Tunnel bolt support fine intervention method and product based on multi-source monitoring information

Abstract

The present invention provides a method and product for fine intervention of tunnel anchor support based on multi-source monitoring information, and relates to the field of geological engineering technology. In the method for fine intervention of tunnel anchor support based on multi-source monitoring information provided by the embodiment of the present invention, geological monitoring data can be fully utilized to carry out scientific design of tunnel support. In the embodiment of the present invention, the scope of the surrounding rock disturbance zone can be accurately determined based on the geological monitoring data, so that the anchor can be effectively controlled to accurately intervene in the surrounding rock disturbance zone, give full play to the support efficiency of the support structure, improve the construction safety of the tunnel, and accelerate the construction progress.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of geological engineering technology, and in particular to a tunnel anchor support fine intervention method and product based on multi-source monitoring information. Background Art

[0002] As underground projects continue to develop deeper, they generally face complex conditions such as high stress, rich faults, and strong disturbances. During the construction process, disasters such as large deformation of surrounding rock, landslides, and rock bursts are prone to occur, leading to the destruction and collapse of tunnel (tunnel) surrounding rock, posing a great threat to project safety.

[0003] As the core of surrounding rock control in underground projects, anchor support can work with surrounding rock to change the mechanical state of surrounding rock itself and form a composite arch, and use the joint action of anchor and surrounding rock to maintain tunnel stability. Therefore, the safety, reliability and accuracy of tunnel support design directly affect the safety, economy and social benefits of the project.

[0004] The existing tunnel support design is mainly based on geological information and project scale. The traditional standard generalized design is relatively rough, and the monitoring data is not fully used in the scientific design of tunnel support. When the traditional anchor support method is used to design the support of deep surrounding rock, the anchor rod cannot accurately intervene in the surrounding rock damage structure, and the bearing capacity of the surrounding rock structure cannot be maximized. The tunnel support structure cannot fully guarantee the long-term stability of the underground project under the action of dynamic disasters. Summary of the invention

[0005] The embodiment of the present invention provides a tunnel bolt support fine intervention method based on multi-source monitoring information to at least partially solve the problems existing in the related art.

[0006] A first aspect of an embodiment of the present invention provides a tunnel bolt support fine intervention method based on multi-source monitoring information, the method comprising:

[0007] Obtaining the surrounding rock mechanical parameters and geological monitoring data of the tunnel to be reinforced, wherein the geological monitoring data includes displacement data, surrounding rock loosening zone data, three-dimensional laser scanning data and microseismic monitoring data;

[0008] Determine the displacement gradient according to the displacement data, determine the shallow damage factor according to the surrounding rock loosening zone data, determine the point cloud data features according to the three-dimensional laser scanning data, and determine the deep damage factor according to the microseismic monitoring data;

[0009] According to the displacement gradient, the shallow damage factor, the point cloud data characteristics and the deep damage factor, three-dimensional damage zone geological modeling is performed based on an implicit function model;

[0010] According to the three-dimensional damage zone data generated by the implicit function model, the distribution of damage factors is analyzed to determine the scope of the surrounding rock disturbance zone;

[0011] The anchor support intervention scheme is determined according to the surrounding rock mechanical parameters of the tunnel to be reinforced and the range of the surrounding rock disturbance zone, and the anchor support intervention scheme includes: the installation position of the anchor and the length of the anchor.

[0012] A second aspect of an embodiment of the present invention provides a tunnel bolt support fine intervention device based on multi-source monitoring information, the device comprising:

[0013] A data acquisition module is used to acquire the surrounding rock mechanical parameters and geological monitoring data of the tunnel to be reinforced, wherein the geological monitoring data includes displacement data, surrounding rock loosening zone data, three-dimensional laser scanning data and microseismic monitoring data;

[0014] A data processing module, used to determine a displacement gradient according to the displacement data, determine a shallow damage factor according to the surrounding rock loosening zone data, determine point cloud data features according to the three-dimensional laser scanning data, and determine a deep damage factor according to the microseismic monitoring data;

[0015] A modeling module, used for performing three-dimensional damage zone geological modeling based on an implicit function model according to the displacement gradient, the shallow damage factor, the point cloud data characteristics and the deep damage factor;

[0016] The analysis module is used to analyze the distribution of damage factors and determine the range of the surrounding rock disturbance zone based on the three-dimensional damage zone data generated by the implicit function model;

[0017] The support intervention scheme determination module is used to determine the anchor support intervention scheme according to the surrounding rock mechanical parameters of the tunnel to be reinforced and the range of the surrounding rock disturbance zone, and the anchor support intervention scheme includes: the installation position of the anchor and the length of the anchor.

