Tunnel advanced detection method for curved section TBM hard rock tunneling

Abstract

The invention relates to the technical field of tunnel advanced detection, in particular to a tunnel advanced detection method for curved section TBM hard rock tunneling, which comprises the following steps: imaging and analyzing a to-be-tunneled area to obtain geological distribution data and geological form data, and judging whether to carry out advanced geological drilling on the to-be-tunneled area according to an analysis result; determining an initial lofting proportion according to the initial area and the initial number; the initial lofting proportion is adjusted according to the curve section tunneling radian comparison result; obtaining a three-dimensional geological image reconstruction model according to the advanced geological drilling result data and the three-dimensional geological image key area analysis result data; and according to the tunnel face detection result image data, carrying out coincidence degree verification on the three-dimensional geological image reconstruction model, and according to a verification result, judging whether to carry out supplementary detection or not. According to the method, the geological image is accurately imaged in a mode of combining a tunnel seismic wave reflection tomography technology and advanced geological drilling, and the three-dimensional geological image reconstruction model is adjusted through imaging data of the to-be-tunneled area of the tunnel face.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel advance detection, and in particular to a tunnel advance detection method for TBM hard rock excavation in a curved section. Background Art

[0002] Tunnel advance detection technology is an essential tool for tunnel construction. It uses seismic wave reflections to image the unexcavated area behind the tunnel face. The results of this imaging can guide construction teams in developing appropriate construction plans and thus avoid accidents.

[0003] Chinese Patent Publication No. CN106443766A discloses a three-dimensional tunnel seismic advance detection method characterized by the following steps: uniformly arranging multiple excitation points at the edge of the tunnel face and one excitation point at the center of the face; uniformly arranging multiple receiving points along the midpoint trajectory between the edge and the center of the tunnel face, with each excitation point and each receiving point connected to a digital seismograph; sequentially emitting signals from the multiple excitation points, with all receiving points simultaneously receiving seismic wave signals, and using a digital seismograph for data acquisition to form multiple sets of seismic wave reflection records; c. extracting data collected from the common excitation points from the digital seismograph and transmitting it to seismic data analysis software; d. data preprocessing; velocity analysis; and obtaining depth data. The calculation results of the two modes of the steps provide an explanation for anomalies, which are then combined with borehole and geological radar data for comprehensive interpretation. The present invention can obtain three-dimensional depth data in front of the tunnel face, achieving the effect of tunnel advance geological prediction.

[0004] It can be seen that the existing technology lacks the ability to accurately image the geological image through a combination of tunnel seismic wave reflection tomography technology and advanced geological drilling when excavating curved tunnels, and to adjust the three-dimensional geological image reconstruction model through the imaging data of the area to be excavated at the face. Summary of the Invention

[0005] To this end, the present invention provides a tunnel advance detection method for TBM hard rock excavation in curved sections, which is used to overcome the problem in the prior art that, when excavating curved tunnels, there is a lack of the ability to accurately image the geological image through a combination of tunnel seismic wave reflection tomography technology and advance geological drilling, and to adjust the three-dimensional geological image reconstruction model through the imaging data of the area to be excavated at the face.

[0006] To achieve the above object, the present invention provides a tunnel advance detection method for TBM hard rock excavation in a curved section, comprising the following steps:

[0007] Imaging the area to be excavated by using tunnel seismic wave reflection tomography technology to obtain an initial three-dimensional geological image of the area to be excavated;

[0008] Analyzing geological distribution data and geological morphology data of the initial three-dimensional geological image to obtain analysis result data of key areas of the three-dimensional geological image, and determining whether to perform advance geological drilling on the area to be excavated based on the analysis result data of key areas of the three-dimensional geological image;

[0009] In the case where advance geological drilling is required for the area to be excavated, an initial area for the stakeout points is determined based on the first geological distribution result data of the key area analysis result data of the three-dimensional geological image, and an initial number level of the stakeout points is determined based on the first geological morphological result data of the key area analysis result data of the three-dimensional geological image;

[0010] determining an initial stakeout ratio according to the initial area and the initial quantity;

[0011] During the excavation process, a current excavation angle is obtained, the current excavation angle is compared with a preset excavation angle range to obtain a comparison result of the excavation arc of the curved section, an initial lofting ratio is adjusted according to the comparison result of the excavation arc of the curved section to obtain a second lofting ratio, and advance geological drilling is determined according to the second lofting ratio to obtain advance detection result data and the analysis result data of the key areas of the three-dimensional geological image to obtain a three-dimensional geological image reconstruction model;

[0012] Tunnel face detection result image data is obtained based on tunnel reflection tomography within a preset detection range of the tunnel face in the excavation direction. Coincidence verification is performed on the three-dimensional geological image reconstruction model based on the tunnel face detection result image data to obtain a coincidence verification result. Whether to perform additional detection is determined based on the coincidence verification result.

[0013] Furthermore, the process of imaging the area to be excavated by using the tunnel seismic wave reflection tomography technology to obtain an initial three-dimensional geological image of the area to be excavated includes:

[0014] Several mechanical seismic sources are installed on the side walls of the tunnel, and seismic sensors are installed at corresponding positions to receive reflected wave signals. The reflected wave signals are pre-processed and converted into initial three-dimensional geological images through tomography technology.

[0015] Furthermore, the process of analyzing the geological distribution data and geological morphology data of the initial three-dimensional geological image to obtain the analysis result data of the key areas of the three-dimensional geological image includes:

[0016] Performing multi-dimensional analysis on the initial three-dimensional geological image to obtain geological distribution result data and geological morphology result data based on the initial three-dimensional geological image;

[0017] The multi-dimensional analysis includes geometric shape analysis, surface feature analysis and dynamic change analysis.

[0018] Furthermore, the process of determining whether to conduct advance geological drilling in the area to be excavated based on the analysis result data of the key areas of the three-dimensional geological image includes:

[0019] The geological distribution result data and the geological morphology result data are normalized to obtain an overlap characteristic value, and the overlap characteristic value is compared with a preset standard overlap characteristic value to obtain a first overlap range comparison result. Based on the first overlap range comparison result, it is determined whether to perform advance geological drilling on the area to be excavated.

[0020] Furthermore, in the case where advance geological drilling is required for the area to be excavated, the process of determining the initial area of the stakeout point based on the first geological distribution result data of the key area analysis result of the three-dimensional geological image includes:

[0021] The distribution range and distribution density of the geological anomaly area are determined based on the first geological distribution result data, the initial area is determined according to the distribution range, and the number and level of initial stakeout points in the initial area are determined according to the distribution density.

[0022] Furthermore, the process of determining the initial number level of the stakeout points based on the first geological morphological result data of the key area analysis result data of the three-dimensional geological image includes:

[0023] The first geological morphology result data is analyzed to obtain the geological morphology category of the area to be excavated, and the quantity level of the initial quantity is determined based on the geological morphology category.

