assessment, and a lower value implies a relatively lower risk.

[0339] Detailed explanation of the formula for step 3

[0340] formula:

[0341]

[0342] Parameter explanation:

[0343] P new : Adjusted excavation path, comprehensive score.

[0344] G i 、F i : Geological risk and feasibility score for segment i.

[0345] Calculation example:

[0346] Assume G i =G for all i:

[0347]

[0348] This P=0.509 represents the comprehensive score of the adjusted excavation path. The high or low value of this value reflects the overall risk and feasibility of the excavation path.

[0349] See also Figure 6 , the specific steps for obtaining risk assessment results are:

[0350] Based on the adjusted excavation path, the ground hardness, water level and geological fracture distribution along the path are monitored using the formula:

[0351]

[0352] Calculate the overall geological state and generate a comprehensive geological state score;

[0353] Among them, h, w, and d are the monitoring data of formation hardness, water level and geological fracture distribution, respectively; X is the comprehensive score of geological status; a, b, c, d, l, and f are adjustment factors, respectively, to enhance the influence and nonlinear effect of hardness, water level and fracture data;

[0354] Using the comprehensive geological status score, we can compare the safety standard threshold T of the risk using the formula:

[0355]

[0356] If x i >t, the degree to which each monitoring point exceeds the safety range is calculated to generate a metric that exceeds the safety range;

[0357] Where Y is the measure beyond the safety range, g and h' are the nonlinear and regularization effects that enhance the measure beyond the safety range;

[0358] Based on the measurement beyond the safety range, re-evaluate the risk level using the formula:

[0359]

[0360] Calculate and obtain risk assessment results;

[0361] Among them, R is the risk assessment result and s is the risk sensitivity coefficient.

[0362] Detailed explanation and example of formula 1

[0363] formula:

[0364]

[0365] Parameter explanation:

[0366] N: the number of monitoring points.

[0367] a, b, c, d, l, f: coefficients used to enhance the influence and nonlinear effects of hardness, water level and crack data.

[0368] h i , w i , d i : The formation hardness, water level and crack data of the i-th monitoring point.

[0369] Assumed parameters:

[0370] N = 3 (number of monitoring points)

[0371] a=1,b=2,c=0.5,d=1,l=0.3,f=3 (adjustment coefficient)

[0372] h i =[2,3,4],w i =[1,1.5,2],d i =[0.2,0.3,0.1](hardness, water level and crack data)

[0373] Calculation process:

[0374] Calculate the combined contribution of each monitoring point:

[0375] Contribution1=1·2 2 +0.5 1 1 +0.3 0.2 3 ≈4.006

[0376] Contribution2=1·3 2 +0.5 1.5 1 +0.3 0.3 3 ≈9.009

[0377] Contribution3=1·4 2 +0.5 2 1 +0.3 0.1 3 ≈16.50003

[0378] Calculate the comprehensive geological status score X:

[0379]

[0380] Example results:

[0381] The comprehensive score X≈9.84 represents the overall geological status of the monitoring site, taking into account the combined effects of hardness, water level, and cracks.

[0382] Detailed explanation and example of formula 2

[0383] formula:

[0384]

[0385] Parameter explanation:

[0386] x i : The geological status score of the ith monitoring point.

[0387] t: safety threshold.

[0388] g, h': coefficients used to enhance the nonlinear and regularization effects of the metric beyond the safety range.

[0389] Assumed parameters:

[0390] t=10(safety threshold)

[0391] g=2,h'=0.5(adjustment coefficient)

[0392] Calculation process:

[0393] Calculate the measure of safety margin exceeded for each monitoring point:

[0394]

[0395]

[0396]

[0397] Calculate the total measure Y that exceeds the safety limit:

[0398]

[0399] Example results:

[0400] The total metric Y≈158.05 represents the total degree to which the entire monitoring area exceeds the safety threshold and is a comprehensive risk indicator.

[0401] Detailed explanation and example of formula 3

[0402] formula:

[0403]

[0404] Parameter explanation:

[0405] y i : The measure of exceeding the safety range of the ith monitoring point.

[0406] s: risk sensitivity coefficient.

[0407] Assumed parameters:

[0408] s=10(risk sensitivity coefficient)

[0409] Calculation process:

[0410] Calculate risk level:

[0411]

[0412] Example results:

[0413] The risk assessment result R≈5.27 represents the overall risk level, with lower values ​​indicating that the overall risk is acceptable, but attention should still be paid to specific high-risk areas.

