Geological advanced prediction method and system fusing tunnel boring machine (TBM) tunneling parameters

Abstract

The present application relates to the geological advanced detection field, in order to improve the prediction accuracy, provide the geological advanced prediction method and system of fusion TBM excavation parameter, by establishing the correction relation of excavation parameter and geophysical parameter, based on the correction of geophysical parameter based on excavation parameter, the detection accuracy of complex stratum can be significantly improved;Promote stage with excavation seismic wave signal and electromagnetic wave signal, step or change sword stage can carry out tomography based on active source seismic wave signal, detection operation and construction process are completely synchronous, construction efficiency is improved by 20%, based on seismic wave tomography+electromagnetic wave coherence method double parameter joint inversion, combined with TBM parameter correction, the geophysical multiple solution is significantly reduced.

Description

Technical Field

[0001] This invention relates to the field of geological advance detection, specifically a geological advance prediction method and system that integrates TBM tunneling parameters. Background Technology

[0002] TBM tunnel geological advance prediction is a core technology for ensuring construction safety. Currently, geological advance prediction in TBM construction mainly relies on geophysical exploration methods. These methods infer geological conditions ahead by deploying excitation and reception devices inside the tunnel and utilizing the differences in the response of geological bodies to elastic or electromagnetic waves. Based on different physical principles, these methods can be mainly divided into seismic wave reflection methods, electromagnetic wave reflection methods, and electrical / electromagnetic methods. To overcome the limitations of single methods, some combined detection schemes have emerged in existing technologies. For example, combining seismic wave methods with ground-penetrating radar aims to balance detection depth and resolution; or comparing and analyzing the results of two or more geophysical methods. However, these combined approaches mostly remain at the level of simple parallel data acquisition and comparative verification of results. Essentially, they are still independent interpretations and mechanical superpositions of information from different physical fields, and problems such as low prediction accuracy in complex strata and prominent geophysical ambiguity issues persist. Summary of the Invention

[0003] To improve forecast accuracy, this invention provides a geological advance forecasting method and system that integrates TBM tunneling parameters.

[0004] The technical solution adopted by the present invention to solve the above problems is:

[0005] Geological advance prediction methods integrating TBM tunneling parameters include:

[0006] Step 1: Collect historical construction data and geophysical parameters of the corresponding geological sections; construction data includes TBM tunneling parameters and geological parameters of the corresponding mileage.

[0007] Step 2: Based on the collected data, filter the tunneling parameters that are strongly correlated with the geophysical parameters through correlation analysis;

[0008] Step 3: Calibrate the correction coefficients between the selected tunneling parameters and geophysical parameters;

[0009] Step 4: During the actual construction process, obtain tunneling parameters and geophysical parameters, obtain correction coefficients based on the tunneling parameters, and correct the obtained geophysical parameters.

[0010] Further, step 2 involves correlation analysis using correlation coefficients or grey relational analysis.

[0011] Furthermore, step 3 includes:

[0012] Step 31, Laboratory Calibration: Prepare standard specimens for different geological conditions, and measure the correspondence between the geophysical parameters of the specimens and the simulated tunneling parameters through simulated TBM tunneling tests to initially establish the range of correction coefficients;

[0013] Step 32, On-site measurement and calibration: Obtain the actual geological parameters at the beginning of the project and determine the correction coefficient based on the actual geological parameters.

[0014] Furthermore, step 3 also includes: optimizing the correction coefficients based on actual geological parameters during the tunneling process.

[0015] Furthermore, geophysical parameters include seismic wave velocity and electromagnetic wave dielectric constant.

[0016] Furthermore, step 4 involves obtaining geophysical parameters using a geological model. The steps for obtaining the geological model are as follows:

[0017] During the advance phase, geophysical signals and tunneling parameters are collected. The geophysical signals include electromagnetic wave signals and vibration noise generated by the cutterhead breaking rock. During the step change phase, geophysical signals are actively transmitted and received. The geophysical signals include seismic wave signals and electromagnetic wave signals.