[0024] Furthermore, the process of comparing the current excavation angle with a preset excavation angle range to obtain a curve segment excavation arc comparison result, and adjusting the initial lofting ratio according to the curve segment excavation arc comparison result to obtain a second lofting ratio includes:

[0025] If the comparison result of the excavation arc of the curved section shows that the current excavation angle is greater than the maximum value of the preset excavation angle range, the excavation angle of the excavation device is adjusted;

[0026] If the comparison result of the excavation arc of the curved section shows that the current excavation angle is less than the minimum value of the preset excavation angle range, adjusting the initial setting out ratio;

[0027] If the comparison result of the excavation arc of the curved section shows that the current excavation angle is within the preset excavation angle range, there is no need to adjust the initial layout ratio and the excavation angle of the excavation device.

[0028] Furthermore, the process of obtaining the advance detection result data and the three-dimensional geological image key area analysis result data by the advance geological drilling determined according to the second lofting ratio to obtain the three-dimensional geological image reconstruction model includes:

[0029] The advanced detection result data and the three-dimensional geological image key area analysis result data are subjected to data preprocessing and data fusion operations to obtain a three-dimensional geological image reconstruction model.

[0030] Furthermore, the process of obtaining tunnel face detection result image data based on tunnel reflection tomography within a preset detection range of the tunnel face in the excavation direction, and performing coincidence verification on the three-dimensional geological image reconstruction model according to the tunnel face detection result image data to obtain a coincidence verification result includes:

[0031] performing geological feature comparison between the tunnel face detection result image data and the corresponding image area in the three-dimensional geological image reconstruction model, determining an actual coincidence degree based on the geological feature comparison result, and comparing the actual coincidence degree with a standard coincidence degree to obtain a coincidence degree comparison result;

[0032] The preset detection range is determined according to the current excavation progress; the geological characteristics include rock stability and fault location.

[0033] Furthermore, the process of determining whether to perform additional detection according to the coincidence check result includes:

[0034] Based on the coincidence comparison result, it is determined whether to perform additional detection on the area to be excavated.

[0035] Compared with existing technologies, the present invention offers the following advantages: it uses tunnel seismic wave reflection tomography to image the area to be excavated, generating an initial three-dimensional geological image of the area to be excavated. This allows for a preliminary determination of the approximate geological distribution and morphology within the area to be excavated, providing strong support for subsequent excavation construction. By combining tunnel seismic wave reflection tomography with advance geological drilling, the geological conditions of the area to be excavated can be more accurately predicted, reducing uncertainty during construction. During excavation, the stakeout ratio is dynamically adjusted based on real-time excavation angles and geological data, ensuring the scientific and adaptable nature of the construction plan. Through advance geological drilling and tunnel face detection, potential geological risks can be identified in advance, allowing appropriate preventive measures to be taken and construction risks to be reduced. By analyzing key areas in the three-dimensional geological image and dynamically adjusting the stakeout ratio, drilling resources can be rationally allocated, avoiding unnecessary drilling work and improving construction efficiency. By verifying the three-dimensional geological image reconstruction model with the tunnel face detection results, the geology in the tunnel face excavation direction can be further detected to promptly identify geological anomalies, ensuring safety during construction. Through accurate geological prediction and dynamic adjustment, construction delays and additional costs caused by geological problems can be reduced, and the economic benefits of the project can be improved.

[0036] Furthermore, the deployment of mechanical seismic sources and seismic sensors enables the acquisition of high-resolution seismic wave reflection signals, which, combined with tomography technology, can generate high-precision three-dimensional geological images. These images clearly reflect the geological structure, lithologic distribution, and potential geological anomalies in the area to be excavated. This technology is a non-destructive exploration method that can obtain underground geological information without drilling or damaging the rock mass. It is suitable for advanced geological exploration before tunnel excavation, minimizing the impact on construction progress. The simple deployment of mechanical seismic sources and seismic sensors allows for rapid data acquisition and processing, enabling the rapid generation of three-dimensional geological images. This provides real-time geological information support for tunnel excavation, improving construction efficiency. By deploying multiple mechanical seismic sources and seismic sensors along the tunnel sidewalls, comprehensive coverage of the entire area to be excavated can be achieved. The three-dimensional geological images enable the early identification of potential geological risks, providing a scientific basis for the development of construction plans. This effectively reduces the probability of accidents such as landslides and water inrush during tunnel excavation. Based on the three-dimensional geological images, tunnel excavation plans can be optimized and excavation parameters can be rationally selected. By placing mechanical seismic sources and seismic sensors on the tunnel sidewalls and combining them with tomography to generate initial 3D geological images, high-precision, non-destructive, real-time, and efficient geological exploration can be achieved. This technology provides reliable geological information support for tunnel excavation, significantly reducing construction risks, optimizing construction plans, and saving costs, possessing significant engineering application value.

[0037] Furthermore, through multi-dimensional analysis, it is possible to accurately identify geological anomalies such as faults, karst caves, and weak interlayers. Targeted construction plans can be formulated for key areas (such as strengthening support and adjusting excavation parameters). Potential geological risks can be discovered in advance to reduce the occurrence of accidents such as landslides and water gushing. By performing geometric shape analysis, surface feature analysis, and dynamic change analysis on the initial three-dimensional geological image, it is possible to fully understand the geological distribution and morphological characteristics of the area to be excavated, accurately identify key areas, provide a scientific basis for tunnel excavation, significantly reduce construction risks, and improve construction efficiency.

[0038] Furthermore, by normalizing the geological distribution and morphological data, differences in dimension and range are eliminated, enabling comparison and analysis at the same scale, thus enhancing the scientific validity of the judgment. By calculating the overlap characteristic value, a comprehensive reflection of the spatial consistency of geological distribution and morphology is achieved, avoiding the limitations of a single data metric and improving the accuracy of the judgment. By presetting a standard overlap characteristic value, the judgment process is quantified, eliminating the influence of subjective experience and making the decision more objective and reliable. By comparing the calculated overlap characteristic value with the standard value, a clear judgment can be made as to whether advance geological drilling is necessary, reducing decision-making uncertainty. If the overlap characteristic value is greater than the standard value, it indicates that the geological conditions in the area are complex or there are potential risks, necessitating advance geological drilling. This allows for targeted resource allocation and avoids blind drilling. If the overlap characteristic value is less than or equal to the standard value, the geological conditions in the area are relatively simple, and advance geological drilling is unnecessary, thus saving manpower, material resources, and time. By analyzing the coincident eigenvalues, areas with complex geological conditions or potential risks can be identified in advance, providing a basis for advanced geological drilling and thus reducing the risk of geological hazards encountered during excavation. Advance geological drilling can further confirm the geological conditions, provide reliable geological data support for excavation projects, and ensure construction safety and smooth progress. For areas requiring drilling, drilling points can be rationally arranged based on the size of the coincident eigenvalues, improving drilling accuracy and efficiency. In actual projects, the standard coincident eigenvalues can be dynamically adjusted based on new geological data, making the judgment process more flexible and adaptable. This method, based on the results of three-dimensional geological image analysis, implements a data-driven decision-making process through data normalization, eigenvalue calculation, and comparative analysis, in line with the development trend of modern engineering management.

