Anchored net-based strategy generation method and system

Abstract

This invention relates to the field of strategic planning technology, and discloses a strategy generation method and system based on anchor bolt mesh installation. The method includes: acquiring all anchor bolt positions and mesh sizes within the tunnel, and correcting the mesh sizes; digitally twinning the anchor bolt positions in a three-dimensional coordinate system to construct a multi-layered mesh digital twin model; and performing multi-objective strategy optimization on the multi-layered mesh digital twin model to generate a mesh installation strategy on the anchor bolts. This invention can automatically generate mesh installation schemes with high coverage, low loss, and strong stability, reducing manual intervention, material waste and rework rates, effectively improving construction quality and automation levels, and has significant engineering application value and promising prospects for wider application.

Description

Technical Field

[0001] This invention relates to the field of strategy planning technology, specifically to a strategy generation method and system based on anchor bolts with mesh installed on them. Background Technology

[0002] In geotechnical engineering fields such as tunnels, slopes, and underground mines, anchor bolts with reinforced mesh are a common method in support structures. Their function is to connect the anchor bolts through the mesh, forming a continuous covering structure and improving the overall stability of the surrounding rock. However, current mesh installation still relies heavily on manual experience for positioning, cutting, and installation, lacking systematic and automated auxiliary design methods. On-site construction workers typically adjust the mesh visually, resulting in low installation accuracy and a low alignment rate between the anchor bolts and mesh openings. This often necessitates forcibly straightening the mesh edges or additional binding work, increasing both the workload and the rate of misinstallation and material waste.

[0003] Furthermore, projects often encounter situations such as uneven anchor bolt distribution and complex spatial arrangements. Conventional two-dimensional drawings or manual measurement methods are insufficient to reflect the actual three-dimensional spatial relationships, resulting in the mesh coverage area not being able to completely match the target anchor bolts, causing problems such as local suspension and severe overlap and redundancy. This inefficient and inaccurate mesh installation process not only affects the stability and safety of the support structure but also leads to significant material waste and construction time costs. In complex environments, if the mesh installation strategy is not adjusted in a timely manner, it may also affect the continuity of subsequent shotcrete, sealing, and other processes, limiting the improvement of construction progress and automation levels. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a strategy generation method based on anchor bolt mesh mounting, comprising:

[0006] Obtain the locations of all anchor bolts and the dimensions of the mesh within the tunnel, and then correct the dimensions of the mesh.

[0007] The anchor bolt positions in the three-dimensional coordinate system are digitally twinned to construct a digital twin model of the multi-layered mesh.

[0008] Multi-objective strategy optimization is performed on the digital twin model of the multi-layer mesh to generate a mesh installation strategy on the anchor bolts;

[0009] The multi-layered digital twin model includes n nodes and m layers, each layer containing n mesh panels, and the number of mesh panels in the m-th layer is less than or equal to n; by adjusting the position of the mesh panels in each layer, the mesh panels can cover all target areas after the m layers are stacked.

[0010] As a preferred embodiment of the strategy generation method based on anchor bolts with mesh as described in this invention, the anchor bolt position includes the position of the mesh-hanging part of the anchor bolt and the hole position where the anchor bolt is anchored into the rock mass;

[0011] The mesh size includes the size of the mesh openings and wires, as well as the geometric layout on the mesh.

[0012] As a preferred embodiment of the strategy generation method based on anchor bolt mesh according to the present invention, the size correction includes: analyzing the mesh specifications, removing the boundary areas of incomplete mesh holes, so that the boundary of the mesh is formed by the outer edge of the outermost complete mesh hole;

[0013] When the size correction is completed, the size of the mesh is updated.

[0014] As a preferred embodiment of the strategy generation method based on anchor bolt mesh as described in this invention, the specific process of the digital twin is as follows:

[0015] Using the anchor bolt's hole position into the rock mass as a reference, establish the adjacent relationship between each anchor bolt;

[0016] Based on the adjacency relationship, three adjacent nodes are constructed into a triangle to obtain all the triangles;

[0017] If the two triangular planes are not in the same plane, then the attributes of the two adjacent triangular planes are assigned; if the two triangular planes are in the same plane, then they are directly merged into the same plane.