[0018] A third aspect of an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when executed, the processor implements the tunnel anchor support fine intervention method based on multi-source monitoring information as described in the first aspect of the present invention.

[0019] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the tunnel anchor support fine intervention method based on multi-source monitoring information as described in the first aspect of the present invention.

[0020] A fifth aspect of an embodiment of the present invention provides a computer program product, including a computer program / instruction, which is used by a processor to implement the steps of the tunnel bolt support fine intervention method based on multi-source monitoring information as described in the first aspect of the present invention.

[0021] In the tunnel anchor support fine intervention method based on multi-source monitoring information provided in the embodiment of the present invention, geological monitoring data can be fully utilized to carry out scientific design of tunnel support. In the embodiment of the present invention, the scope of the surrounding rock disturbance zone can be accurately determined based on the geological monitoring data, so that the anchor can be effectively controlled to accurately intervene in the surrounding rock disturbance zone, give full play to the support efficiency of the support structure, improve the construction safety of the tunnel, and accelerate the construction progress. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0023] Figure 1 A flowchart showing the steps of a tunnel bolt support fine intervention method based on multi-source monitoring information provided by an embodiment of the present invention is shown;

[0024] Figure 2 A schematic diagram of three-dimensional damaged area data obtained in a tunnel bolt support fine intervention method based on multi-source monitoring information provided by an embodiment of the present invention is shown;

[0025] Figure 3 A schematic diagram of an anchor support intervention scheme determined in a tunnel anchor support fine intervention method based on multi-source monitoring information provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0026] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] In an embodiment of the present invention, a tunnel bolt support fine intervention method based on multi-source monitoring information is provided. Figure 1 As shown, Figure 1 The flowchart of the steps of the tunnel bolt support fine intervention method based on multi-source monitoring information provided by an embodiment of the present invention is shown; specifically, the method comprises the following steps:

[0028] S101, obtaining mechanical parameters of the surrounding rock and geological monitoring data of the tunnel to be reinforced, wherein the geological monitoring data includes displacement data, surrounding rock loosening zone data, three-dimensional laser scanning data and microseismic monitoring data;

[0029] S102, determining a displacement gradient according to the displacement data, determining a shallow damage factor according to the surrounding rock loosening zone data, determining point cloud data features according to the three-dimensional laser scanning data, and determining a deep damage factor according to the microseismic monitoring data;

[0030] S103, performing three-dimensional geological modeling of the damaged area based on an implicit function model according to the displacement gradient, the shallow damage factor, the point cloud data feature and the deep damage factor;

[0031] S104, analyzing the distribution of damage factors based on the three-dimensional damage zone data generated by the implicit function model, and determining the range of the surrounding rock disturbance zone;

[0032] S105, determining an anchor support intervention plan according to the surrounding rock mechanical parameters of the tunnel to be reinforced and the range of the surrounding rock disturbance zone, wherein the anchor support intervention plan includes: an installation position of the anchor and a length of the anchor.

[0033] In the actual construction process, in order to improve the precision and accuracy of monitoring and effectively reveal the scope of the tunnel excavation damage area, the embodiment of the present invention divides the long tunnel into several 20-meter unit tunnel sections for monitoring and analysis.

[0034] In the embodiment of the present invention, the geological monitoring data can be fully utilized to carry out scientific design of tunnel support. In the embodiment of the present invention, the scope of the surrounding rock disturbance zone can be accurately determined based on the geological monitoring data, so that the anchor rods can be effectively controlled to accurately intervene in the surrounding rock disturbance zone, the support efficiency of the support structure can be fully utilized, the construction safety of the tunnel can be improved, and the construction progress can be accelerated.