[0039] Furthermore, by analyzing the distribution of geologically anomaly areas, the area to be excavated is divided into several initial zones, making the layout of stakeout points more scientific and rational. The number of stakeout points is dynamically adjusted based on the geological complexity of each initial zone, ensuring more stakeout points in high-density areas and fewer in low-density areas, improving the targeted layout. By rationally allocating stakeout points based on distribution density, the system avoids over-deploying stakeout points in low-density areas, saving manpower, material resources, and time. Concentrating more stakeout points in high-density areas allows for more comprehensive geological information, improves drilling efficiency, and reduces duplication of effort. By analyzing the distribution and density of geologically anomaly areas, high-risk areas (such as areas with dense faults and developed karst caves) can be identified in advance, providing a basis for advanced geological drilling and reducing the risk of geological hazards (such as landslides and water inrush) that may be encountered during excavation. By placing more stakeout points in high-density areas, the system provides a more accurate understanding of the geological conditions, providing data support for adjusting construction plans and ensuring construction safety. By dividing the initial area and arranging stakeout points based on density, we ensure that every local area within the geological anomaly is covered, preventing the omission of important geological information. Placing more stakeout points in high-density areas allows for more detailed geological data, improving its accuracy and reliability. This method comprehensively considers the distribution and density of geological anomalies, adapting to analysis requirements under complex geological conditions and providing comprehensive geological information support for tunneling projects.

[0040] Furthermore, when the current excavation angle exceeds the maximum excavation angle range, the inclination of the tunneling device's cutterhead, and therefore the tunneling angle of the tunnel boring machine, is adjusted to ensure the excavation direction aligns with the designed axis, avoiding deviation from the designed trajectory and improving construction accuracy and safety. When the current excavation angle is less than the minimum excavation angle range, the initial stakeout ratio is adjusted, increasing the number of stakeout points and increasing the coverage density of advance geological drilling, ensuring the comprehensiveness and accuracy of geological data and reducing construction risks. By monitoring the current excavation angle in real time and dynamically adjusting excavation parameters, it is possible to adapt to construction needs under complex geological conditions and reduce the occurrence of geological disasters such as landslides and water inrush. Adjusting the stakeout ratio based on geological conditions and excavation angle ensures sufficient coverage of high-risk areas (such as fault zones and karst caves), improving construction safety. When the excavation angle is within the preset range, there is no need to adjust the stakeout ratio or excavation angle, avoiding unnecessary waste of resources. This dynamic adjustment ensures the scientific nature of the excavation direction and stakeout point layout, reduces duplication of work and construction delays, and improves construction efficiency. By setting the cutterhead inclination compensation parameters and the layout ratio compensation parameters, the construction parameters can be flexibly adjusted according to the difference between the actual excavation angle and the preset range, thereby enhancing the adaptability and flexibility of the construction.

[0041] Furthermore, data preprocessing steps improve the accuracy and reliability of the advanced exploration data. Data acquired from different exploration devices are converted into a unified format to facilitate subsequent data fusion and analysis. Missing data points are interpolated to increase data density and ensure spatial continuity and integrity. Improving image contrast and clarity enhances the geological features of key areas, making them easier for engineers to identify and analyze. Key areas are separated from the background, highlighting critical geological information and reducing interference. Geometric and texture features of key areas are extracted, providing a foundation for subsequent data fusion and model reconstruction. The advanced exploration data and the analysis results of key areas in the 3D geological image are spatially registered to ensure the data are in a unified coordinate system, improving spatial consistency. The exploration data are converted from the device coordinate system to the tunnel coordinate system to facilitate comparison and analysis with engineering design parameters and construction data. Based on data characteristics and project requirements, weighted fusion, interpolation fusion, and model fusion methods are selected to ensure optimal fusion results. By setting weights, interpolation methods, and model parameters, the data fusion process is optimized to generate a high-precision 3D geological image reconstruction model. Perform data fusion operations to organically combine the advanced detection result data with the analysis result data of key areas of the 3D geological image to generate a comprehensive and accurate 3D geological image reconstruction model.

[0042] Furthermore, through coincidence verification and supplementary surveys, the geological conditions ahead can be more accurately understood, allowing for the timely identification of potential risks, such as unstable rock formations and faults, allowing for proactive countermeasures and preventing accidents during construction. Based on accurate geological information, the construction team can more rationally plan excavation paths and construction methods, avoiding large-scale excavation in unstable areas and reducing construction difficulty and costs. Confirming geological conditions through supplementary surveys can reduce work stoppages and rework caused by geological uncertainty, improve construction efficiency, and shorten the project schedule. Accurate geological information and coincidence verification results provide solid data support for construction decisions, strengthening the confidence of the construction team and relevant personnel in the construction plan. By avoiding unnecessary excavation and support in unstable areas, construction costs can be significantly reduced, improving the economic benefits of the project. Accurate geological information and a rational construction plan ensure the quality of tunnel construction and extend its service life. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Flowchart of the tunnel advance detection method for TBM hard rock excavation in a curved section in this embodiment;

[0044] Figure 2 This is a flow chart for obtaining an initial three-dimensional geological image of the area to be excavated in this embodiment;

[0045] Figure 3Flowchart of the steps for processing advance detection result data of the tunnel advance detection method for TBM hard rock excavation in curved sections in this embodiment;

[0046] Figure 4 Flowchart of the data processing steps for the key area analysis results of the three-dimensional geological image of the method for tunnel advance detection for hard rock excavation by TBM in curved sections in this embodiment;

[0047] Figure 5 This is a flow chart of the comparison results of the curved section excavation arc of the tunnel advance detection method for curved section TBM hard rock excavation in this embodiment. DETAILED DESCRIPTION

[0048] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0049] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0050] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0051] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0052] See also Figure 1-Figure 5 As shown, Figure 1 Flowchart of the tunnel advance detection method for TBM hard rock excavation in a curved section in this embodiment; Figure 2 This is a flow chart for obtaining an initial three-dimensional geological image of the area to be excavated in this embodiment; Figure 3 Flowchart of the steps for processing advance detection result data of the tunnel advance detection method for TBM hard rock excavation in curved sections in this embodiment; Figure 4Flowchart of the data processing steps for the key area analysis results of the three-dimensional geological image of the method for tunnel advance detection for hard rock excavation by TBM in curved sections in this embodiment; Figure 5 This is a flow chart of the comparison results of the curved section excavation arc of the tunnel advance detection method for curved section TBM hard rock excavation in this embodiment.