[0018] Preprocess the collected geophysical signals;

[0019] An initial geological model was established based on geophysical signals collected during the advancement phase;

[0020] The initial geological model is corrected based on the geophysical signals acquired during the step-by-step phase.

[0021] Furthermore, the steps for obtaining the geological model also include:

[0022] Correction coefficients are determined based on the tunneling parameters collected during the advancement phase, and the inversion results of the corrected geological model are calibrated based on the correction coefficients.

[0023] The calibrated results are compared with the actual excavation results. If the deviation is greater than the threshold, the parameters of the corrected geological model are adjusted again.

[0024] Furthermore, preprocessing includes: noise reduction, removal of outlier data, and time synchronization.

[0025] It further includes step 5, generating a geological interpretation report based on the corrected geophysical parameters.

[0026] A geological advance prediction system integrating TBM tunneling parameters is used to implement a geological advance prediction method that integrates TBM tunneling parameters, including:

[0027] Geophysical signal excitation module, used to excite geophysical signals;

[0028] The data acquisition module is used to collect tunneling parameters and geophysical signals;

[0029] Geophysical parameter inversion module, which inverts geophysical parameters based on geophysical signals;

[0030] The geophysical parameter correction module determines the correction coefficients based on the tunneling parameters and corrects the geophysical parameters based on the correction coefficients.

[0031] The advantages of this invention compared to the prior art are:

[0032] (1) Integrating tunneling parameters to improve detection accuracy: By incorporating tunneling parameters such as TBM thrust and torque into the interpretation of geophysical parameters, the detection accuracy of complex strata can be significantly improved through the dual constraints of "geophysical data + construction parameters". The identification resolution of adverse geological conditions such as water-rich faults and weak interlayers is improved from 5m to 1-2m.

[0033] (2) Dynamic detection along with construction process to improve construction efficiency: No need to stop the machine, seismic wave signals and electromagnetic wave signals are collected during the advance stage; tomography based on active source seismic wave signals can be carried out during the step change or cutter change stage. The detection operation is completely synchronized with the construction process, and the construction efficiency is improved by 20%.

[0034] (3) Reduce the ambiguity of geophysical exploration and improve the reliability of results: The dual-parameter joint inversion of "seismic wave tomography (velocity) + electromagnetic wave coherence method (dielectric constant)" combined with TBM parameter correction significantly reduces the ambiguity of geophysical exploration. Attached Figure Description

[0035] Figure 1 Flowchart of a geological advance prediction method that integrates TBM tunneling parameters. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0037] like Figure 1 As shown, the geological advance prediction method integrating TBM tunneling parameters includes:

[0038] Step 1: Collect historical construction data and geophysical parameters of the corresponding geological sections; construction data includes TBM tunneling parameters and geological parameters of the corresponding mileage.

[0039] Collect historical construction data from similar projects (such as hard rock tunnels and complex geological formations): including TBM tunneling parameters (including thrust F, torque T, cutterhead penetration P, and muck density). tunneling speed Geological survey data corresponding to the mileage (including rock mass compressive strength) Integrity coefficient Moisture content (Scale of unfavorable geological conditions)

[0040] Synchronous acquisition of geophysical data: Geophysical data is collected for the same geological section, and a three-dimensional database of "tunneling parameters - geological parameters - geophysical parameters" is established.

[0041] By collecting and analyzing data from similar projects, the accuracy of the analysis results has been improved.

[0042] Geophysical parameters can be obtained using existing single or combined methods. In this embodiment, to improve the accuracy of the geophysical method, a dual-wavefield detection system is used to obtain the seismic wave velocity v and the electromagnetic wave dielectric constant. .

[0043] Step 2: Based on the collected data, filter the tunneling parameters that are strongly correlated with the geophysical parameters through correlation analysis.

[0044] Using methods such as correlation coefficients and grey relational analysis, tunneling parameters strongly correlated with geophysical parameters are screened to determine the core correction factors. In this embodiment, correlation coefficients with an absolute value greater than 0.7 are considered strongly correlated; for example, the correlation coefficient between F and v > 0.8. and If the correlation coefficient is greater than -0.7, then F is related to v. and Strong correlation.