[0035] In an optional implementation, based on the above embodiment, step S101 in the tunnel bolt support fine intervention method based on multi-source monitoring information includes the following sub-steps:

[0036] S1011, obtaining displacement data collected by displacement meters respectively arranged at a plurality of displacement meter position points of the tunnel to be reinforced, wherein the displacement data includes: displacement meter position points, timestamps and displacement values;

[0037] S1012, obtaining surrounding rock loosening zone data obtained by drilling observation distributed at multiple drilling positions of the tunnel to be reinforced, wherein the surrounding rock loosening zone data includes: drilling position points, loosening zone thickness and depth range;

[0038] S1013, obtaining three-dimensional laser scanning data obtained by scanning the tunnel to be reinforced using a three-dimensional laser scanner, wherein the three-dimensional laser scanning data includes: point cloud coordinates and reflection intensity;

[0039] S1014, obtaining microseismic monitoring data recorded by microseismic monitoring sensors arranged inside the underground rock mass of the tunnel to be reinforced, wherein the microseismic monitoring data includes: a timestamp, a microseismic event location, a frequency, and an energy.

[0040] In the embodiment of the present invention, a plurality of data acquisition devices are arranged in the tunnel to be reinforced to collect corresponding geological monitoring data. Specifically, a group of displacement meters is installed at intervals of 80 to 120 m in the tunnel to be reinforced, and each group of displacement meters includes: a plurality of displacement meters respectively installed at corresponding positions of the tunnel top, upstream and downstream spandrels and side walls.

[0041] Specifically, the displacement meter location points refer to multiple location points determined at intervals of 80 to 120 m on the roof, upstream and downstream spandrels, and side walls of the tunnel to be reinforced.

[0042] In the embodiment of the present invention, a group of borehole acoustic wave and imaging test holes is distributed every 80-120 m in the tunnel to be reinforced, and each group of boreholes includes: a plurality of boreholes distributed at corresponding positions of the tunnel roof, upstream and downstream spandrels and side walls.

[0043] Specifically, the drilling location points refer to multiple location points determined at intervals of 80 to 120 m on the roof, upstream and downstream spandrels, and side walls of the tunnel to be reinforced.

[0044] In the embodiment of the present invention, the drilling position point and the displacement meter position point may be the same position point or different position points.

[0045] In the embodiment of the present invention, the hole depth corresponding to the installation of the displacement meter is 8 m, and the hole depth corresponding to the drilling acoustic wave and imaging test hole is 10 m.

[0046] In the embodiment of the present invention, the displacement meter and the drilling acoustic wave and imaging test hole can be used to carry out regular observation and testing of the tunnel to be reinforced to collect geological monitoring data.

[0047] In the embodiment of the present invention, a control site for 3D laser scanning of the tunnel can be pre-established, and a 3D laser scanner can be used to quickly obtain 3D point cloud data of the tunnel, and a high-precision, high-resolution real-scene replication visualization model of the underground engineering can be constructed through the Surface module in the point cloud library PCL.

[0048] In the embodiment of the present invention, six microseismic acceleration sensors can be arranged in advance with the vicinity of the tunnel face to be reinforced as the key monitoring area. Specifically, two sensors are installed on the left and right side walls of each section on three sections behind the excavation face of the tunnel to be reinforced (each section is 30m away).

[0049] In an embodiment of the present invention, multi-point displacement meters installed at different positions of the underground rock mass of the tunnel to be reinforced can monitor the displacement changes of the rock mass in real time, record the displacement data of each monitoring point, ensure the time synchronization and spatial consistency of the data, and obtain displacement data in the data format of: timestamp, displacement value (x, y, z).

[0050] In the embodiment of the present invention, each displacement meter can collect a set of displacement data, and the displacement data collected by multiple displacement meters can be used to obtain a displacement data set.

[0051] In an embodiment of the present invention, through borehole observation, the loosening range of the surrounding rock can be determined, the thickness and spatial distribution of the surrounding rock loosening circle can be obtained, and the surrounding rock loosening circle data can be formed. The data format of the surrounding rock loosening circle data is: borehole position, loosening circle thickness, and depth range.

[0052] In the embodiment of the present invention, a set of surrounding rock loosening zone data can be collected based on each borehole, and the surrounding rock loosening zone data obtained by observing multiple boreholes can obtain a surrounding rock loosening zone data set.