[0053] This embodiment provides a tunnel advance detection method for TBM hard rock excavation in a curved section, comprising the following steps:

[0054] Step S1, imaging the area to be excavated by using tunnel seismic wave reflection tomography technology to obtain an initial three-dimensional geological image of the area to be excavated;

[0055] Step S2, analyzing the geological distribution data and geological morphology data of the initial three-dimensional geological image to obtain analysis result data of key areas of the three-dimensional geological image, and determining whether to perform advance geological drilling on the area to be excavated based on the analysis result data of key areas of the three-dimensional geological image;

[0056] Step S3, in the case where advance geological drilling is required for the area to be excavated, determining an initial area for stakeout points based on first geological distribution result data of the key area analysis result of the three-dimensional geological image, and determining an initial number level of stakeout points based on first geological morphological result data of the key area analysis result data of the three-dimensional geological image;

[0057] Step S4, determining an initial stakeout ratio according to the initial area and the initial quantity;

[0058] Step S5: During the tunneling process, a current tunneling angle is obtained, the current tunneling angle is compared with a preset tunneling angle range to obtain a comparison result of the tunneling arc of the curved section, an initial lofting ratio is adjusted according to the comparison result of the tunneling arc of the curved section to obtain a second lofting ratio, and advance geological drilling is performed according to the second lofting ratio to obtain advance detection result data and the analysis result data of the key areas of the 3D geological image to obtain a 3D geological image reconstruction model;

[0059] Step S6: tunnel reflection tomography is performed on the tunnel face in a preset detection range in the excavation direction to obtain tunnel face detection result image data; a coincidence check is performed on the three-dimensional geological image reconstruction model based on the tunnel face detection result image data to obtain a coincidence check result; and whether to perform additional detection is determined based on the coincidence check result.

[0060] This embodiment provides a step of obtaining an initial three-dimensional geological image of the area to be excavated, including:

[0061] Step S101, evenly install a number of mechanical seismic sources and seismic sensors on both sides of the tunnel;

[0062] Step S102, starting the mechanical seismic source to generate seismic waves, and the seismic sensor receives the reflected wave signal;

[0063] Step S103 : performing signal processing, inversion calculation, and three-dimensional reconstruction on the reflected wave signal to convert the reflected wave signal into an initial three-dimensional geological image.

[0064] Specifically, the process of imaging the area to be excavated by using the tunnel seismic wave reflection tomography technology to obtain an initial three-dimensional geological image of the area to be excavated includes:

[0065] Several mechanical seismic sources are installed on the side walls of the tunnel, and seismic sensors are installed at corresponding positions to receive reflected wave signals. The reflected wave signals are pre-processed and converted into initial three-dimensional geological images through tomography technology.

[0066] The present invention uses tunnel seismic reflection tomography to image the area to be excavated, generating an initial three-dimensional geological image of the area to be excavated. This allows for a preliminary determination of the approximate geological distribution and morphology within the area to be excavated, providing strong support for subsequent excavation construction. By combining tunnel seismic reflection tomography with advanced geological drilling, the geological conditions of the area to be excavated can be more accurately predicted, reducing uncertainty during construction. During excavation, the stakeout ratio is dynamically adjusted based on real-time excavation angles and geological data, ensuring the scientific and adaptable nature of the construction plan. Advanced geological drilling and tunnel face detection allow for the early detection of potential geological risks, enabling appropriate preventive measures to be taken and construction risks to be reduced. By analyzing key areas of the three-dimensional geological image and dynamically adjusting the stakeout ratio, drilling resources can be rationally allocated, avoiding unnecessary drilling work and improving construction efficiency. By verifying the three-dimensional geological image reconstruction model with the tunnel face detection results, the geology in the tunnel face excavation direction can be further detected to promptly identify geological anomalies, ensuring safety during construction. Accurate geological prediction and dynamic adjustment can reduce construction delays and additional costs caused by geological issues, thereby improving the economic benefits of the project.

[0067] The deployment of mechanical seismic sources and seismic sensors enables the acquisition of high-resolution seismic wave reflection signals, which, combined with tomography technology, generate high-precision 3D geological images. These images clearly depict the geological structure, lithologic distribution, and potential geological anomalies in the area to be excavated. This technology is a non-destructive exploration method that obtains underground geological information without drilling or damaging the rock mass. It is suitable for advanced geological exploration prior to tunnel excavation, minimizing the impact on construction progress. The simple deployment of mechanical seismic sources and seismic sensors allows for rapid data acquisition and processing, enabling the rapid generation of 3D geological images. This provides real-time geological information support for tunnel excavation and improves construction efficiency. By deploying multiple mechanical seismic sources and seismic sensors along the tunnel sidewalls, comprehensive coverage of the entire area to be excavated can be achieved. 3D geological images enable the early identification of potential geological risks, providing a scientific basis for the development of construction plans. This effectively reduces the probability of accidents such as landslides and water inrush during tunnel excavation. Based on 3D geological images, tunnel excavation plans can be optimized and excavation parameters can be rationally selected. By placing mechanical seismic sources and seismic sensors on the tunnel sidewalls and combining them with tomography to generate initial 3D geological images, high-precision, non-destructive, real-time, and efficient geological exploration can be achieved. This technology provides reliable geological information support for tunnel excavation, significantly reducing construction risks, optimizing construction plans, and saving costs, possessing significant engineering application value.

[0068] Specifically, the process of analyzing the geological distribution data and geological morphology data of the initial three-dimensional geological image to obtain the analysis result data of the key areas of the three-dimensional geological image includes:

[0069] Performing multi-dimensional analysis on the initial three-dimensional geological image to obtain geological distribution result data and geological morphology result data based on the initial three-dimensional geological image;

[0070] The multi-dimensional analysis includes geometric shape analysis, surface feature analysis and dynamic change analysis.

[0071] The steps of geometric shape analysis include analyzing the geometric shape characteristics of the geological interface, including data such as interface undulation, inclination, and curvature; calculating the geometric parameters of the geological interface using point cloud data or grid data in the initial three-dimensional geological image; extracting the geometric characteristics of the geological interface through an algorithm, wherein the geometric shape data of the geological interface (such as undulation height, inclination size, and curvature distribution) are included;

[0072] The surface feature analysis step involves analyzing the surface characteristics of the geological interface, including roughness, fracture distribution, and lithologic variations. The surface features of the geological interface are extracted using texture information and reflected wave signal characteristics from the initial 3D geological image. Surface fractures and lithologic variations are identified through image processing techniques (such as edge detection and texture analysis). Surface feature data of the geological interface (such as roughness distribution, fracture density, and areas of lithologic variation) are collected, and areas of abnormal surface characteristics (such as areas with dense fractures and areas of sudden lithologic changes) are identified.

[0073] The steps of dynamic change analysis include analyzing the dynamic change characteristics of the geological interface in space, including interface continuity and thickness changes; using the spatial distribution data in the initial three-dimensional geological image to analyze the change law of the geological interface in three-dimensional space; and extracting the dynamic change characteristics of the geological interface through interpolation algorithms or spatial statistical analysis.

[0074] In this example, 3D geological modeling software (such as Petrel and GOCAD) was used to analyze geometric shapes and surface features, and image processing algorithms (such as edge detection and curvature calculation) were used to extract geological interface features. Geometric shape analysis included curvature calculation and inclination analysis algorithms. Surface feature analysis included texture analysis and fracture identification algorithms. Dynamic change analysis included spatial interpolation and statistical analysis algorithms.

[0075] Through multi-dimensional analysis, faults, karst caves, weak interlayers, and other geological anomalies can be accurately identified. Targeted construction plans (such as strengthening support and adjusting excavation parameters) can be formulated for key areas. Potential geological risks can be discovered in advance to reduce the occurrence of accidents such as landslides and water gushing. By performing geometric shape analysis, surface feature analysis, and dynamic change analysis on the initial three-dimensional geological image, the geological distribution and morphological characteristics of the area to be excavated can be fully understood, key areas can be accurately identified, and a scientific basis can be provided for tunnel excavation, significantly reducing construction risks and improving construction efficiency.