[0045] Step 3: Calibrate the correction coefficients between the selected tunneling parameters and geophysical parameters.

[0046] To obtain more reliable and practical calibration results and improve the overall quality of the analysis, this embodiment adopts a laboratory + on-site calibration method, specifically including:

[0047] Laboratory calibration: Standard specimens with different geological conditions (such as sandstone with different water content and limestone with different degrees of fracture) are prepared. Through simulated TBM tunneling tests, the geophysical parameters (v, ε) of the specimens are measured to measure the correspondence between the simulated tunneling parameters (simulated thrust, torque) and to initially establish the range of correction coefficients.

[0048] On-site measurement and calibration: In the early stages of the project (such as the first 100m tunneling section), real geological parameters are obtained through methods such as core drilling and ground-penetrating radar verification. The deviation between the "uncorrected geophysical inversion results" and the "real geological parameters" is compared, and the correction coefficient is iteratively optimized in combination with real-time tunneling parameters.

[0049] Example of parameter correction is shown below:

[0050]

[0051] Step 4: During the actual construction process, obtain tunneling parameters and geophysical parameters, obtain correction coefficients based on the tunneling parameters, and correct the obtained geophysical parameters.

[0052] Geophysical parameters are obtained through geological model inversion. In this embodiment, a segmented data processing method is adopted according to the construction sequence:

[0053] I. Advancement Phase (Passive Detection Mode)

[0054] Data collection content:

[0055] Passive source signals: vibration noise generated by the cutterhead breaking rock (as a passive source of seismic waves, sampling frequency 2kHz), electromagnetic wave signals (100MHz).

[0056] Synchronization parameters: TBM real-time tunneling parameters (thrust F, cutterhead penetration P, muck density) (Spindle speed n, sampling frequency 1Hz).

[0057] Data processing steps:

[0058] Preprocessing: Seismic waves were denoised using wavelet thresholding (to remove TBM motor vibration interference), and electromagnetic waves were denoised using adaptive filtering (to remove electromagnetic shielding interference from steel structures), based on 3D... The criteria exclude abnormal data (such as signal distortion caused by sudden changes in tunneling parameters).

[0059] Time synchronization: Based on the TBM PLC clock signal (error ≤ 1ms), the tunneling parameters are aligned with the geophysical signals (e.g., the seismic wave travel time data at the same time corresponds to a thrust of 2500kN at a certain moment).

[0060] Preliminary interpretation: A preliminary geological profile is obtained using a simplified inversion model (such as a rapid seismic wave velocity estimation formula). For example, "a thrust of 2500 kN corresponds to a seismic wave velocity of 4000 m / s, which is inferred to be a medium-hardness rock mass".

[0061] Data storage: The preprocessed geophysical data and tunneling parameter sequences are stored in the data terminal for subsequent data fusion and verification with the step-change stage.

[0062] This stage involves real-time monitoring of geological conditions without interrupting construction, providing an "initial geological model" for high-precision exploration in the next stage, thereby reducing the number of subsequent inversion iterations.

[0063] II. Step / Tool Change Phase (Active Fine Detection Mode)

[0064] Data collection content:

[0065] Active source signal: Encoded seismic waves are transmitted via the hydraulic exciter (TDIS 1800) integrated into the TBM, and electromagnetic waves of a specific frequency are transmitted via an electromagnetic wave transmitting antenna; Received signal: The seismic wave sensor array receives reflected / scattered seismic waves, and the electromagnetic wave receiving antenna receives reflected electromagnetic waves (the sampling frequency is consistent with the propulsion stage).

[0066] Auxiliary parameters: There are no tunneling parameters in the step-change stage, but the tunneling parameters stored in the advance stage will be called. In this embodiment, the average value of the 10 most recent sets of tunneling parameters in the advance stage is used as the tunneling parameters for the step-change stage.

[0067] Data processing steps:

[0068] Active signal preprocessing: Denoising the actively excited seismic / electromagnetic wave signals (same as the algorithm in the propulsion stage) and enhancing the signals (decoding the encoded signals to improve the signal-to-noise ratio).