[0018] The attribute is assigned as follows: Let the common edge of node i and node j be... Corresponding to two triangular faces and In the simulation of meshing in a multi-layered digital twin model, if the mesh is blocked by a common edge... The truncated portion is then passed through and The relative positional relationship of the cut mesh will be reflected in... and Within the triangular face it resides in, and in the generation and At that time, based on the vectors of the two planes in three-dimensional space Using the Bayesian algorithm, the loss rate of the mesh during installation is determined. ; express The normal vector, express The normal vector.

[0019] As a preferred embodiment of the strategy generation method based on anchor bolt mesh described in this invention, the digital twin model of the multi-layer mesh further includes constraints on the mesh simulation process: in each layer, n mesh panels are added on the basis of the previous layer; and all n nodes are directly or indirectly connected to the newly added mesh panels at least once.

[0020] Direct connection refers to a mesh coverage area that includes nodes; indirect connection refers to the area coverage of a mesh being connected to another mesh through a transmission relationship, thus connecting the mesh directly connected to the nodes.

[0021] During the network simulation, the public edges that are assigned attributes are... Above, simulate the loss of the mesh: ;

[0022] ;

[0023] in, Indicates that the net sheet is in Above, the area loss each time it is truncated; Indicates that the net sheet is in Above, the numerical value of length; Indicates that the net sheet is in The work loss each time the circuit is interrupted; Units Below, the power loss per unit angle; It is a linear function that represents the angle between two surfaces; Indicates standard area;

[0024] The netting simulation includes randomly arranging the positions of the midpoints of the netting and the angle of the netting according to a preset step size; the constraints during the arrangement are: the netting covers all the triangular faces, and the number of netting does not exceed the minimum number of netting in the random arrangement result + the total area of ​​the triangular faces × Ω.

[0025] Where Ω represents the preset conversion coefficient.

[0026] As a preferred embodiment of the strategy generation method based on anchor bolt mesh according to the present invention, the multi-objective strategy optimization includes: obtaining the final solution through solving two rounds of objective optimization strategies; using the first round of objective optimization strategy, performing Pareto optimization to obtain a set of solutions; arranging the elements in the set in ascending order of the number of mesh panels; analyzing the increment of the total work done for each additional mesh panel; if the increment of the total work done after the p-th mesh panel is added is greater than a preset value, then only elements in the set with fewer than p mesh panels are retained, completing the first round of solution selection; using the solution selection results of the first round of solution selection, performing the second round of objective optimization strategy;

[0027] The first round of target optimization strategy includes, for each scheme, calculating the total work done and the number of mesh panels; where, the total work done = the number of mesh panels in... The work loss when the cable is cut each time + the work loss when the cable is aligned with the anchor rod.

[0028] The work loss when the mesh and anchor are aligned includes the following: for each mesh panel, when the mesh panel is directly connected to anchor a, if anchor a is entirely located at the mesh opening, the measured work loss is 0; if anchor a is on mesh panel b, the measured work loss is... When the mesh is indirectly connected to anchor bolt a, the metering power loss is 0.

[0029] in, This indicates the work required to insert anchor rod a into the mesh. Indicates the work loss per unit distance; R represents the distance between the center of the network cable b and the axis of the anchor rod a, and R represents the radius of the anchor rod.

[0030] The strategy is optimized with the goal of minimizing the number of meshes used and minimizing power loss.

[0031] As a preferred embodiment of the strategy generation method based on anchor bolt mesh according to the present invention, the second round of target optimization strategy includes performing a layer-by-layer stability analysis on the digital twin model of the multi-layer mesh to obtain the optimal stability scheme.

[0032] The stability of each layer is equal to the sum of the core stability of the current layer and all previous layers; for each mesh y, according to the relative position of the overlapping part of mesh y with other meshes and the relative position of mesh y with anchor bolt, the stability of all meshes in each layer is assigned, and the core stability is obtained by summing the stability assignment results of all meshes in each layer.

[0033] The stability of each mesh is the sum of the values ​​assigned to the two stability factors.

[0034] Calculate the uniformity of the overlapping area distribution around the center of each mesh; assign feature values ​​based on the uniformity to obtain the first element of mesh stability; and assign stability values ​​by inputting the result of the feature assignment through a preset mapping function 1.

[0035] When anchor bolts are present in the mesh, the supporting performance of each anchor bolt in the mesh is analyzed, and feature values ​​are assigned to obtain the second element of mesh stability; through the preset mapping function 2, the result of the feature assignment is input to perform stability assignment.