[0053] In the embodiment of the present invention, a 3D laser scanner is used to scan the underground rock mass of the tunnel to be reinforced, so that high-precision 3D point cloud data can be obtained, and the point cloud data is preprocessed to remove noise and abnormal points to ensure the accuracy of the data. A 3D laser scanning data set can be obtained, and the data format of the 3D laser scanning data set is: point cloud coordinates (x, y, z), reflection intensity.

[0054] In an embodiment of the present invention, microseismic monitoring sensors are arranged inside the underground rock mass of the tunnel to be reinforced, so that microseismic events can be recorded in real time, including information such as the time, position, frequency and energy of the microseismic events, to form a microseismic monitoring data set. The data format of the microseismic monitoring data is: timestamp, event position (x, y, z), frequency, and energy.

[0055] In an optional implementation, based on the above embodiment, the tunnel bolt support fine intervention method based on multi-source monitoring information further includes the following steps:

[0056] S1015, based on the multiple displacement meter position points, the multiple drilling position points, the position points where the three-dimensional laser scanner is located, and the position points where the microseismic monitoring sensor is located, aligning the displacement data, the surrounding rock loosening zone data, the three-dimensional laser scanning data, and the microseismic monitoring data so that the spatial coordinates of the various data are consistent;

[0057] S1016, based on the weighted average interpolation algorithm, the aligned displacement data, surrounding rock loosening zone data, 3D laser scanning data and microseismic monitoring data are fused to obtain a multi-dimensional geological monitoring data set.

[0058] In the embodiment of the present invention, the location points where each data acquisition device is installed can be used as known location points. Based on these known location points, the collected displacement data, surrounding rock loosening zone data, three-dimensional laser scanning data and microseismic monitoring data can be aligned. Specifically, the alignment operation can include one or more of the following operations: translation, rotation and scaling. In the embodiment of the present invention, the spatial coordinates of each aligned data are consistent, and the damaged area of ​​the tunnel to be reinforced can be comprehensively analyzed based on the aligned geological monitoring data.

[0059] In the embodiment of the present invention, time alignment may also be performed based on the time stamp of each data included in each data set.

[0060] In an embodiment of the present invention, the interpolation algorithm based on weighted average can assign different weights according to the importance or reliability of each data set (displacement data set, surrounding rock loosening zone data set, three-dimensional laser scanning data set and microseismic monitoring data set), and then calculate a comprehensive interpolation result.

[0061] In the embodiment of the present invention, the weight of each data set can be determined in advance according to the reliability, accuracy or importance of each data set. For example, if the microseismic monitoring data is considered to be the most reliable, it can be given a higher weight.

[0062] In an embodiment of the present invention, the multi-dimensional geological monitoring data set includes: geological monitoring data of multiple dimensions, specifically including: displacement data after alignment and fusion, surrounding rock loosening zone data after alignment and fusion, three-dimensional laser scanning data after alignment and fusion, and microseismic monitoring data after alignment and fusion.

[0063] In an embodiment of the present invention, in the multi-dimensional geological monitoring data set obtained by alignment and fusion, the data set of each dimension maintains spatial and temporal consistency with other data, which is convenient for subsequent analysis. Moreover, the data set of each dimension is fused with the data sets of other dimensions to obtain a more reasonable and accurate data set.

[0064] In an optional implementation, based on the above embodiment, in step S102, the displacement gradient may be determined based on the following steps:

[0065] The displacement gradient reflecting the severity of rock mass deformation is calculated using the following formula: G :

[0066] ;

[0067] in, u represents the displacement value in the aligned and fused displacement data included in the multi-dimensional geological monitoring data set, and the displacement value is expressed as ( x, y, z ).

[0068] In the embodiment of the present invention, the Sobel gradient operator is specifically used to calculate the displacement gradient reflecting the severity of rock mass deformation.

[0069] In the embodiment of the present invention, the displacement data after alignment and fusion included in the multi-dimensional geological monitoring data set is continuous data. Each displacement value is expressed as ( x, y, z ) form.

