Intelligent solution method for three-dimensional excavation boundary line of tunnel portal side slope

Abstract

The present application belongs to the technical field of tunnel design, and discloses a kind of tunnel portal side slope three-dimensional excavation boundary line intelligent solving method.The present application generates three-dimensional route and terrain model under local coordinate system by establishing tunnel portal local coordinate system;Based on tunnel portal three-dimensional route and terrain model, side slope design section is established, and excavation parameter is determined;The terrain feature point of side slope design section is calculated using projection method, and the natural ground line in section is generated;According to side slope design section and its excavation parameter, side slope surface line after excavation is generated, and the intersection of side slope surface line after excavation and natural ground line is taken as excavation boundary control point;According to clustering-improved discrete grey wolf algorithm, the coordinate set of excavation boundary control point is sorted, and the ordered control point coordinate set is obtained;According to three-dimensional spline curve and ordered control point coordinate set, tunnel portal side slope three-dimensional excavation boundary line is finally fitted, which can greatly improve the efficiency and accuracy of excavation boundary line solving.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tunnel design, in particular to a kind of tunnel portal side slope three-dimensional excavation boundary line intelligent solving method. BACKGROUND

[0002] In the construction of railway mountain tunnel portal project, often accompanied by a large number of natural and artificial side slope. Among them, the determination of side slope excavation boundary line is the premise of subsequent design, construction such as design of water drain ditch, calculation of engineering quantity and excavation construction lofting, and is one of the important contents of tunnel portal design.

[0003] At present, the design of tunnel portal side and slope excavation scheme is carried out on two-dimensional horizontal and vertical sections, so the excavation boundary line is also a two-dimensional multi-segment line calculated by artificial and finally expressed on the plane, and the main solution process is: design section is determined at intervals of 10m from the starting point of tunnel portal design and side slope excavation parameter design is completed; the intersection of design section trace and contour line is calculated one by one and line is drawn manually; the horizontal distance from the intersection point of design excavation line and natural ground line to tunnel center line is calculated; the excavation boundary line control point is made in the plane according to the above distance, the control point sequence is identified artificially, and the spline line is connected manually. It can be seen that the design and solution process of tunnel portal side and slope excavation boundary line contains a large number of steps that need to be identified, calculated and drawn manually, and the final result is output in two-dimensional form, which cannot meet the current efficient and refined design requirements.

[0004] The above content is only used to assist in understanding the technical solutions of the present application and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0005] The main purpose of the present application is to provide a kind of tunnel portal side slope three-dimensional excavation boundary line intelligent solving method, to solve the technical problems of low automation and low precision in the prior art.

[0006] To achieve the above purpose, the present application provides a kind of tunnel portal side slope three-dimensional excavation boundary line intelligent solving method, the method comprises the following steps:

[0007] Establish a local coordinate system of tunnel portal, and generate a tunnel portal three-dimensional route and a terrain model according to the local coordinate system of tunnel portal;

[0008] Generate a side slope design section based on the tunnel portal three-dimensional route and the terrain model, and determine the excavation parameters;

[0009] Calculate the characteristic points of the side slope design section according to the projection method, and generate the natural ground line of the side slope design section according to the characteristic points;

[0010] According to the edge-slope design section and the excavation parameters thereof, an edge-slope surface line after excavation is generated, and the natural ground line is obtained by intersecting the natural ground line with the edge-slope surface line, and a coordinate set of an excavation boundary control point is obtained by intersecting the natural ground line with the edge-slope surface line;

[0011] According to the cluster-improved discrete grey wolf algorithm, the coordinate set of the excavation boundary control point is sorted to obtain an ordered control point coordinate set;

[0012] According to the three-dimensional spline curve and the ordered control point coordinate set, a three-dimensional excavation boundary line is fitted.