[0036] On the other hand, a strategy generation system based on anchor bolt-mounted mesh using the method described in this invention, wherein:

[0037] The data acquisition unit obtains the locations of all anchor bolts and the dimensions of the mesh within the tunnel, and corrects the dimensions of the mesh.

[0038] The simulation unit digitally twins the anchor bolt positions in the three-dimensional coordinate system to construct a digital twin model of the multi-layered hanging net.

[0039] The optimization unit performs multi-objective strategy optimization on the digital twin model of the multi-layered netting to generate the netting strategy on the anchor bolts.

[0040] A computer device includes: a memory and a processor; the memory stores a computer program, wherein: when the processor executes the computer program, it implements the steps of the method described in any one of the present invention.

[0041] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of the present invention.

[0042] The beneficial effects of this invention are as follows: The strategy generation method for installing mesh on anchor bolts provided by this invention achieves accurate modeling and simulation of the mesh installation process by constructing a digital twin model of multi-layer mesh installation and combining the spatial distribution of anchor bolts and the geometric characteristics of the mesh panels. A multi-objective optimization strategy is adopted to balance the number of mesh panels and the work loss during installation, significantly improving installation efficiency and resource utilization. Simultaneously, structural stability analysis is introduced to ensure the reliability and practicality of the final solution under complex spatial structures. Compared with traditional experience-based construction methods, this invention can automatically generate mesh installation schemes with high coverage, low loss, and strong stability, reducing manual intervention, material waste, and rework rates, effectively improving construction quality and automation levels, and has significant engineering application value and promising prospects for promotion. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 The first embodiment of the present invention provides an overall flowchart of a strategy generation method based on anchor bolt mesh. Detailed Implementation

[0045] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0046] Example 1, referring to Figure 1 As an embodiment of the present invention, a strategy generation method based on anchor bolt mesh is provided, comprising:

[0047] S1: Obtain the location of all anchor bolts and the size of the mesh within the tunnel, and correct the size of the mesh.

[0048] Furthermore, the anchor bolt location includes the position of the anchor bolt's mesh attachment portion and the anchor bolt's hole position into the rock mass. The position of the anchor bolt's mesh attachment portion represents the exposed end of the anchor bolt on the rock surface used to fix the mesh, and is a key anchor point that needs to be accurately aligned during mesh deployment. During mesh installation simulation, this position is used to determine whether the mesh openings can accurately cover the anchor bolt's mesh attachment point and to decide whether to rotate, move, or cut the mesh. Its alignment accuracy directly affects the amount of work involved in straightening and binding the mesh during construction, and is one of the core factors in controlling manual intervention and work loss. The anchor bolt's hole position into the rock mass is the endpoint where the anchor bolt is anchored inside the rock mass, and is fundamental data reflecting the actual spatial distribution of the anchor bolts and their contact relationship with the rock mass. In this invention, this point serves as a reference point for digital twin modeling, used to construct the adjacent topological relationships between anchor bolts, and based on this, to generate a triangular mesh, realizing the restoration of the support surface and the construction of the mesh coverage surface. It ensures the spatial realism of the mesh installation model and the accuracy of stability analysis. The mesh size includes the size of the mesh openings and wires, as well as the geometric layout on the mesh.

[0049] The mesh specifications are analyzed, and the boundary areas of incomplete mesh holes are removed so that the boundary of the mesh is formed by the outer edge of the outermost complete mesh hole; when the size correction is completed, the mesh size is updated.

[0050] It's important to note that this dimensional correction step is designed to address the positioning errors, connection difficulties, and insufficient stability caused by incomplete mesh openings at the edges of the mesh during actual construction. In standard industrial production, mesh sheets are often cut to uniform dimensions. However, due to the need for alignment with anchor bolts during installation, incomplete mesh openings at the edges cannot be effectively connected. This can lead to problems such as anchor bolts being difficult to insert accurately into incomplete mesh openings, requiring additional bending or manual fixing. By analyzing the mesh sheet specifications and eliminating incomplete mesh opening areas at the edges, the boundary of the mesh sheet can be formed by the outer edge of complete mesh openings, creating a regular and controllable geometric boundary.

[0051] S2: Digital twin the anchor bolt positions in the three-dimensional coordinate system to construct a digital twin model of the multi-layered hanging net.