[0076] Specifically, the process of determining whether to conduct advance geological drilling in the area to be excavated based on the analysis result data of the key areas of the three-dimensional geological image includes:

[0077] The geological distribution result data and the geological morphology result data are normalized to obtain an overlap characteristic value, and the overlap characteristic value is compared with a preset standard overlap characteristic value to obtain a first overlap range comparison result. Based on the first overlap range comparison result, it is determined whether to perform advance geological drilling on the area to be excavated.

[0078] If the first overlap range comparison result shows that the overlap characteristic value is greater than the standard overlap characteristic value, advance geological drilling is required in the area to be excavated;

[0079] If the comparison result of the first overlap range shows that the overlap characteristic value is less than or equal to the standard overlap characteristic value, there is no need to perform advance geological drilling in the excavation area.

[0080] Data normalization: First, the geological distribution data and the geological morphology data are normalized. The purpose of normalization is to bring data of different dimensions or ranges to the same scale, facilitating subsequent comparison and analysis. For example, suppose the geological distribution data is the rock hardness value of a certain area (range 0-100), and the geological morphology data is the inclination angle of the formation (range 0-90 degrees). Through normalization, these data are converted to values between 0 and 1. The normalized geological distribution data and geological morphology data are then overlaid and analyzed to calculate the overlap eigenvalue. The overlap eigenvalue reflects the degree of spatial consistency between the two data sets. For example, if the normalized rock hardness value in a certain area is 0.8 and the formation inclination is 0.7, then a weighted or calculated method (such as average or weighted average) can be used to determine the overlap eigenvalue, assuming it is 0.75. The calculated overlap eigenvalue is then compared with a preset standard overlap eigenvalue. The standard overlap eigenvalue is a threshold set based on historical data and is used to determine whether advance geological drilling is necessary.

[0081] For example, assuming that the preset standard coincidence characteristic value is 0.6, and the calculated coincidence characteristic value is 0.75, then the comparison result is 0.75>0.6, indicating that the geological conditions in the area are relatively complex or there are potential risks, and advanced geological drilling is needed to further confirm the geological conditions.

[0082] Normalizing the geological distribution and morphological data eliminates differences in dimension and range, enabling comparison and analysis at the same scale and improving the accuracy of the decision. Calculating the overlap characteristic value comprehensively reflects the spatial consistency of geological distribution and morphology, avoiding the limitations of a single data metric and improving the accuracy of the decision. Presetting a standard overlap characteristic value quantifies the decision-making process, eliminating the influence of subjective experience and making the decision more objective and reliable. Comparing the calculated overlap characteristic value with the standard value enables a clear judgment on whether advance geological drilling is necessary, reducing decision-making uncertainty. If the overlap characteristic value is greater than the standard value, it indicates that the geological conditions in the area are complex or there are potential risks, necessitating advance geological drilling. This allows for targeted resource allocation and avoids blind drilling. If the overlap characteristic value is less than or equal to the standard value, the geological conditions in the area are relatively simple, eliminating the need for advance geological drilling, thus saving manpower, material resources, and time. By analyzing the coincident eigenvalues, areas with complex geological conditions or potential risks can be identified in advance, providing a basis for advanced geological drilling and thus reducing the risk of geological hazards encountered during excavation. Advance geological drilling can further confirm the geological conditions, provide reliable geological data support for excavation projects, and ensure construction safety and smooth progress. For areas requiring drilling, drilling points can be rationally arranged based on the size of the coincident eigenvalues, improving drilling accuracy and efficiency. In actual projects, the standard coincident eigenvalues can be dynamically adjusted based on new geological data, making the judgment process more flexible and adaptable. This method, based on the results of three-dimensional geological image analysis, implements a data-driven decision-making process through data normalization, eigenvalue calculation, and comparative analysis, in line with the development trend of modern engineering management.

[0083] Specifically, in the case where advance geological drilling is required for the area to be excavated, the process of determining the initial area of the stakeout point based on the first geological distribution result data of the key area analysis result of the three-dimensional geological image includes:

[0084] The distribution range and distribution density of the geological anomaly area are determined based on the first geological distribution result data, the initial area is determined according to the distribution range, and the number and level of initial stakeout points in the initial area are determined according to the distribution density.

[0085] Based on the first geological distribution data (such as lithology, fault distribution, and groundwater distribution), the approximate scope of geological anomaly areas (such as fault zones, weak interlayers, and karst caves) is identified. Through 3D geological image analysis, the boundary information of the geological anomaly area is extracted and its spatial distribution range is determined.

[0086] Assume that a fault zone is discovered in the 3D geological image of the area to be excavated. Its distribution range is 50 meters along the excavation direction and 10 meters wide. Based on this distribution range, it can be preliminarily determined that the area affected by the fault zone is a rectangular area 50 meters in the excavation direction and 10 meters wide.

[0087] According to the distribution range of the geological anomaly area, it is divided into several initial areas to facilitate the layout of subsequent stakeout points. According to the shape and size of the geological anomaly area, it is divided into several regular sub-areas (such as rectangles, circles or other geometric shapes).

[0088] For the above-mentioned fault zone area of 50 meters × 10 meters, it can be divided into 5 initial areas, each of which is 10 meters × 10 meters in size. Each initial area corresponds to a local fault zone range, which is convenient for the arrangement of subsequent stakeout points.

[0089] According to the distribution density of geological anomaly areas (such as fault density, lithology change frequency, etc.), the geological complexity of each initial area is evaluated, and the distribution density is calculated by counting the geological anomaly characteristics in each initial area (such as the number of faults, the number of lithology changes, etc.).

[0090] Suppose that within a certain initial area (10 m x 10 m), the fault density is high, and statistics show that three faults pass through this area. In contrast, within another initial area, the fault density is low, with only one fault passing through it. Based on the fault density, we can determine that the geological complexity of the first initial area is higher, while that of the second area is lower. The number of stakeout points is determined based on the distribution density of each initial area. The higher the distribution density, the more stakeout points are required; the lower the distribution density, the fewer the stakeout points are required. Based on the preset correspondence between distribution density and the number of stakeout points, the number of stakeout points for each initial area is determined.

[0091] For example:

[0092] Assume that the preset number of stakeout points is as follows:

[0093] High-density area: 5 stakeout points are arranged in each initial area;

[0094] Medium-density area: 3 stakeout points are arranged in each initial area;

[0095] Low-density area: one stakeout point is arranged in each initial area;

[0096] For the initial area with a higher fault density, it belongs to a high-density area, so 5 stakeout points are arranged.

[0097] For the initial area with low fault density, it belongs to the low-density area, so one stakeout point is arranged.