[0414] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. The shield tunnel online monitoring system is characterized by: The system comprises: The real-time data acquisition module collects the cutterhead wear and geological condition data of the shield machine in real time based on the cutterhead wear status and geological data collection, analyzes the wear mode of the contact between the cutterhead and the rock and soil, identifies the current construction environment, obtains the real-time geotechnical mechanical parameters and construction conditions, and integrates them into real-time monitoring synthetic data; The data analysis and optimization module calculates the stress distribution under the current geological conditions based on the real-time monitoring synthetic data, simulates the influence of differentiated geotechnical parameters and construction conditions on the stress field, determines the geotechnical parameters matching the current geological environment by evaluating the stability of the stress field and the parameter fitting, and establishes the optimal geotechnical parameters; The steps for obtaining the optimal geotechnical parameters are specifically as follows: Extract geotechnical properties from real-time monitoring synthetic data using the formula: Differentiated geotechnical parameters are calculated; Among them, Γ is the differentiated geotechnical parameter, γ k is the weight of the kth monitoring point, x k is the geotechnical property of the kth monitoring point, f(x k ) represents the k Standardization operation, N represents the number of monitoring points; Using the differentiated geotechnical parameters, the formula is adopted: Evaluate the stability and parameter fit of the stress field and generate calibrated geotechnical parameters; Among them, Ψ is the calibrated geotechnical parameter, ξ is the bias adjustment parameter, β' and α' are the calibration coefficient and sensitivity parameter respectively, Γ k =Γ; Combining the construction conditions and the calibrated geotechnical parameters, the formula is adopted: Determine the geotechnical parameters that match the current geological environment and establish the optimal geotechnical parameters; Among them, Ω is the optimal geotechnical parameter, The path adjustment module calculates the feasibility and geological risk of the tunneling path based on the optimal geotechnical parameters, predicts the geological conditions that the shield machine will encounter in the future, and establishes an adjusted tunneling path; Based on the adjusted excavation path, the risk management module monitors the stratum hardness, water level and geological fracture distribution along the path, and compares the risk safety standard threshold. If it is found that the data exceeds the safety range, the degree of excess is calculated and the risk level is re-evaluated to obtain the risk assessment result.

2. The shield tunnel online monitoring system according to claim 1 is characterized in that: The steps for obtaining the real-time monitoring synthetic data are specifically as follows: Based on the cutterhead wear status and geological data collection, the cutterhead wear and geological condition data of the shield machine are collected in real time, and the average geological hardness and wear index are calculated using the formula: Obtain preliminary geological hardness data; Among them, P represents the average geological hardness, N represents the number of monitoring points, and p i represents the geological hardness of the i-th monitoring point, and γ is the hardness adjustment coefficient; Integrate the wear data with the geological hardness data using the formula: Computationally generate geotechnical wear models; Where H represents the rock wear model, w i represents the i-th wear monitoring point, δ is the wear adjustment coefficient, and θ is the offset coefficient; Based on the rock and soil wear model, combined with construction conditions and rock and soil mechanics parameters, the formula is adopted: Obtain real-time monitoring synthetic data; Among them, S represents real-time monitoring synthetic data, and α and β are adjustment parameters.

3. The shield tunnel online monitoring system according to claim 2 is characterized in that: The steps of obtaining the stress distribution are specifically as follows: The geotechnical properties are extracted from the real-time monitoring synthetic data using the formula: Calculate the weighted average stress distribution of N monitoring points and generate preliminary stress distribution data; Among them, σ ij represents the stress distribution in the i, j directions, ω k represents the weight of the kth monitoring point, x kij represents the geotechnical properties of the kth monitoring point in the i, j direction, λ is the attenuation coefficient, and N represents the number of monitoring points; Based on the preliminary stress distribution data, the stress distribution is adjusted through the variability analysis of geotechnical parameters, using the formula: Calculate and generate adjusted stress distribution data; Among them, τ ij represents the adjusted stress distribution, μ is the geotechnical property adjustment factor, D represents the geotechnical heterogeneity measure, and θ' is the constant threshold; Based on the adjusted stress distribution data and combined with the construction conditions, the formula is adopted: Calculate the adaptability of the adjusted stress distribution data under the current geological environment and generate stress distribution; Where Φ represents the stress distribution, ρ ij is the density factor of geological conditions, and M is the total number of reference directions.

4. The shield tunnel online monitoring system according to claim 1, characterized in that: The steps for obtaining the adjusted excavation path are specifically as follows: Based on the optimal geotechnical parameters, the feasibility of the excavation path is calculated using the formula: Generate a feasibility score for the excavation path; Among them, F is the feasibility score of the excavation path, k' and C are the sensitivity coefficient and the excavation condition threshold, respectively, and Ω i represents the optimal geotechnical parameters of the i-th segment, M1 represents the number of segments on the path; Using the feasibility score of the tunneling path described, the future geological conditions are predicted using the formula: Calculate and generate geological risk assessment results; Among them, G is the result of geological risk assessment, F i Score the feasibility of segment i, Based on the geological risk assessment results, the adjusted excavation path is determined using the formula: Calculate and establish adjusted excavation paths; Among them, P new is the comprehensive score of the adjusted excavation path, G i is the geological risk of the i-th section, G i =G.

5. The shield tunnel online monitoring system according to claim 4 is characterized in that: The steps for obtaining the risk assessment results are specifically as follows: Based on the adjusted excavation path, the ground hardness, water level and geological fracture distribution along the path are monitored, using the formula: Calculate the overall geological state and generate a comprehensive geological state score; Among them, h i 、w i ,d i are the monitoring data of formation hardness, water level and geological fracture distribution, X is the comprehensive score of geological status, a, b, c, d, l and f are adjustment factors, which enhance the influence and nonlinear effect of hardness, water level and fracture data; Using the comprehensive geological status score, the safety standard threshold t of the risk is compared, using the formula: If x i >t, the degree to which each monitoring point exceeds the safety range is calculated to generate a metric that exceeds the safety range; Where Y is the measure beyond the safety range, g and h' are the nonlinear and regularization effects that enhance the measure beyond the safety range, Based on the measure of exceeding the safety range, the risk level is re-evaluated using the formula: Calculate and obtain risk assessment results; Among them, R is the risk assessment result, s is the risk sensitivity coefficient,

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