[0052] Furthermore, the specific process of digital twin creation is as follows:

[0053] Using the anchor bolt's hole position into the rock mass as a reference, the adjacency relationship between each anchor bolt is established. Using the anchor bolt's hole position into the rock mass as a reference avoids coordinate deviations caused by varying exposed lengths of the anchor bolts, thus more accurately reflecting the spatial distribution of the anchor bolts within the structure.

[0054] Based on the adjacency relationship, three adjacent nodes are constructed into a triangular face, resulting in all triangular faces. By constructing the adjacency relationship and forming triangular faces from three adjacent points, a continuous support surface model is created, providing a foundation for the mesh laying.

[0055] If the two triangular planes are not in the same plane, then the attributes of the two adjacent triangular planes are assigned; if the two triangular planes are in the same plane, then they are directly merged into the same plane.

[0056] The attribute is assigned as follows: Let the common edge of node i and node j be... Corresponding to two triangular faces and In the simulation of meshing in a multi-layered digital twin model, if the mesh is blocked by a common edge... The truncated portion is then passed through and The relative positional relationship of the cut mesh will be reflected in... and Within the triangular face it resides in, and in the generation and At that time, based on the vectors of the two planes in three-dimensional space Using the Bayesian algorithm, the loss rate of the mesh during installation is determined. ; express The normal vector, express The normal vector.

[0057] Furthermore, the multi-layered digital twin model includes n nodes and m layers, each layer containing n mesh panels, with the number of mesh panels in the m-th layer being less than or equal to n. By adjusting the position of the mesh panels in each layer, the mesh panels can cover the entire target area after the m layers are stacked. Each mesh panel has a cost attribute: the cost of a mesh opening is 0, and the cost of a mesh cable is 1.

[0058] The meshing simulation process is constrained as follows: in each layer, n mesh panels are added based on the previous layer; and each of the n nodes is directly or indirectly connected to the newly added mesh panel at least once. By constraining the meshing simulation process, the calculation process can be simplified. Obviously unreasonable schemes can be directly filtered out.

[0059] Direct connection refers to a mesh coverage area that includes nodes; indirect connection refers to the area coverage of a mesh being connected to another mesh through a transmission relationship, thus connecting the mesh directly connected to the nodes.

[0060] By requiring that each newly added mesh layer ensures that all anchor nodes are directly or indirectly covered at least once, the system ensures that there are no blind spots or suspended areas in the final multi-layer structure, thus strengthening the integrity and continuity of the support. This is one of the key engineering constraints for ensuring the continuous closure of the support structure. Adding constraint checks during the meshing simulation (such as "incomplete node coverage," "isolated mesh," and "local blank areas") allows for the rapid identification and removal of mesh combinations that clearly do not meet engineering requirements in the early stages. This reduces the search space in the Pareto optimization and stability analysis stages, significantly improving computational efficiency and solution quality. Finally, during strategy generation, meshing can be performed layer by layer based on the mesh arrangement. Allowing multi-layer mesh stacking solves the problem of insufficient single-layer coverage caused by irregular anchor distribution and severe rock surface undulations, ensuring complete meshing even in complex terrain. Simultaneously, by setting a constraint that the number of mesh layers in each layer does not exceed n, the model size is controlled, avoiding overfitting and excessive resource consumption.

[0061] During the network simulation, the public edges that are assigned attributes are... Above, simulate the loss of the mesh: ;

[0062] .

[0063] in, Indicates that the net sheet is in Above, the area loss at each truncation, in units of ; Indicates that the net sheet is in Above, the numerical value of length; is to convert a "length" with units into a quantity that only has numerical values ​​but no units. Indicates that the net sheet is in The above represents the work loss during each interruption; the unit is J. Units Below, the power loss per unit angle; the unit is J / rad; It is a linear function that represents the angle between two surfaces, with the unit being rad. Represents standard area, unit: This is used to standardize units. It closely integrates the loss of the mesh at the corners, the external force (work) required for adjustment, and the mesh covering process, ultimately forming a simulation framework that can "automatically identify high-loss layouts and automatically iterate low-loss layouts," possessing adaptive capabilities and construction realism.