[0070] In an optional implementation, based on the above embodiment, in step S102, the shallow damage factor may be determined based on the following steps:

[0071] The differences in the degree of fracture at different hole depths are determined based on the aligned and fused surrounding rock loosening zone data included in the multi-dimensional geological monitoring data set;

[0072] According to the difference in the degree of rupture at different hole depths, the average wave velocity v of the loose zone P and the average wave velocity outside the loose circle v P0 , calculate the shallow damage factor α , the formula for determining the shallow damage factor value is:

[0073] ;

[0074] Among them, v P0 is the original rock (outside the loosening zone) wave velocity, which represents the speed of elastic wave propagation in the undisturbed original surrounding rock, v P It is the rock wave velocity in the shallow damage zone (within the loosening zone), which represents the speed of elastic wave propagation in shallow damage.

[0075] By analyzing the propagation characteristics of sound waves in the rock mass (usually the wave velocity), the rock mass zoning cracking and mechanical properties are calculated. Compared with physical and mechanical testing, this method has the advantages of low cost, no damage to the object being tested, simple operation, and rapid testing.

[0076] In an optional implementation, based on the above embodiment, in step S102, the point cloud data features may be determined based on the following steps:

[0077] According to the aligned and fused 3D laser scanning data included in the multi-dimensional geological monitoring data set, based on the iterative nearest point high-density point cloud spatial difference algorithm, the deformation location and value of the underground engineering are obtained through the iteration of two-phase point cloud data of the underground engineering excavation surface.

[0078] In an optional implementation, based on the above embodiment, in step S102, the deep damage factor may be determined based on the following steps:

[0079] Based on the aligned and fused microseismic monitoring data included in the multi-dimensional geological monitoring data set, the spatiotemporal distribution characteristics of microseismic events are determined; the microseismic release energy is obtained ΔU Energy released by rock mass U ;

[0080] Release energy through micro-vibrations ΔU Energy released by rock mass U Compare and calculate the deep damage factor of underground engineering rock mass D :

[0081] .

[0082] As a three-dimensional "body" monitoring method with dynamic time and space, microseismic monitoring technology can timely capture micro-fractures inside the rock mass, and can monitor and analyze in real time the entire process of surrounding rock crack initiation, development, expansion, and penetration until macroscopic deformation occurs, thereby realizing three-dimensional visualization of the damaged area of ​​underground cavern excavation and prediction and early warning of surrounding rock deformation.

[0083] Since the deformation of the surrounding rock of underground engineering tunnels is an instability problem in the process of rock mass rupture, it goes through a process from continuous deformation to discontinuous destruction. If the conventional surrounding rock deformation monitoring method and the microseismic monitoring method for monitoring internal rock damage can be organically combined, the whole process of surrounding rock rupture, deformation and instability of underground engineering can be monitored from multiple angles and levels in the form of "point", "line" and "body", which will have important guiding significance for the evaluation of the excavation damage zone and the optimization of the support range of deep underground engineering.

[0084] In the embodiment of the present invention, in step S103, the damage area can be represented as a continuous three-dimensional field using an implicit function method (such as a level set method or an implicit function method) according to the displacement gradient, the shallow damage factor, the point cloud data feature and the deep damage factor. The zero level set of the implicit function represents the boundary of the damage area, and the three-dimensional damage area data is generated.

[0085] In the embodiment of the present invention, the three-dimensional damage area data generated by the implicit function model can be converted into a software format suitable for visualization, and damage areas of different degrees can be distinguished by different colors or transparencies.

[0086] For example, Figure 2 As shown, it shows a schematic diagram of three-dimensional damage zone data obtained in an embodiment of the present invention, wherein part a and part b respectively represent the distribution of damage zones corresponding to different sections in the tunnel to be reinforced.

[0087] In the embodiment of the present invention, the distribution of damage factors can be analyzed based on the three-dimensional damage zone data generated by the implicit function model to determine the range of the surrounding rock disturbance zone (EDZ).

[0088] Then, the support intervention plan is carefully determined according to the surrounding rock conditions of the tunnel to be reinforced to ensure that the installation of anchor rods covers the entire EDZ range of the focus area and give full play to the support effectiveness of the support measures.