[0013] Optionally, the edge-slope design section is generated based on the tunnel portal three-dimensional line and the terrain model, and the excavation parameters are determined, including:

[0014] A control mileage in the tunnel portal is determined;

[0015] A slope control design section is determined with the line coordinates of the control mileage as an origin and a plane perpendicular to the line as the slope control design section, and excavation parameters of the slope control design section are determined, the excavation parameters of the slope control design section including at least temporary slope height, slope rate, permanent slope height, slope rate, and step width;

[0016] A slope control design section is determined with the light-dark division mileage as an origin and a plane parallel to the line as the slope control design section, and excavation parameters of the slope control design section are determined, the excavation parameters of the slope control design section including at least temporary slope height, slope rate, permanent slope height, slope rate, and step width;

[0017] The gap between the slope control design section and the slope control design section is encrypted according to a preset interval to obtain a slope encrypted design section and a slope encrypted design section;

[0018] The excavation parameters of the slope control design section and the slope control design section are interpolated to obtain the excavation parameters of the slope encrypted design section and the slope encrypted design section.

[0019] Optionally, the feature points of the edge-slope design section are calculated according to the projection method, and the natural ground line of the edge-slope design section is generated according to the feature points, including:

[0020] According to the origin of the edge-slope design section, a projection trace line of the edge-slope design section on a horizontal plane is obtained along a direction perpendicular to the line;

[0021] The projection trace line is discretized according to a preset discrete precision to obtain a plurality of segment points;

[0022] According to the cross-section origin coordinates, the direction vector perpendicular to the line direction, and the length of the cross-section projection trace, the planar coordinates of the characteristic points of the ground line in the design cross-section are obtained;

[0023] According to the planar coordinates of the characteristic points of the ground line in the design cross-section, a vertical ray is intersected with the unit terrain surface, and the intersection point is added to the terrain surface intersection point list;

[0024] The intersection points of the terrain surface intersection point list are sequentially connected to generate the natural ground line of the side-slope design cross-section.

[0025] Optionally, the generation of the coordinate set of the excavation boundary control points according to the intersection points of the post-excavation side-slope surface line and the natural ground line of the same cross-section comprises:

[0026] Establishing the set of excavation boundary control points;

[0027] According to the excavation parameters, the post-excavation side-slope surface line is calculated and drawn;

[0028] The post-excavation side-slope surface line is intersected with the natural ground line of the same cross-section to obtain the control point coordinates, and the control point coordinates are added to the set of excavation boundary control points.

[0029] Optionally, the sorting of the coordinate set of the excavation boundary control points according to the clustering-improved discrete gray wolf algorithm to obtain the ordered control point coordinate set comprises:

[0030] The coordinate set of the excavation boundary control points is segmented by k-means clustering to obtain a left subset and a right subset;

[0031] The left subset and the right subset are traversed respectively, and the point closest to the segmentation line in the subset is taken as the sorting starting point of the corresponding subset;

[0032] According to the improved discrete gray wolf algorithm, the control point coordinates in the left subset and the right subset are sorted respectively with the sorting starting point;

[0033] The sorted right subset is reversed, and the reversed right subset and the sorted left subset are spliced again to obtain the ordered control point coordinate set.

[0034] Optionally, the sorting of the coordinate set of the excavation boundary control points according to the improved discrete gray wolf algorithm with the sorting starting point comprises:

[0035] The basic parameters of the improved discrete gray wolf algorithm are determined, and the basic parameters at least include the population size, the variable dimension, the search space, the basic mutation ratio, the maximum mutation ratio, and the iteration number.

[0036] According to the number of points to be sorted in the control point coordinate set, the index of the point is taken as a set of sorting solutions;

[0037] Connecting the control points in the coordinate set in the order of the sorting solutions to obtain a polyline, and taking the length of the polyline as fitness;

[0038] Based on the number of populations, a plurality of groups of feasible sorting solutions are generated according to a shuffle algorithm, and the same point does not appear repeatedly in the same group of sorting solutions;

[0039] The fitness is sorted, and the part with the fitness greater than the variable neighborhood lower limit is subjected to variable neighborhood search, and the variable neighborhood lower limit is obtained by the basic mutation ratio, the maximum mutation ratio, the current iteration number and the maximum iteration number;

[0040] According to the direction of moving the position of the current individual to the optimal position in the population, the exchange order is determined;

[0041] According to the exchange order and a random number, the position update order of the current individual is determined;

[0042] According to the position update order of the current individual, the position of the current individual is updated;

[0043] The steps of sorting the fitness and performing variable neighborhood search on the part with the fitness greater than the variable neighborhood lower limit are repeatedly executed until the iteration number reaches an upper limit.