[0064] The meshing simulation involves randomly arranging the positions of the mesh midpoints and the mesh placement angles according to a preset step size. The constraints during arrangement are: the meshes must cover all triangular faces, and the number of meshes must not exceed the minimum number of meshes in the random arrangement plus the total area of ​​the triangular faces multiplied by Ω. Here, Ω represents a preset conversion coefficient. This ensures complete mesh coverage (no missed meshes); avoids wasting computational resources with a large number of redundant meshes; and uses the conversion coefficient Ω to achieve a balance between flexibility and stability in adjusting the arrangement, providing a reasonably reasonable initial population for subsequent optimization.

[0065] S3: Perform multi-objective strategy optimization on the digital twin model of the multi-layered netting to generate the netting strategy on the anchor bolts.

[0066] It's important to understand that multi-objective strategy optimization involves solving two rounds of objective optimization strategies to obtain the final solution. Using the first round of objective optimization strategies, Pareto optimization is performed to obtain a set of solutions. The elements in the set are sorted in ascending order by the number of mesh panels. The increase in total work done with each additional mesh panel is analyzed. If, after adding the p-th mesh panel, the increase in total work is greater than a preset value, only elements with fewer than p mesh panels are retained, completing the first round of solution selection. The results of the first round of solution selection are then used for the second round of objective optimization. Using Pareto non-dominated sorting establishes an equilibrium between two conflicting objectives—minimizing the number of mesh panels and minimizing work loss—obtaining a set of non-dominated solutions (Pareto front solution set). This provides a global, non-single-biased initial candidate solution for subsequent optimization, effectively avoiding imbalances caused by single-objective bias (such as saving materials but making construction difficult, or being easy to construct but wasting materials). After sorting the Pareto solution set in ascending order of the number of meshes, the change in work increment brought about by each additional mesh is calculated to determine whether an inflection point of "decreasing input-output ratio" has occurred. For example, if the addition of the first few meshes leads to a significant decrease in work, it indicates that the optimization is effective; if, starting from the p-th mesh, the work increment tends to level off or even rises sharply, it indicates that the cost-effectiveness of adding meshes thereafter is low. By setting a preset threshold (such as work increment tolerance), the solution set can be truncated before this inflection point, retaining only the better subset, thus completing the efficient screening of the first round of solutions.

[0067] The first round of target optimization strategy includes, for each scheme, calculating the total work done and the number of mesh panels; where, the total work done = the number of mesh panels in... The power loss when the cable is cut off each time + the power loss when the cable is aligned with the anchor rod.

[0068] The work loss when the mesh and anchor are aligned includes the following: for each mesh panel, when the mesh panel is directly connected to anchor a, if anchor a is entirely located at the mesh opening, the measured work loss is 0; if anchor a is on mesh panel b, the measured work loss is... When the mesh is indirectly connected to anchor bolt a, the metered work loss is 0; this actually reflects the "cost attribute" of the mesh. If the cost is 0, then the loss is directly calculated as 0 (which can be understood as 0 multiplied by any number equals 0). If the cost is 1, it means that the number reflected by this cost is 1 multiplied by the work value.

[0069] in, This indicates the work required to insert anchor rod a into the mesh. Indicates the work loss per unit distance; R represents the distance between the center of the network cable b and the center of the anchor rod a, and R represents the radius of the anchor rod.

[0070] The strategy is optimized with the goal of minimizing the number of meshes used and minimizing power loss.

[0071] In other alternative embodiments, the "first round of scheme screening" can also analyze the "work increment" of the Pareto solution set one by one, so that the part where the ratio of work increment to the number of meshes is greater than a certain preset value is retained, and the other part is discarded, thereby completing the screening.

[0072] The second round of target optimization strategy involves performing a layer-by-layer stability analysis on the digital twin model of the multi-layer mesh to obtain the most stable solution. During the generation of the multi-layer mesh strategy, some mesh panels, due to their large coverage area or the regular structure of the area they are located in, can effectively cover the target triangular face at multiple locations, meaning there are multiple feasible layout schemes. These schemes may have the same number of mesh panels and similar work loss values ​​in the first round of Pareto optimization, but their specific spatial distribution differs, leading to significant differences in stability, disturbance resistance, and subsequent splicing difficulty. Therefore, simply relying on the first round of optimization results, which are quantity- and energy-consumption-oriented, cannot guarantee the structural stability and long-term reliability of the scheme in actual construction. To address this issue, a second round of target optimization strategy is designed, introducing a layer-by-layer structural analysis mechanism for the stability of the mesh scheme. This further filters out the optimal spatial layout among multiple equivalent solutions, achieving a decision leap from "usable" to "optimal." Specifically, by establishing stability characteristic indicators such as the overlap relationship between mesh panels and the connection method with anchor bolts, and conducting cumulative evaluations in multi-layer structures, the contribution of each layer of mesh panels to the overall structural stability can be quantified. Ultimately, a stability evaluation system guided by strong anti-disturbance capability, uniform support points, and reasonable overlap distribution is formed, used to select the optimal mesh panel combination scheme among multiple feasible locations.