[0089] Specifically, in the embodiment of the present invention, in the support intervention scheme, the support density of each of the different cross-sectional units can be determined in the axial direction, and the support length of each cross-sectional unit can be determined in the radial direction.

[0090] In the embodiment of the present invention, the minimum length of the anchor bolt can be calculated based on the difference between the depth of the surrounding rock disturbance zone and the deformation value of the underground engineering determined by three-dimensional laser scanning, and the length can be appropriately increased according to the engineering requirements such as the initial ground stress and the surrounding rock mechanical parameters to ensure that the anchor bolt length is greater than the depth of the surrounding rock disturbance zone. Figure 3 As shown, it shows a schematic diagram of the bolt support intervention scheme obtained in an embodiment of the present invention, which shows the bolt support intervention scheme finally determined according to the comprehensive analysis of various geological monitoring data, wherein the damaged zone is the EDZ range obtained by the final analysis, the excavation contour line is the excavation contour of the tunnel to be reinforced, the microseismic event is the microseismic monitoring data recorded by the microseismic monitoring sensor, and the multi-point displacement meter is the displacement data collected according to multiple displacement meters ( x, y, z ) is a comprehensive representation of the borehole acoustic wave and imaging test hole drilling observations, and the acoustic wave test is obtained by testing the borehole acoustic wave and imaging test hole.

[0091] In an embodiment of the present invention, geological monitoring data can also be continuously collected based on a variety of data acquisition devices to evaluate the stability and safety of the support scheme. When the rock mass of the excavated tunnel is damaged and deformed, the three-dimensional damage zone data generated by the implicit function model is adjusted and updated based on the actual damage and deformation conditions. The support scheme is further adjusted based on the adjusted and updated three-dimensional damage zone data to obtain a support scheme that better conforms to the actual situation.

[0092] In the embodiment of the present invention, after the anchor support intervention plan is obtained, the plan can be adjusted based on the on-site design requirements during the construction period to obtain an optimized plan for anchor fine support during the tunnel construction period.

[0093] Based on the same inventive concept, an embodiment of the present invention further provides a tunnel bolt support fine intervention device based on multi-source monitoring information. Specifically, the device includes:

[0094] A data acquisition module is used to acquire the surrounding rock mechanical parameters and geological monitoring data of the tunnel to be reinforced, wherein the geological monitoring data includes displacement data, surrounding rock loosening zone data, three-dimensional laser scanning data and microseismic monitoring data;

[0095] A data processing module, used to determine a displacement gradient according to the displacement data, determine a shallow damage factor according to the surrounding rock loosening zone data, determine point cloud data features according to the three-dimensional laser scanning data, and determine a deep damage factor according to the microseismic monitoring data;

[0096] A modeling module, used for performing three-dimensional damage zone geological modeling based on an implicit function model according to the displacement gradient, the shallow damage factor, the point cloud data characteristics and the deep damage factor;

[0097] The analysis module is used to analyze the distribution of damage factors and determine the range of the surrounding rock disturbance zone based on the three-dimensional damage zone data generated by the implicit function model;

[0098] The support intervention scheme determination module is used to determine the anchor support intervention scheme according to the surrounding rock mechanical parameters of the tunnel to be reinforced and the range of the surrounding rock disturbance zone, and the anchor support intervention scheme includes: the installation position of the anchor and the length of the anchor.

[0099] Optionally, the data acquisition module is specifically used to:

[0100] Acquire displacement data collected by displacement meters respectively arranged at a plurality of displacement meter position points of the tunnel to be reinforced, wherein the displacement data includes: a timestamp and a displacement value;

[0101] Acquire surrounding rock loosening zone data obtained by drilling observation distributed at multiple drilling positions of the tunnel to be reinforced, wherein the surrounding rock loosening zone data includes: drilling position points, loosening zone thickness and depth range;

[0102] Acquire three-dimensional laser scanning data obtained by scanning the tunnel to be reinforced using a three-dimensional laser scanner, wherein the three-dimensional laser scanning data includes: point cloud coordinates and reflection intensity;

[0103] The microseismic monitoring data recorded by the microseismic monitoring sensors arranged inside the underground rock mass of the tunnel to be reinforced are obtained, wherein the microseismic monitoring data include: timestamp, microseismic event location, frequency and energy.