[0044] In addition, in order to achieve the above purpose, the application further provides a tunnel portal side slope three-dimensional excavation boundary line intelligent solving device, the tunnel portal side slope three-dimensional excavation boundary line intelligent solving device comprises:

[0045] A solving preparation module is configured to establish a tunnel portal local coordinate system and generate a tunnel portal three-dimensional route and a terrain model according to the tunnel portal local coordinate system;

[0046] A section solving module is configured to generate a side slope design section based on the tunnel portal three-dimensional route and the terrain model, and determine excavation parameters;

[0047] The curve solving module is further configured to calculate feature points of the side slope design section according to a projection method, and generate a natural ground line of the side slope design section according to the feature points;

[0048] A coordinate determination module is configured to generate a side slope surface line after excavation according to the side slope design section and the excavation parameters thereof, intersect the natural ground line with the natural ground line, and obtain a coordinate set of excavation boundary control points;

[0049] The coordinate sorting module is configured to sort a set of coordinates of the excavation boundary control points according to the cluster-improved discrete grey wolf algorithm to obtain an ordered control point coordinate set.

[0050] The result output module is configured to obtain a three-dimensional excavation boundary line according to the three-dimensional spline curve and the ordered control point coordinate set.

[0051] In addition, to achieve the above-mentioned purpose, the present application also provides a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device, which comprises a memory, a processor and a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program stored in the memory and executable on the processor, and the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program is configured to implement the steps of the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method as described above.

[0052] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which stores a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program, and the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program implements the steps of the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method as described above when executed by a processor.

[0053] The present application can greatly improve the efficiency and precision of the edge and slope excavation boundary line solving by establishing a tunnel portal local coordinate system, generating a tunnel portal three-dimensional line and a terrain model according to the tunnel portal local coordinate system, generating an edge and slope design section based on the tunnel portal three-dimensional line and the terrain model, determining excavation parameters, calculating feature points of the edge and slope design section according to the projection method, generating a natural ground line of the edge and slope design section according to the feature points, generating an edge / slope surface line after excavation according to the excavation parameters and the edge and slope design section, obtaining the coordinates of the control points according to the edge / slope surface line after excavation, sorting the coordinates of the control points according to the cluster-improved discrete grey wolf algorithm to obtain an ordered control point coordinate set, and fitting a three-dimensional spline curve with the ordered control point coordinate set to obtain a three-dimensional excavation boundary line. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 is a structural schematic diagram of a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device related to the hardware running environment of the embodiment scheme of the present application;

[0055] Figure 2 is a flowchart of the first embodiment of the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method of the present application;

[0056] Figure 3 is a technical roadmap of the first embodiment of the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method of the present application;

[0057] Figure 4 The tunnel portal line and the surrounding terrain schematic diagram of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application;

[0058] Figure 5 The portal surrounding three-dimensional terrain surface of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application;

[0059] Figure 6 The control design section and the encryption design section schematic diagram of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application;

[0060] Figure 7 The excavation boundary control point on the slope design section LP+06 of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application;

[0061] Figure 8 The scattered boundary control point set before sorting of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application;

[0062] Figure 9 The flowchart schematic diagram of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method second embodiment of the application;

[0063] Figure 10 The flowchart of the improved discrete gray wolf algorithm for intelligent sorting of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application;

[0064] Figure 11 The schematic diagram of three kinds of variable neighborhood operations of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application, including reverse order, exchange and insertion;

[0065] Figure 12 The result of the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application, which divides the complete point set into left and right subsets by using clustering;

[0066] Figure 13 The fitness convergence process when the right subset is intelligently sorted in the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application;

[0067] Figure 14 The fitness convergence process when the left subset is intelligently sorted in the tunnel portal edge slope three-dimensional excavation boundary line intelligent solving method first embodiment of the application;

[0068] Figure 15The high-precision three-dimensional excavation boundary line of the first embodiment of the tunnel portal side slope three-dimensional excavation boundary line intelligent solving method of the application;

[0069] Figure 16 The structural block diagram of the first embodiment of the tunnel portal side slope three-dimensional excavation boundary line intelligent solving device of the application.

[0070] The implementation, functional features and advantages of the application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0071] It should be understood that the specific embodiments described herein are merely intended to explain the application and are not intended to limit the application.