[0098] By analyzing the distribution of geologically anomalous areas, the area to be excavated is divided into several initial zones, making the layout of stakeout points more scientific and rational. The number of stakeout points is dynamically adjusted based on the geological complexity of each initial zone, ensuring more stakeout points in high-density areas and fewer in low-density areas, improving the targeted layout. By rationally allocating stakeout points based on density, excessive stakeout points in low-density areas are avoided, saving manpower, material resources, and time. Concentrating more stakeout points in high-density areas allows for more comprehensive geological information, improves drilling efficiency, and reduces duplication of effort. By analyzing the distribution and density of geologically anomalous areas, high-risk areas (such as areas with dense faults and developed karst caves) can be identified in advance, providing a basis for advanced geological drilling and reducing the risk of geological hazards (such as landslides and water inrush) encountered during excavation. By placing more stakeout points in high-density areas, a more accurate understanding of the geological conditions is achieved, providing data support for adjusting construction plans and ensuring construction safety. By dividing the initial area and arranging stakeout points based on density, we ensure that every local area within the geological anomaly is covered, preventing the omission of important geological information. Placing more stakeout points in high-density areas allows for more detailed geological data, improving its accuracy and reliability. This method comprehensively considers the distribution and density of geological anomalies, adapting to analysis requirements under complex geological conditions and providing comprehensive geological information support for tunneling projects.

[0099] Specifically, the process of determining the initial number level of the stakeout points based on the first geological morphological result data of the key area analysis result data of the three-dimensional geological image includes:

[0100] The first geological morphology result data is analyzed to obtain the geological morphology category of the area to be excavated, and the quantity level of the initial quantity is determined based on the geological morphology category.

[0101] Identify geological morphological categories through 3D geological image analysis. Geological morphological categories can include:

[0102] Dip angle of the formation: the inclination angle of the formation (such as horizontal, gently inclined, steeply inclined, etc.);

[0103] Layer thickness: thickness variation of the rock layer (e.g. uniform, thin, thick, etc.);

[0104] Fault characteristics: type of fault (e.g. normal fault, reverse fault, etc.) and size;

[0105] Cave development: the distribution density and scale of caves;

[0106] Joint development: density and directionality of joints;

[0107] For example:

[0108] Assume that by analyzing the first geological morphology result data, it is found that the stratum inclination of the area to be excavated is 30°, the rock layer thickness is uniform, the fault density is low, and the cave development is relatively small. According to the geological morphology characteristics, the area to be excavated is divided into different geological morphology categories. Based on the preset classification criteria, the geological morphology characteristics are classified into different categories.

[0109] The preset geological morphology classification standards are as follows:

[0110] Category A: The formation dip is less than 15°, the rock layer thickness is uniform, the fault density is low, and there are few caves;

[0111] Category B: The formation dip angle is 15°-45°, the rock thickness varies moderately, the fault density is moderate, and the cave development is moderate;

[0112] Category C: The formation dip is greater than 45°, the rock thickness varies greatly, the fault density is high, and there are many caves;

[0113] According to the above classification standards, the geological morphology category of the area to be excavated is Category B.

[0114] Determine the initial quantitative level based on geological morphological categories

[0115] According to the geological morphology category, determine the number and level of stakeout points in each initial area.

[0116] Based on the preset staking point quantity level rules, the corresponding number of staking points is assigned to each geological morphology category. For example, the preset staking point quantity level rules are as follows:

[0117] Category A: low-density area, one stakeout point is arranged in each initial area;

[0118] Category B: Medium-density area, with 3 stakeout points arranged in each initial area;

[0119] Category C: High-density area, 5 stakeout points are arranged in each initial area;

[0120] Since the geological morphology of the area to be excavated is category B, three stakeout points are arranged in each initial area.

[0121] In a tunnel excavation project, a first geological morphology result data is obtained by analyzing key areas of a three-dimensional geological image. The geological morphology characteristics of the area to be excavated are as follows:

[0122] Stratum dip: 25° (gentle); Stratum thickness: moderately variable,

[0123] Fault density: Medium (two faults per 10 m x 10 m area);

[0124] Cave development: moderate (one small cave per 10m x 10m area);

[0125] Extracted geological features: stratum dip angle of 25°, moderate variation in rock thickness, moderate fault density, and moderate cave development. Based on the preset classification criteria, the geological morphology of this area is Category B. According to the rules for the number of stakeout points, Category B corresponds to three stakeout points for each initial area.

[0126] Specifically, the process of comparing the current excavation angle with a preset excavation angle range to obtain a curve segment excavation arc comparison result, and adjusting the initial lofting ratio according to the curve segment excavation arc comparison result to obtain a second lofting ratio includes:

[0127] If the comparison result of the excavation arc of the curved section shows that the current excavation angle is greater than the maximum value of the preset excavation angle range, the excavation angle of the excavation device is adjusted;

[0128] If the comparison result of the excavation arc of the curved section shows that the current excavation angle is less than the minimum value of the preset excavation angle range, adjusting the initial setting out ratio;

[0129] If the comparison result of the excavation arc of the curved section shows that the current excavation angle is within the preset excavation angle range, there is no need to adjust the initial layout ratio and the excavation angle of the excavation device.

[0130] The initial stakeout ratio is determined based on the quotient of the initial quantity and the initial area. The measurement system equipped on modern roadheaders monitors the current tunneling angle. The preset tunneling angle range is determined based on 3D geological images and engineering design parameters.

[0131] A tunnel project is currently excavating a curved section. The preset excavation angle range is 2° to 4°, the initial scale is 1:200, and the excavation device is a tunnel boring machine.

[0132] Using the tunnel boring machine's built-in measurement system, real-time monitoring shows that the current excavation angle is 3.5°. By comparing the current excavation angle with the preset excavation angle range,

[0133] If the comparison result of the excavation arc of the curved section shows that the current excavation angle is within the preset excavation angle range, there is no need to adjust the initial setting out ratio and the tunnel boring machine excavation angle. The current excavation angle is 3.5°, and the preset range is 2° to 4°. If the current excavation angle is within the preset range, there is no need to adjust the initial setting out ratio and the tunnel boring machine excavation angle, and excavation continues according to the current parameters.

[0134] If the comparison result of the excavation arc of the curved section shows that the current excavation angle is greater than the maximum value of the preset excavation angle range, the excavation angle of the excavation device is adjusted.

[0135] The current excavation angle is 4.5°, and the preset maximum excavation angle range is 4°. The excavation angle of the tunnel boring machine is adjusted. According to the difference between the current excavation angle and the maximum value of the preset excavation angle range and the effect of the difference between the current excavation angle and the maximum value of the preset excavation angle range on the inclination of the cutterhead, the inclination of the cutterhead is adjusted by the compensation parameter so that the excavation angle is reduced to within 4°.

[0136] Set the compensation parameter for the effect of the difference between the current excavation angle and the maximum value of the preset excavation angle range on the inclination of the cutter head to 0.5, and then adjust the inclination of the cutter head to the initial inclination angle of 0.5°×0.5=0.25°;

[0137] For the case where the comparison result of the excavation arc of the curved section shows that the current excavation angle is less than the minimum value of the preset excavation angle range, the initial lofting ratio is adjusted according to the compensation parameter based on the difference between the current excavation angle and the minimum value of the preset excavation angle range and the influence of the difference between the current excavation angle and the minimum value of the preset excavation angle range on the initial lofting ratio. The initial lofting ratio is adjusted when the current excavation angle is 1.5° and the minimum value of the preset range is 2°.