[0069] High-precision joint inversion: Constructing a joint inversion model of "seismic wave tomography + electromagnetic wave coherence method", using the "seismic wave velocity (v) - dielectric constant (v)" of geological bodies as the basis for the model. Prior information such as ")" serves as a double constraint, and three-dimensional inversion is achieved using the least squares method:

[0070] ,

[0071] Where: d represents the observed data (seismic wave travel time + received voltage), G represents the forward modeling operator, and m represents the model parameters (v, ), For the data weight matrix, This is the model weight matrix. This is the regularization parameter (value 0.01). It is the square of the L2 norm.

[0072] The preprocessed active source signal is input into the joint inversion model of "seismic wave tomography + electromagnetic wave coherence method". The preliminary geological model of the advancement stage is used as the initial value, and the three-dimensional velocity-dielectric constant model is obtained through iterative optimization.

[0073] This stage utilizes the stoppage window during step / tool ​​change to achieve high-precision imaging through an active source, compensating for the insufficient accuracy of passive detection during the propulsion stage, and ultimately forming a dual guarantee of "real-time monitoring + high-precision verification".

[0074] Ultimately, the data from both phases were processed through "initial model → high-precision correction," ensuring both construction continuity (drilling and exploration as needed during the advancement phase) and detection accuracy (active imaging during the step-change phase).

[0075] To improve the accuracy of the prediction, this embodiment also adopts a feedback correction method. That is, if the prediction result deviates from the actual geological conditions revealed later during the tunneling process by more than a preset value, the correction coefficient and / or the three-dimensional velocity-dielectric constant model are automatically updated.

[0076] Furthermore, it also includes outputting a final geological interpretation report based on the corrected geological parameters, including the location, scale, and nature of adverse geological features. It can also generate a three-dimensional geological imaging map (color scale: red = water-rich fault, yellow = weak interlayer), and trigger an audible and visual warning when an adverse geological feature is identified at a distance from the cutterhead less than the warning value.

[0077] The method of this invention is applicable to the advance prediction of adverse geological conditions (faults, water-rich layers, weak interlayers) within 50-100m in front of the cutterhead during TBM construction. It achieves deep coupling between the detection equipment and the mechanical structure and construction procedures of the TBM, and improves the detection accuracy by integrating TBM tunneling parameters. It can be applied to TBM construction scenarios of hard rock tunnels and composite strata tunnels.

[0078] Correspondingly, this embodiment also provides a geological advance prediction system that integrates TBM tunneling parameters, used to implement a geological advance prediction method that integrates TBM tunneling parameters, including:

[0079] Geophysical signal excitation module, used to excite geophysical signals;

[0080] The data acquisition module is used to collect tunneling parameters and geophysical signals;

[0081] Geophysical parameter inversion module, which inverts geophysical parameters based on geophysical signals;

[0082] The geophysical parameter correction module determines the correction coefficients based on the tunneling parameters and corrects the geophysical parameters based on the correction coefficients.

[0083] In this embodiment, the active source seismic wave signal excitation device adopts a telescopic TBM source mounting fixture to achieve integrated mounting of the source device (TDIS1800) and the TBM. Electrical components control the hydraulic circuit switch, thereby enabling the automatic extension and retraction of the hydraulic cylinder to excite the active source seismic wave signal. The source can be installed in various ways (suspended, wall-mounted, bottom-mounted) and can be placed at locations such as the TBM tail, support shoe, and L1 platform.

[0084] The signal receiving module adopts a wear-resistant stainless steel rod-type integrated design (rod diameter) (Length 300mm)

[0085] The front end of the pole is equipped with a miniaturized vibration-resistant acceleration sensor (model: KISTLER8762A5, vibration resistance level ≥1000g) as a detector, which is connected to the pole body through a polyurethane damping block (hardness 50 ShoreA) to reduce TBM vibration interference.