[0072] Reference Figure 1 , Figure 1 The structural diagram of the tunnel portal side slope three-dimensional excavation boundary line intelligent solving device related to the hardware running environment of the embodiment scheme of the application.

[0073] As Figure 1 shown, the tunnel portal side slope three-dimensional excavation boundary line intelligent solving device can include a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between the components. The user interface 1003 can include a display screen, an input unit such as a keyboard, and can also include a standard wired interface, a wireless interface. The network interface 1004 can optionally include a standard wired interface, a wireless interface (such as a wireless fidelity (Wi-Fi) interface). The memory 1005 can be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a magnetic disk memory. The memory 1005 can also be a storage device independent of the aforementioned processor 1001.

[0074] Those skilled in the art can understand Figure 1 that the structure shown in the figure does not constitute a limitation on the tunnel portal side slope three-dimensional excavation boundary line intelligent solving device, and can include more or fewer components than the illustrated components, or combine certain components, or different component arrangements.

[0075] As Figure 1As a storage medium, the memory 1005 can include an operating system, a network communication module, a user interface module, and a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program.

[0076] In Figure 1 In the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device shown, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device can be arranged in the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device, the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device calls the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program stored in the memory 1005 through the processor 1001, and executes the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method provided in the embodiment of the application.

[0077] The embodiment of the application provides a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method, which refers to Figure 2 , Figure 2 The tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method provided in the embodiment of the application is shown in the flowchart of the first embodiment.

[0078] In the embodiment, the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method comprises the following steps:

[0079] Step S10: Establishing a tunnel portal local coordinate system, and generating a tunnel portal three-dimensional route and a terrain model according to the tunnel portal local coordinate system.

[0080] It should be noted that the execution subject of the embodiment is a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device, wherein the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device has functions of data processing, data communication and program running, and can be an integrated controller, a control computer or other devices with similar functions, and the embodiment does not limit this.

[0081] It should be understood that the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method provided in the embodiment of the application refers to Figure 3 , Figure 3 The technical flowchart of the present scheme is shown. The line data and the terrain point cloud data are extracted from the early survey design results, the left line inner rail top point at the portal design mileage is taken as the origin, the line direction is taken as the y direction, the portal local coordinate system is established, the line horizontal and vertical control point coordinates are converted to the portal local coordinate system, and a three-dimensional route model is generated by fitting; the ground point cloud in the influence range of the tunnel portal is screened, the coordinates are extracted and the coordinate system is converted, and a three-dimensional terrain surface of the portal is established.

[0082] A single-hole double-line tunnel exit is planned to be located in the DK216+386~DK216+405 mileage range, the tunnel portal type is selected as a hat inverted cut type portal, the design length is 19 m, and the design outer diameter is 14.7 m. The terrain around the tunnel exit is shown in Figure 4 , and the ground surface is mainly covered by silty clay and fully weathered slate.

[0083] In the specific implementation, a local coordinate system of the tunnel exit is established with the top surface of the left line rail at the DK216+386 mileage of the tunnel exit as the origin, and the line direction of the large mileage as the y direction. A 50 m range is intercepted from the local coordinate origin to the large and small mileage directions, respectively, the line control point coordinates of the tunnel portal section are extracted and converted to the coordinate system, and a smooth three-dimensional line model is fitted again. At the same time, the terrain point cloud in the interception range is extended by 50 m around the local coordinate origin, and is registered to the local coordinate, and a three-dimensional terrain surface mesh is generated by using Delaunay subdivision as shown in Figure 5 .

[0084] Step S20: generating side and slope design sections based on the three-dimensional line of the tunnel portal and the terrain model, and determining excavation parameters.

[0085] It can be understood that the control mileage in the portal section is selected, the line coordinate at the control mileage is taken as the origin, and the plane perpendicular to the line is taken as the slope control design section; the number of steps, slope height, slope rate, and step width in all control design sections are determined one by one; the light and dark boundary mileage is taken as the origin, the plane parallel to the line is taken as the slope control design section, and the excavation parameters of the slope control section are designed. After the control section design is completed, the encrypted side slope design section and slope design section are generated as shown in Figure 6 at intervals of 0.5-1 m, and the excavation parameters are determined by interpolation of the corresponding parameters of two adjacent control sections.