[0104] Optionally, the device further comprises:

[0105] An alignment module, for aligning the displacement data, surrounding rock loosening zone data, three-dimensional laser scanning data and microseismic monitoring data based on the multiple displacement meter position points, multiple drilling position points, the position points where the three-dimensional laser scanner is located and the position points where the microseismic monitoring sensor is located, so as to make the spatial coordinates of each data consistent;

[0106] The fusion module is used to fuse the aligned displacement data, surrounding rock loosening zone data, 3D laser scanning data and microseismic monitoring data based on the weighted average interpolation algorithm to obtain a multi-dimensional geological monitoring data set.

[0107] Optionally, the data processing module is specifically used to:

[0108] The displacement gradient reflecting the severity of rock mass deformation is calculated using the following formula: G :

[0109] ;

[0110] in, u represents the displacement value in the aligned and fused displacement data included in the multi-dimensional geological monitoring data set, and the displacement value is expressed as ( x, y, z ).

[0111] Optionally, the data processing module is specifically used to:

[0112] The differences in the degree of fracture at different hole depths are determined based on the aligned and fused surrounding rock loosening zone data included in the multi-dimensional geological monitoring data set;

[0113] According to the difference in the degree of rupture at different hole depths, the average wave velocity v of the loose zone P and the average wave velocity outside the loose circle v P0 , calculate the shallow damage factor α , the formula for determining the shallow damage factor value is:

[0114] ;

[0115] Among them, v P0 is the average wave velocity outside the loosening zone, representing the original rock wave velocity, representing the speed of elastic wave propagation in the undisturbed original surrounding rock, v P It is the average wave velocity of the loosening zone, which represents the wave velocity of the rock mass in the shallow damage zone and the speed of elastic wave propagation in the shallow damage.

[0116] Optionally, the data processing module is specifically used to:

[0117] According to the aligned and fused 3D laser scanning data included in the multi-dimensional geological monitoring data set, based on the iterative nearest point high-density point cloud spatial difference algorithm, the deformation location and value of the underground engineering are obtained through the iteration of two-phase point cloud data of the underground engineering excavation surface.

[0118] Optionally, the data processing module is specifically used to:

[0119] Based on the aligned and fused microseismic monitoring data included in the multi-dimensional geological monitoring data set, the spatiotemporal distribution characteristics of microseismic events are determined, and the microseismic release energy is obtained. ΔU Energy released by rock mass U ;

[0120] Release energy through micro-vibrations ΔU Energy released by rock mass U Compare and calculate the deep damage factor of underground engineering rock mass D :

[0121] .

[0122] Based on the same inventive concept, an embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and run on the processor, wherein when the processor executes, the steps in the method for fine intervention of tunnel anchor support based on multi-source monitoring information as described in any of the above embodiments are implemented.

[0123] Based on the same inventive concept, an embodiment of the present invention also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the tunnel anchor support fine intervention method based on multi-source monitoring information described in any of the above embodiments are implemented.

[0124] Based on the same inventive concept, an embodiment of the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the tunnel anchor support fine intervention method based on multi-source monitoring information described in any of the above embodiments.