[0086] The sensor is wrapped with an electromagnetic shielding layer (copper mesh + ferrite core) to shield the electromagnetic interference of the TBM motor (power ≥1600kW), with an electromagnetic shielding effectiveness ≥60dB.

[0087] The pole is made of 316L stainless steel and coated with polytetrafluoroethylene (PTFE) (0.5mm thick), which provides water resistance and abrasion resistance.

[0088] The pole is equipped with a waterproof aviation connector (model: M20-12 core) at the end, which connects to the seismic wave signal cable and the electromagnetic wave signal cable respectively, to achieve sealed signal transmission.

Claims

1. A geological advance prediction method integrating TBM tunneling parameters, characterized in that, include: Step 1: Collect historical construction data and geophysical parameters of the corresponding geological sections; construction data includes TBM tunneling parameters and geological parameters of the corresponding mileage. Step 2: Based on the collected data, filter the tunneling parameters that are strongly correlated with the geophysical parameters through correlation analysis; Step 3: Calibrate the correction coefficients between the selected tunneling parameters and geophysical parameters; Step 4: During the actual construction process, obtain tunneling parameters and geophysical parameters, obtain correction coefficients based on the tunneling parameters, and correct the obtained geophysical parameters. Step 3 includes: Step 31, Laboratory Calibration: Prepare standard specimens for different geological conditions, and measure the correspondence between the geophysical parameters of the specimens and the simulated tunneling parameters through simulated TBM tunneling tests to initially establish the range of correction coefficients; Step 32, On-site measurement and calibration: Obtain the actual geological parameters at the beginning of the project and determine the correction coefficient based on the actual geological parameters.

2. The geological advance prediction method integrating TBM tunneling parameters according to claim 1, characterized in that, Step 2 involves correlation analysis using correlation coefficients or grey relational analysis.

3. The geological advance prediction method integrating TBM tunneling parameters according to claim 1, characterized in that, Step 3 also includes: optimizing the correction coefficients based on the actual geological parameters during the tunneling process.

4. The geological advance prediction method integrating TBM tunneling parameters according to claim 1, characterized in that, Geophysical parameters include seismic wave velocity and electromagnetic wave dielectric constant.

5. The geological advance prediction method integrating TBM tunneling parameters according to claim 4, characterized in that, Step 4: Obtain geophysical parameters using a geological model. The steps for obtaining the geological model are as follows: During the advance phase, geophysical signals and tunneling parameters are collected. The geophysical signals include electromagnetic wave signals and vibration noise generated by the cutterhead breaking rock. During the step change phase, geophysical signals are actively transmitted and received. The geophysical signals include seismic wave signals and electromagnetic wave signals. Preprocess the collected geophysical signals; An initial geological model was established based on geophysical signals collected during the advancement phase; The initial geological model is corrected based on the geophysical signals acquired during the step-by-step phase.

6. The geological advance prediction method integrating TBM tunneling parameters according to claim 5, characterized in that, The steps for obtaining a geological model also include: Correction coefficients are determined based on the tunneling parameters collected during the advancement phase, and the inversion results of the corrected geological model are calibrated based on the correction coefficients. The calibrated results are compared with the actual excavation results. If the deviation is greater than the threshold, the parameters of the corrected geological model are adjusted again.

7. The geological advance prediction method integrating TBM tunneling parameters according to claim 5, characterized in that, Preprocessing includes: Noise reduction, removal of outlier data, and time synchronization.

8. The geological advance prediction method integrating TBM tunneling parameters according to any one of claims 1-7, characterized in that, It also includes step 5, generating a geological interpretation report based on the corrected geophysical parameters.

9. A geological advance prediction system integrating TBM tunneling parameters, used to implement the geological advance prediction method integrating TBM tunneling parameters as described in any one of claims 1-8, characterized in that, include: Geophysical signal excitation module, used to excite geophysical signals; The data acquisition module is used to collect tunneling parameters and geophysical signals; Geophysical parameter inversion module, which inverts geophysical parameters based on geophysical signals; The geophysical parameter correction module determines the correction coefficients based on the tunneling parameters and corrects the geophysical parameters based on the correction coefficients.

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