[0086] Further, the generation of the side and slope design sections based on the three-dimensional line of the tunnel portal and the terrain model, and the determination of the excavation parameters, include:

[0087] determining the control mileage in the tunnel portal;

[0088] taking the line coordinate at the control mileage as the origin, taking the plane perpendicular to the line as the slope control design section, and determining the excavation parameters of the slope control design section;

[0089] taking the light and dark boundary mileage as the origin, taking the plane parallel to the line as the slope control design section, and determining the excavation parameters of the slope control design section;

[0090] The gaps between the side slope control design section and the upward slope control design section are encrypted according to a preset interval to obtain a side slope encrypted design section and an upward slope encrypted design section.

[0091] The excavation parameters of the side slope control design section and the excavation parameters of the upward slope control design section are interpolated to obtain the excavation parameters of the side slope and upward slope encrypted design sections.

[0092] In a specific implementation, four side slope control design sections are established with DK216+386, DK216+387, DK216+390 and DK216+405 as control mileages. Similarly, two upward slope control design sections parallel to the line direction are established at the light-dark boundary mileage DK216+405. In each design section, the excavation parameters such as the number of side slope / upward slope, slope height, slope rate and step width are designed, as shown in Table 1. After the control section excavation parameters are determined, 15 side slope encrypted design sections and 12 upward slope encrypted design sections are automatically encrypted at an interval of 1 m, and their excavation parameters are automatically calculated.

[0093] Table 1: Side slope control design section excavation parameter table

[0094]

[0095]

[0096] Step S30: calculating the feature points of the side / upward slope design section according to the projection method, and generating the natural ground line of the side / upward slope design section according to the feature points.

[0097] It should be noted that for all side slope design sections and upward slope design sections, the feature points of the terrain surface in the design section are calculated according to the projection method according to the required accuracy, and the natural ground line in the section is generated based on this.

[0098] Further, the calculating the terrain feature points of the side / upward slope design section according to the projection method, and generating the natural ground line of the side / upward slope design section according to the feature points, comprises:

[0099] obtaining the projection trace of the side / upward slope design section on the horizontal plane according to the origin of the side / upward slope design section along the direction perpendicular to the line direction;

[0100] discretizing the projection trace according to a preset discrete precision to obtain a plurality of segment points;

[0101] obtaining the plane coordinates of the feature points of the ground in the design section according to the origin coordinates of the section, the direction vector perpendicular to the line direction and the length of the section projection trace;

[0102] According to the planar coordinates of the feature points of the ground line in the design section, a vertical ray is intersected with the unit terrain surface, and the intersection point is added to the terrain surface intersection point list;

[0103] The intersection points of the terrain surface intersection point list are sequentially connected to generate the natural ground line of the side-slope design section.

[0104] In a specific implementation, a projection trace of the design section on the origin plane is made, and the trace is segmented at intervals of 0.5 m as the x and y coordinates of the natural ground line control points. Taking the DK216+390 design section as an example, the x and y coordinates of the ground line control points are calculated according to formula 1, and a vertical ray is made upward from the segmentation point as the starting point to obtain the elevation of the intersection point of the ray and the three-dimensional terrain surface as the z coordinate of the control point. The results are shown in Table 2. The projection trace of the section on the horizontal plane is made along the x direction through the origin of the design section, and the trace is discretized at a set precision Δn meters. The coordinates of the segmented points can be calculated according to formula 1:

[0105]

[0106] In the formula, proj i (x, y) is the planar coordinate of the i-th feature point of the ground line in the design section, O is the coordinate of the section origin, is the normalized section x-direction vector, and len is the length of the projection trace of the section.

[0107] Table 2: Natural ground line control point coordinate table of DK216+390 section:

[0108]

[0109]

[0110] According to the coordinate data in Table 2, all the control points are sequentially connected to generate the natural ground line in the design section DK216+390.

[0111] Step S40: According to the side-slope design section and its excavation parameters, the post-excavation side-slope surface line is generated, and the coordinates of the excavation boundary control points are obtained by intersecting with the natural ground line.

[0112] In a specific implementation, according to the side-slope design section and its excavation parameters, the post-excavation side-slope surface line is generated, and the coordinates of the control points obtained can be described as establishing the excavation boundary control point set. According to the side-slope excavation parameters, the post-excavation side-slope surface line in all design sections is calculated and drawn, and an intersection operation is performed with the natural ground line in the same section. All intersection points are added to the control point set. Since there may be multiple intersection points in the same section, the control point set obtained at this time is in a scattered and disordered state.