[0138] The image compensation parameter for the initial stakeout ratio, calculated based on the difference between the current excavation angle and the minimum preset excavation angle range, is set to 1. Assuming that each 1° difference corresponds to a 20-unit adjustment in the stakeout ratio (i.e., 1:200 is adjusted to 1:180), a 0.5° difference results in an adjustment of 0.5 × 20 = 10 units, resulting in a 1:190 scale. Adjusting the scale from 1:200 to 1:190 means placing more stakeout points within the same area, increasing the coverage density of the advanced geological drilling.

[0139] When the current excavation angle exceeds the maximum excavation angle range, the cutterhead inclination of the tunnel boring machine (TBM) is adjusted, thereby ensuring the excavation direction aligns with the designed axis and preventing deviation from the designed trajectory, thereby improving construction accuracy and safety. When the current excavation angle is less than the minimum excavation angle range, the initial stakeout ratio is adjusted, increasing the number of stakeout points and increasing the coverage density of advance geological drilling, ensuring the comprehensiveness and accuracy of geological data and reducing construction risks. By monitoring the current excavation angle in real time and dynamically adjusting excavation parameters, it can adapt to construction needs under complex geological conditions and reduce the occurrence of geological hazards such as landslides and water inrush. Adjusting the stakeout ratio based on geological conditions and excavation angle ensures sufficient coverage of high-risk areas (such as fault zones and karst caves), improving construction safety. When the excavation angle is within the preset range, there is no need to adjust the stakeout ratio or excavation angle, avoiding unnecessary waste of resources. This dynamic adjustment ensures the scientific nature of the excavation direction and stakeout point layout, reduces duplication of work and construction delays, and improves construction efficiency. By setting the cutterhead inclination compensation parameters and the layout ratio compensation parameters, the construction parameters can be flexibly adjusted according to the difference between the actual excavation angle and the preset range, thereby enhancing the adaptability and flexibility of the construction.

[0140] Specifically, the process of obtaining the advance detection result data and the three-dimensional geological image key area analysis result data by the advance geological drilling determined according to the second lofting ratio to obtain the three-dimensional geological image reconstruction model includes:

[0141] The advanced detection result data and the three-dimensional geological image key area analysis result data are subjected to data preprocessing and data fusion operations to obtain a three-dimensional geological image reconstruction model.

[0142] The data processing steps of the advanced detection results include:

[0143] Step S511, removing noise, outliers and duplicate data;

[0144] Step S512, converting the data obtained by different detection devices into a unified format;

[0145] Step S513: interpolation processing is performed on the missing data points to increase the data density and convert the detection data from the device coordinate system to the tunnel coordinate system.

[0146] The data processing steps for the analysis results of key areas of 3D geological images include:

[0147] Step S521, improving image contrast and clarity, and highlighting key area features;

[0148] Step S522, separating the key area from the background;

[0149] Step S523: extracting geometric, texture and other features of the key area.

[0150] The advanced detection result data and the analysis result data of key areas of the 3D geological image are spatially aligned to ensure that the data are in a unified coordinate system; according to the data characteristics and engineering requirements, appropriate data fusion methods are selected, such as weighted fusion, interpolation fusion, model fusion, etc.; data fusion parameters such as weights, interpolation methods, model parameters, etc. are set to obtain the best fusion effect; and data fusion operations are performed to generate a fused 3D geological image reconstruction model.

[0151] Data preprocessing improves the accuracy and reliability of advanced exploration data. Data from different exploration devices are converted to a unified format to facilitate subsequent data fusion and analysis. Missing data points are interpolated to increase data density and ensure spatial continuity and integrity. Improving image contrast and clarity enhances the geological features of key areas, making them easier for engineers to identify and analyze. Key areas are separated from the background, highlighting critical geological information and reducing interference. Geometric and texture features of key areas are extracted, providing a foundation for subsequent data fusion and model reconstruction. Advanced exploration data and key area analysis data from 3D geological images are spatially registered to ensure a unified coordinate system and improve spatial consistency. Exploration data are converted from the device coordinate system to the tunnel coordinate system to facilitate comparison and analysis with engineering design parameters and construction data. Based on data characteristics and project requirements, weighted fusion, interpolation fusion, and model fusion methods are selected to ensure optimal fusion results. By setting weights, interpolation methods, and model parameters, the data fusion process is optimized to generate a high-precision 3D geological image reconstruction model. Perform data fusion operations to organically combine the advanced detection result data with the analysis result data of key areas of the 3D geological image to generate a comprehensive and accurate 3D geological image reconstruction model.

[0152] Specifically, the process of obtaining tunnel face detection result image data based on tunnel reflection tomography within a preset detection range in the tunneling direction, and performing coincidence verification on the three-dimensional geological image reconstruction model according to the tunnel face detection result image data to obtain a coincidence verification result includes:

[0153] performing geological feature comparison between the tunnel face detection result image data and the corresponding image area in the three-dimensional geological image reconstruction model, determining an actual coincidence degree based on the geological feature comparison result, and comparing the actual coincidence degree with a standard coincidence degree to obtain a coincidence degree comparison result;

[0154] The preset detection range is determined according to the current excavation progress; the geological characteristics include rock stability and fault location.

[0155] Specifically, the process of determining whether to perform additional detection according to the coincidence verification result includes:

[0156] Based on the coincidence comparison result, it is determined whether to perform additional detection on the area to be excavated.

[0157] In this embodiment, the preset detection range is set to 15 to 25 meters ahead, and the standard coincidence is set to 95%;

[0158] Based on the current excavation progress of 150 meters, the preset detection range is determined to be an area 15 to 25 meters ahead, and a tunnel reflection tomography system is set up for detection. The tunnel reflection tomography system is operated to detect the tunnel face, collect and process the detection data, and generate tunnel face detection image data. Geological features, including rock layer stability and fault location, are extracted from the tunnel face detection image data. Within the 3D geological image reconstruction model, the image area corresponding to the tunnel face detection image data is identified.

[0159] Compare the geological features between the two:

[0160] The tunnel face detection results showed that the rock formation 20 meters ahead was less stable, while the model predicted that this area was more stable.

[0161] The tunnel face detection results showed a fault 22 meters ahead, while the model predicted the fault location to be 21 meters ahead.

[0162] According to the geological feature comparison results, the overlap between the tunnel face detection image data and the three-dimensional geological image reconstruction model is assessed to be 90%.

[0163] Comparing the actual coincidence with the standard coincidence, the actual coincidence is lower than the standard coincidence. Since the actual coincidence is lower than the standard coincidence, it shows that there are certain differences between the model and the actual geological conditions. In order to ensure construction safety and accurate understanding of the geological conditions ahead, it was decided to conduct additional detection in the area 15 to 25 meters ahead. The additional detection is advanced geological drilling until the three-dimensional geological image reconstruction model approaches the real geological image.