[0073] The stability of each layer is equal to the sum of the core stability of the current layer and all previous layers. For each mesh y, the stability of all meshes in each layer is assigned according to the relative position of the overlapping part of mesh y with other meshes and the relative position of mesh y with the anchor. The core stability is obtained by summing the stability assignment results of all meshes in each layer.

[0074] The stability of each mesh is the sum of the values ​​assigned to the two stability factors.

[0075] Calculate the uniformity of the overlapping area distribution around the center of each mesh; assign feature values ​​based on the uniformity to obtain the first element of mesh stability; and assign stability values ​​by inputting the result of the feature assignment through a preset mapping function 1.

[0076] When anchor bolts are present in the mesh, the supporting performance of each anchor bolt in the mesh is analyzed, and feature values ​​are assigned to obtain the second element of mesh stability; through the preset mapping function 2, the result of the feature assignment is input to perform stability assignment.

[0077] In this embodiment, both "assigning feature values ​​based on the uniformity" and "analyzing the support performance of each anchor bolt in the mesh and assigning feature values" are implemented using a Bayesian algorithm. The evaluation assesses whether the anchor bolts are symmetrically distributed at key peripheral locations on the mesh to provide good boundary support and structural balance, preventing the mesh edges from curling, sagging, or twisting during installation. It also evaluates whether the overlapping areas between meshes have a symmetrical geometric feature on the periphery. This feature directly affects the quality of the mesh's constraint boundaries and the overall balance after installation. For example: if the overlapping area is concentrated around the outer edge of the mesh and symmetrically distributed or forms a ring structure → high assignment value (strong stability); if concentrated on one side or distributed in irregular patches → medium or low assignment value; if the overlapping area is concentrated in the center with no intersection at the edges → lowest assignment value (risk of overhanging or sagging). The overlapping region is modeled using polar coordinates (with the center of the mesh as the origin), and its distribution density and directional symmetry are statistically analyzed. A symmetry prior model is constructed, and the posterior probability that the current mesh overlapping distribution belongs to the ideal peripheral symmetry pattern is calculated. This posterior probability is then used as the feature value input to the mapping function 1.

[0078] Furthermore, in a wire mesh structure, the supporting performance of an anchor bolt does not depend on whether it is located in an overlapping area, but rather on its ability to stably constrain the "critical distribution areas" on the mesh, i.e., the distribution locations of various forces or overlapping stresses on the mesh. These areas are typically discrete, highly coupled small regions with certain spatial distribution characteristics. Therefore, the core objective is to analyze the relationship between the anchor bolt and discrete areas on the mesh (such as overlapping areas, edge areas, and stress-bearing areas), and to determine the supporting effect and quantify its value based on spatial center / density characteristics. Case 1: There is only one anchor bolt on the mesh:

[0079] If the anchor is located at the center of all discrete regions (such as overlapping areas), it indicates that it can constrain the entire area of ​​action and has good support performance → high value. If the anchor deviates from the center of the discrete region cluster, or even is close to the edge, it cannot provide effective in-plane stability → low value. Core indicator: The smaller the distance from the anchor to the centroid of the discrete region, the higher the stability. Case 2: Multiple anchors exist on the mesh: Analyze the location of all discrete regions to form a spatial distribution density map. If multiple anchors reasonably cover these high-density regions, that is, each dense point intersects with the support domain of one or more anchors → high value. If the anchors are concentrated and the discrete regions are extensive, or there are support blind spots (unconstrained areas) → medium to low value. Core indicators: anchor-density coverage, anchor distribution variance, maximum support blind spot radius, etc.