[0125] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0126] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0127] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0128] The above is a detailed introduction to the tunnel anchor support fine intervention method based on multi-source monitoring information provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A fine intervention method for tunnel bolt support based on multi-source monitoring information, characterized in that: The method comprises: Obtaining the surrounding rock mechanical parameters and geological monitoring data of the tunnel to be reinforced, wherein the geological monitoring data includes displacement data, surrounding rock loosening zone data, three-dimensional laser scanning data and microseismic monitoring data; Determine the displacement gradient according to the displacement data, determine the shallow damage factor according to the surrounding rock loosening zone data, determine the point cloud data features according to the three-dimensional laser scanning data, and determine the deep damage factor according to the microseismic monitoring data; According to the displacement gradient, the shallow damage factor, the point cloud data characteristics and the deep damage factor, three-dimensional damage zone geological modeling is performed based on an implicit function model; According to the three-dimensional damage zone data generated by the implicit function model, the distribution of damage factors is analyzed to determine the scope of the surrounding rock disturbance zone; Determine an anchor support intervention scheme according to the surrounding rock mechanical parameters of the tunnel to be reinforced and the range of the surrounding rock disturbance zone, wherein the anchor support intervention scheme includes: the installation position of the anchor and the length of the anchor; Obtain the surrounding rock mechanical parameters and geological monitoring data of the tunnel to be reinforced, including: Acquire displacement data collected by displacement meters respectively arranged at a plurality of displacement meter position points of the tunnel to be reinforced, wherein the displacement data includes: a timestamp and a displacement value; Acquire surrounding rock loosening zone data obtained by drilling observation distributed at multiple drilling positions of the tunnel to be reinforced, wherein the surrounding rock loosening zone data includes: drilling position points, loosening zone thickness and depth range; Acquire three-dimensional laser scanning data obtained by scanning the tunnel to be reinforced using a three-dimensional laser scanner, wherein the three-dimensional laser scanning data includes: point cloud coordinates and reflection intensity; Acquire microseismic monitoring data recorded by microseismic monitoring sensors arranged inside the underground rock mass of the tunnel to be reinforced, wherein the microseismic monitoring data includes: timestamp, microseismic event location, frequency and energy; The method further comprises: Based on the multiple displacement meter position points, the multiple drilling position points, the position points where the three-dimensional laser scanner is located, and the position points where the microseismic monitoring sensor is located, the displacement data, the surrounding rock loosening zone data, the three-dimensional laser scanning data, and the microseismic monitoring data are aligned to make the spatial coordinates of the various data consistent; Based on the weighted average interpolation algorithm, the aligned displacement data, surrounding rock loosening zone data, 3D laser scanning data and microseismic monitoring data are fused to obtain a multi-dimensional geological monitoring data set. The shallow damage factor is determined based on the surrounding rock loosening zone data, including: The differences in the degree of fracture at different hole depths are determined based on the aligned and fused surrounding rock loosening zone data included in the multi-dimensional geological monitoring data set; According to the difference in the degree of rupture at different hole depths, the average wave velocity v of the loose zone P and the average wave velocity outside the loose circle v P0 , calculate the shallow damage factor α, and the formula to determine the shallow damage factor value is: Among them, v P0 is the average wave velocity outside the loosening zone, representing the original rock wave velocity, representing the speed of elastic wave propagation in the undisturbed original surrounding rock, v P It is the average wave velocity of the loosening zone, which represents the wave velocity of the rock mass in the shallow damage zone and the speed of elastic wave propagation in the shallow damage.

2. The method for fine intervention of tunnel bolt support based on multi-source monitoring information according to claim 1 is characterized in that: Determining a displacement gradient according to the displacement data includes: The displacement gradient G, which reflects the severity of rock mass deformation, is calculated using the following formula: ； Wherein, u represents the displacement value in the aligned and fused displacement data included in the multi-dimensional geological monitoring data set, and the displacement value is expressed as (x, y, z).

3. The tunnel bolt support fine intervention method based on multi-source monitoring information according to claim 1 is characterized in that: Determining point cloud data features according to the three-dimensional laser scanning data includes: According to the aligned and fused 3D laser scanning data included in the multi-dimensional geological monitoring data set, based on the iterative nearest point high-density point cloud spatial difference algorithm, the deformation location and value of the underground engineering are obtained through the iteration of two-phase point cloud data of the underground engineering excavation surface.

4. The method for fine intervention of tunnel bolt support based on multi-source monitoring information according to claim 1 is characterized in that: Determining deep damage factors based on the microseismic monitoring data includes: According to the aligned and fused microseismic monitoring data included in the multi-dimensional geological monitoring data set, the spatiotemporal distribution characteristics of microseismic events are determined, and the microseismic released energy ΔU and the rock mass releasable energy U are obtained; By comparing the microseismic energy ΔU with the releasable energy U of the rock mass, the deep damage factor D of the underground engineering rock mass is calculated: 。 5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the tunnel bolt support fine intervention method based on multi-source monitoring information described in any one of claims 1-4 is implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for fine intervention of tunnel bolt support based on multi-source monitoring information as described in any one of claims 1 to 4 is implemented.

7. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the tunnel bolt support fine intervention method based on multi-source monitoring information described in any one of claims 1-4 are implemented.

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