[0164] Coincidence verification and supplementary surveys provide a more accurate understanding of the geological conditions ahead, enabling timely identification of potential risks such as unstable rock formations and faults. This allows for proactive countermeasures and prevents accidents during construction. Based on accurate geological information, the construction team can more effectively plan excavation paths and construction methods, avoiding large-scale excavation in unstable areas and reducing construction difficulty and costs. Confirming geological conditions through supplementary surveys reduces work stoppages and rework due to geological uncertainty, improving construction efficiency and shortening the project schedule. Accurate geological information and coincidence verification results provide solid data support for construction decisions, strengthening the confidence of the construction team and relevant personnel in the construction plan. By avoiding unnecessary excavation and support in unstable areas, construction costs can be significantly reduced, improving the project's economic benefits. Accurate geological information and a sound construction plan ensure the quality of tunnel construction and extend its service life.

[0165] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0166] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A tunnel advance detection method for TBM hard rock excavation in curved sections, characterized in that: The following steps are included: Imaging the area to be excavated by using tunnel seismic wave reflection tomography technology to obtain an initial three-dimensional geological image of the area to be excavated; Analyzing geological distribution data and geological morphology data of the initial three-dimensional geological image to obtain analysis result data of key areas of the three-dimensional geological image, and determining whether to perform advance geological drilling on the area to be excavated based on the analysis result data of key areas of the three-dimensional geological image; In the case where advance geological drilling is required for the area to be excavated, an initial area for the stakeout points is determined based on the first geological distribution result data of the key area analysis result data of the three-dimensional geological image, and an initial number level of the stakeout points is determined based on the first geological morphological result data of the key area analysis result data of the three-dimensional geological image; determining an initial stakeout ratio according to the initial area and the initial quantity; During the excavation process, a current excavation angle is obtained, the current excavation angle is compared with a preset excavation angle range to obtain a comparison result of the excavation arc of the curved section, an initial lofting ratio is adjusted according to the comparison result of the excavation arc of the curved section to obtain a second lofting ratio, and advance geological drilling is determined according to the second lofting ratio to obtain advance detection result data and the analysis result data of the key areas of the three-dimensional geological image to obtain a three-dimensional geological image reconstruction model; Tunnel face detection result image data is obtained based on tunnel reflection tomography within a preset detection range of the tunnel face in the excavation direction. Coincidence verification is performed on the three-dimensional geological image reconstruction model based on the tunnel face detection result image data to obtain a coincidence verification result. Whether to perform additional detection is determined based on the coincidence verification result.

2. The tunnel advance detection method for TBM hard rock excavation in curved sections according to claim 1 is characterized in that: The process of imaging the area to be excavated by using the tunnel seismic wave reflection tomography technology to obtain an initial three-dimensional geological image of the area to be excavated includes: Several mechanical seismic sources are installed on the side walls of the tunnel, and seismic sensors are installed at corresponding positions to receive reflected wave signals. The reflected wave signals are pre-processed and converted into initial three-dimensional geological images through tomography technology.

3. The tunnel advance detection method for TBM hard rock excavation in curved sections according to claim 2 is characterized in that: The process of analyzing the geological distribution data and geological morphology data of the initial three-dimensional geological image to obtain the analysis result data of the key areas of the three-dimensional geological image includes: Performing multi-dimensional analysis on the initial three-dimensional geological image to obtain geological distribution result data and geological morphology result data based on the initial three-dimensional geological image; The multi-dimensional analysis includes geometric shape analysis, surface feature analysis and dynamic change analysis.

4. The tunnel advance detection method for TBM hard rock excavation in curved sections according to claim 3 is characterized in that: The process of determining whether to conduct advance geological drilling in the area to be excavated based on the analysis result data of the key areas of the three-dimensional geological image includes: The geological distribution result data and the geological morphology result data are normalized to obtain an overlap characteristic value, and the overlap characteristic value is compared with a preset standard overlap characteristic value to obtain a first overlap range comparison result. Based on the first overlap range comparison result, it is determined whether to perform advance geological drilling on the area to be excavated.

5. The tunnel advance detection method for TBM hard rock excavation in curved sections according to claim 4 is characterized in that: In the case where advance geological drilling is required for the area to be excavated, the process of determining the initial area of the stakeout point based on the first geological distribution result data of the key area analysis result of the three-dimensional geological image includes: The distribution range and distribution density of the geological anomaly area are determined based on the first geological distribution result data, the initial area is determined according to the distribution range, and the number and level of initial stakeout points in the initial area are determined according to the distribution density.

6. The method for tunnel advance detection for hard rock excavation by TBM in curved sections according to claim 5, characterized in that: The process of determining the initial number level of the stakeout points based on the first geological morphological result data of the key area analysis result data of the three-dimensional geological image includes: The first geological morphology result data is analyzed to obtain the geological morphology category of the area to be excavated, and the quantity level of the initial quantity is determined based on the geological morphology category.

7. The tunnel advance detection method for TBM hard rock excavation in curved sections according to claim 6, characterized in that: The process of comparing the current excavation angle with a preset excavation angle range to obtain a curve segment excavation arc comparison result, and adjusting the initial lofting ratio according to the curve segment excavation arc comparison result to obtain a second lofting ratio includes: If the comparison result of the excavation arc of the curved section shows that the current excavation angle is greater than the maximum value of the preset excavation angle range, the excavation angle of the excavation device is adjusted; If the comparison result of the excavation arc of the curved section shows that the current excavation angle is less than the minimum value of the preset excavation angle range, adjusting the initial setting out ratio; If the comparison result of the excavation arc of the curved section shows that the current excavation angle is within the preset excavation angle range, there is no need to adjust the initial layout ratio and the excavation angle of the excavation device.

8. The method for tunnel advance detection for hard rock excavation by TBM in curved sections according to claim 7, characterized in that: The process of obtaining the advance geological drilling determined according to the second lofting ratio to obtain the advance detection result data and the three-dimensional geological image key area analysis result data to obtain the three-dimensional geological image reconstruction model includes: The advanced detection result data and the three-dimensional geological image key area analysis result data are subjected to data preprocessing and data fusion operations to obtain a three-dimensional geological image reconstruction model.

9. The method for tunnel advance detection in hard rock excavation by TBM in curved sections according to claim 8, characterized in that: The process of obtaining tunnel face detection result image data based on tunnel reflection tomography within a preset detection range of the tunnel face in the excavation direction, and performing coincidence verification on the three-dimensional geological image reconstruction model according to the tunnel face detection result image data to obtain a coincidence verification result includes: performing geological feature comparison between the tunnel face detection result image data and the corresponding image area in the three-dimensional geological image reconstruction model, determining an actual coincidence degree based on the geological feature comparison result, and comparing the actual coincidence degree with a standard coincidence degree to obtain a coincidence degree comparison result; The preset detection range is determined according to the current excavation progress; the geological characteristics include rock stability and fault location.

10. The tunnel advance detection method for TBM hard rock excavation in curved sections according to claim 9, characterized in that: The process of determining whether to perform additional detection according to the coincidence verification result includes: Based on the coincidence comparison result, it is determined whether to perform additional detection on the area to be excavated.

Images