[0080] By establishing a stability characteristic index system, the spatial distribution of each layer of mesh is evaluated. This includes two main categories of factors: the overlap distribution characteristics between mesh layers, determining whether it is predominantly peripheral and symmetrically distributed to provide good boundary closure and force transmission continuity; and the support capacity of anchor bolts within the mesh, analyzing whether anchor bolts can effectively cover key stress or coupling areas on the mesh, including overlapping areas, edge areas, and other discrete target areas. Both features are modeled using Bayesian algorithms, calculating the posterior stability score of the mesh layer through polar coordinate direction density symmetry analysis of overlapping areas and geometric matching ability analysis of anchor bolts to discrete distribution areas. By accumulating and summing the stability of each layer, a global stability score for the complete meshing strategy is further formed. This ensures that among multiple structurally feasible solutions, the "optimal" combination is prioritized, thereby improving the edge support capacity, disturbance resistance, and structural coordination of the overall meshing system in actual construction. It effectively avoids construction problems such as local slackness, curling, and sagging caused by structural asymmetry or unbalanced coverage, achieving a value leap from "algorithm optimization" to "engineering practicality."

[0081] Mapping function 1 and mapping function 2 are preset scoring functions used to convert stability probability and support probability into stability values ​​for meshes. In this embodiment, both mapping functions are linear functions, and the values ​​are directly assigned based on the posterior probabilities calculated using the Bayesian algorithm.

[0082] In other alternative implementations, "assigning features based on the uniformity" and "analyzing the support performance of each anchor in the mesh and assigning features" can also be implemented using a pre-trained lightweight neural network.

[0083] Example 2: This example also provides a strategy generation system based on anchor bolts with mesh, which includes: a data acquisition unit, which acquires the positions of all anchor bolts and the size of the mesh in the tunnel, and corrects the size of the mesh.

[0084] The simulation unit digitally twins the anchor bolt positions in the three-dimensional coordinate system to construct a digital twin model of the multi-layered hanging net.

[0085] The optimization unit performs multi-objective strategy optimization on the digital twin model of the multi-layered netting to generate the netting strategy on the anchor bolts.

[0086] If the above functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0087] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0088] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0089] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0090] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for generating a strategy based on the anchoring of a net on a pole, characterized in that, The method comprises the following steps: Obtaining the positions of all anchor rods and the sizes of all meshes in the tunnel, and correcting the sizes of the meshes; Digitally cloning the positions of the anchor rods in a three-dimensional coordinate system to construct a digital twin model of the multi-layer hanging mesh; Optimizing the digital twin model of the multi-layer hanging mesh by using a multi-objective strategy to generate a hanging mesh strategy on the anchor rods; The digital twin model of the multi-layer hanging mesh comprises n nodes and m layers, each layer contains n meshes, and the number of meshes in the mth layer is less than or equal to n; by adjusting the positions of the meshes in each layer, the meshes can cover all target areas after the m layers are stacked; The specific process of the digital cloning is as follows: Taking the hole positions of the anchor rods in the rock mass as references, the adjacent relationship between each anchor rod is established; According to the adjacent relationship, three nodes adjacent to each other are constructed into a triangular face to obtain all triangular faces; If two triangular planes are not in the same plane, attribute assignment is performed between the two adjacent triangular planes; if the two triangular planes are in the same plane, they are directly merged into the same plane; The attribute assignment includes, if node i and node j have a common edge , corresponding two triangular faces , In the simulation of the hanging net in the digital twin model of the multi-layer hanging net, if the net sheet is truncated by the common edge , the truncated net sheet is reflected to the triangular faces where and are located through the relative position relationship between and , and when and are generated, the loss rate of the net sheet in the hanging net is determined according to the vector of the two planes in the three-dimensional space by using the Bayesian algorithm ; represents the normal vector of , represents the normal vector of ; The digital twin model of the multi-layer hanging mesh further comprises a constraint on the process of the hanging mesh simulation: in each layer, n meshes are added on the basis of the previous layer; and the n nodes are directly or indirectly connected to the newly added meshes at least once; Direct connection refers to that the mesh covers the node; indirect connection refers to that the mesh is connected to the mesh directly connected to the node through the area coverage of other meshes; In the course of the mesh simulation, the public edges that are endowed with attributes The mesh loss simulation is carried out on the upper: ; ； wherein, represents the area loss of the mesh at each time of being cut off; represents the length of the mesh at each time of being cut off; represents the work loss of the mesh at each time of being cut off; represents the work loss per unit length and per unit angle; is a linear function, representing the angle between the two faces; represents the standard area;​​​ The hanging mesh simulation comprises randomly arranging the positions of the mesh points and the mesh angles according to a preset step size; the constraint during the arrangement is that the mesh covers all triangular faces, and the number of meshes does not exceed the minimum number of meshes in the random arrangement result + the total area of the triangular faces × Ω; Wherein, Ω represents a preset conversion coefficient.