[0113] Further, the method comprises: generating a slope surface line after excavation according to the design section of the slope and the excavation parameters, and obtaining a coordinate set of the excavation boundary control points according to the intersection of the slope surface line after excavation and the natural ground line.

[0114] establishing a set of excavation boundary control points;

[0115] calculating and drawing the slope surface line after excavation according to the excavation parameters;

[0116] performing intersection operation on the slope surface line after excavation and the natural ground line of the same section to obtain control point coordinates, and adding the control point coordinates to the set of excavation boundary control points.

[0117] In a specific implementation, the set of excavation boundary control points is established by collecting the intersection points of the slope surface line after excavation and the natural ground line in all design sections, and the control point coordinates of the slope surface line after excavation are calculated. The control points of the slope surface after excavation of all design sections can be calculated according to the excavation parameters:

[0118]

[0119] In the formula, O n,i is the i-th control point coordinate of the design section n, O n,x , O n,y , O n,z are the x, y, and z coordinates of the origin of the section, l s is the distance from the origin of the section to the slope starting point, α n is the angle between the section and the x-axis direction of the local coordinate system, sw j , and pw j are the widths of the j-th slope / step in the section, and sh j is the height of the j-th slope.

[0120] For all design sections, the coordinates calculated according to formula 2 are sequentially connected to form the slope surface line after excavation, and the intersection operation is performed on the slope surface line after excavation and the natural ground line. At this time, the intersection points are the excavation boundary control points, so all intersection points are added to the set of boundary control points.

[0121] Taking the upper slope design section LP+06 as an example, the excavation control point coordinates calculated according to formula 2 are shown in Table 3, which are connected and drawn as the slope surface line after excavation, and intersected with the natural ground line in the same design section to obtain three excavation boundary control point coordinates as shown in Figure 7 Table 4, which are (0.91, 23.55, 379.19), (0.91, 34.31, 384.19), and (0.91, 37.31, 386.19).

[0122] Table 3: Coordinates of ground line control points after excavation of design section LP+06 of side slope

[0123] Excavation control point x coordinate y coordinate z coordinate Primary temporary slope start 0.91 19.00 362.09 Primary temporary slope end 0.91 19.00 373.64 Secondary temporary slope end 0.91 21.00 375.64 Primary permanent slope end 0.91 31.00 383.64 Primary step end 0.91 33.00 383.64 Secondary permanent slope end 0.91 43.00 391.64 Secondary step end 0.91 45.00 391.64 Tertiary permanent slope end 0.91 55.00 399.64 Tertiary step end 0.91 57.00 399.64

[0124] As shown in Figure 8 , the excavation boundary control points in all design sections are solved one by one and integrated to obtain a complete but disordered set of excavation boundary control points.

[0125] Step S50: Sort the set of coordinates of the excavation boundary control points according to the clustering-improved discrete grey wolf algorithm to obtain an ordered set of control point coordinates.

[0126] In a specific implementation, the disordered control point set is intelligently sorted using the clustering-improved discrete grey wolf algorithm. To generate a continuous, non-self-intersecting and shortest three-dimensional excavation boundary line, the control point set is segmented into left and right subsets using the k-means clustering method; the disordered points are intelligently sorted in each subset using the discrete grey wolf optimization algorithm; and the sorted subsets are reversed and spliced to generate a complete and ordered control point set.

[0127] Step S60: Fit a three-dimensional excavation boundary line according to the three-dimensional spline curve and the ordered set of control point coordinates.

[0128] In a specific implementation, the three-dimensional excavation boundary line is fitted using a three-dimensional spline curve and an ordered control point. According to the control point coordinates and the connection order, the three-dimensional B-Spline curve is used to fit it to generate a smooth transition three-dimensional excavation boundary line, and the obtained three-dimensional excavation boundary is applied to the actual tunnel excavation process.