2. The anchor on the net-based policy generation method of claim 1, wherein: The anchor rod positions comprise the positions of the anchor rod hanging mesh parts and the hole positions of the anchor rods in the rock mass; The mesh sizes comprise the sizes of the mesh holes and mesh lines, and the geometric layout on the mesh.

3. The method for policy generation based on anchor on the web as claimed in claim 2, wherein: The size correction comprises analyzing the mesh specifications, removing the boundary area of the incomplete mesh holes, and making the boundary of the mesh consist of the outer edges of the outermost complete mesh holes; When the size correction is completed, the mesh sizes are updated.

4. The method for policy generation based on anchor on the web as claimed in claim 3, wherein: The multi-objective strategy optimization comprises obtaining the final scheme through two rounds of solution of the target optimization strategy; In the first round of target optimization strategy, Pareto optimization is performed to obtain a set of solutions, the elements in the set are arranged in ascending order of the number of meshes, the increment of the total work amount is analyzed when one mesh is added, and if the increment of the total work amount is greater than a preset value after the pth mesh is added, only the elements with the number of meshes less than p in the set are retained to complete the first round of scheme screening; The second round of target optimization strategy is performed by using the scheme screening result of the first round; The first round target optimization strategy comprises, for each scheme, calculating total work and mesh number; wherein total work = work loss of mesh when being cut off each time + work loss of relative position alignment of mesh wire and anchor rod. The first round target optimization strategy comprises, for each scheme, calculating total work and mesh number; wherein total work = work loss of mesh when being cut off each time + work loss of relative position alignment of mesh wire and anchor rod. The work loss of the net line when the relative position is aligned with the anchor rod includes, for each net piece, when the net piece is directly connected with the anchor rod a, if the anchor rod a is located in the net hole position, the work loss is 0; if the anchor rod a is on the net line b, the work loss is ; when the net piece is indirectly connected with the anchor rod a, the work loss is 0; wherein, represents the work needed to be done for the anchor rod a to be inserted into the mesh hole; represents the work loss per unit distance; represents the distance between the mesh wire b and the axis of the anchor rod a, and R represents the radius of the anchor rod; The strategy optimization is performed with the least number of meshes and the least work loss as the target.

5. The anchor on the net-based policy generation method of claim 4, wherein: The second round of target optimization strategy comprises Performing a layer-by-layer stability analysis on the digital twin model of the multi-layer hanging mesh to obtain an optimal scheme in stability; The stability of each layer is equal to the sum of the core stability of the current layer and all previous layers. The stability of each mesh y is assigned according to the relative position of the mesh y to the overlapping part of other meshes and the relative position of the mesh y to the anchor rod in each layer, and the core stability is obtained by summing the stability assignment results of all meshes in each layer; The stability of each mesh is the sum of the assignment results of two stability elements; The uniformity of the distribution of the overlapping area around the center of the mesh is calculated, and the first element of the stability of the mesh is obtained by assigning a feature value according to the uniformity; the stability assignment is performed by inputting the feature value result into the preset mapping function 1; When the anchor rod exists in the mesh, the support performance of each anchor rod in the mesh is analyzed, a feature value is assigned, and the second element of the stability of the mesh is obtained; the stability assignment is performed by inputting the feature value result into the preset mapping function 2.

6. A strategy generation system based on mesh hanging on anchor rods, which adopts the method according to any one of claims 1-5, characterized in that: An acquisition unit acquires the positions of all anchor rods in the tunnel and the size of the mesh, and corrects the size of the mesh; An simulation unit performs digital twinning on the anchor rod positions in the three-dimensional coordinate system, and constructs a digital twinning model of the multi-layer mesh hanging; An optimization unit performs multi-objective strategy optimization on the digital twinning model of the multi-layer mesh hanging, and generates a mesh hanging strategy on the anchor rods.

7. A computer device comprising: A memory and a processor; The memory stores a computer program, and the processor implements the steps of the method according to any one of claims 1-5 when executing the computer program.

8. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to implement the steps of the method according to any one of claims 1-5.

Images