[0129] The embodiment establishes a local coordinate system of a tunnel portal, generates a three-dimensional route and terrain model of the tunnel portal according to the local coordinate system of the tunnel portal, generates a side and side slope design section based on the three-dimensional route and terrain model of the tunnel portal, determines excavation parameters, calculates terrain feature points of the side and side slope design section according to the projection method, generates a natural ground line of the side and side slope design section according to the feature points, generates a post-excavation side / side slope surface line according to the excavation parameters and the side and side slope design section, obtains the coordinates of the control points according to the post-excavation side / side slope surface line, sorts the coordinates of the control points according to the clustering-improved discrete grey wolf algorithm to obtain an ordered set of control point coordinates, and fits a three-dimensional excavation boundary line according to the three-dimensional spline curve and the ordered set of control point coordinates, which can greatly improve the efficiency and accuracy of solving the side and side slope excavation boundary line.

[0130] Reference Figure 9 , Figure 9 is a flowchart of a second embodiment of the intelligent solving method for a three-dimensional excavation boundary line of a side and side slope of a tunnel portal.

[0131] Based on the first embodiment, the tunnel portal edge three-dimensional excavation boundary line intelligent solving method of the embodiment further comprises the following steps S50 based on the first embodiment:

[0132] Step S501: The k-means clustering method is used to segment the coordinate set of the excavation boundary control points, to obtain a left subset and a right subset;

[0133] Step S502: The left subset and the right subset are traversed respectively, and the point closest to the distance segmentation line in the subset is taken as the sorting starting point of the corresponding subset;

[0134] Step S503: According to the improved discrete gray wolf optimization algorithm, the coordinates of the control points in the left subset and the right subset are sorted respectively with the sorting starting point;

[0135] Step S504: The right subset after sorting is subjected to a reverse sequence operation, and the right subset after the reverse sequence operation is spliced with the left subset after sorting to obtain the ordered control point coordinate set.

[0136] In a specific implementation, to improve the efficiency and accuracy of solving, the unordered control point set is segmented into left and right subsets, and then the subsets are intelligently sorted. In this method, to effectively divide the scattered points into left and right subsets and avoid interference from other directions, the number of clusters is set to 2 when clustering the points, and only the x coordinates of the points are considered for one-dimensional k-means clustering. For the left and right subsets, the points closest to the distance separation line are calculated and taken out respectively, as the starting points P sL , sR for sorting the subsets subsequently. The discrete gray wolf optimization algorithm is used to intelligently sort the remaining unordered points in the subsets, wherein the gray wolf optimization algorithm is a swarm intelligence optimization algorithm, and the idea is to regard the set of finite groups of feasible solutions of a problem as a gray wolf population, wherein the position of each gray wolf represents a group of feasible solutions, and then the search for the optimal solution can be regarded as a process of driving the gray wolf population to constantly update the position and take the optimal one. To solve discrete problems, the discrete gray wolf optimization algorithm is used. Meanwhile, to avoid premature convergence and falling into a local optimal solution, adaptive variable neighborhood search and local search strategies are used for improvement, and the optimization process of the improved discrete gray wolf optimization algorithm is as shown in Figure 10 .

[0137] First, the basic parameters of the optimization algorithm are set, including the population size, variable dimension, search space, basic mutation ratio v min , and maximum mutation ratio v maxand the main parameters such as the number of iterations, where the population size is the number of feasible solutions in iterations, the variable dimension is the number of variables in a set of feasible solutions, and the search space is the value range of the solution. The discrete grey wolf optimization algorithm redefines the feasible solution form and search range. For an unordered point set containing n points, the feasible ordering solution can be expressed as an n-dimensional vector:

[0138] X = (P1, P2,... P i ,...P n ) (Formula 3)

[0139] In the formula, X is a set of feasible solutions, n is the number of points to be sorted, P i is the point in the i-th position in the current solution, which is represented by the number of the point set before sorting. Based on this definition, the value range of each variable in the feasible solution is [1, 2,..., n], but due to the restriction of the non-self-intersection condition, the same point cannot appear in a set of solutions, so P i ≠ P j .

[0140] In order to make the multi-segment line connected by scattered points according to the ordering solution non-self-intersecting and shortest, a fitness function with a penalty mechanism is designed to solve the optimal ordering:

[0141]

[0142] In the formula, F is the fitness value, l(P s , P1) is the distance from the first point in the ordering solution to the given starting point P s , and l(P i , P i+1 ) is the length of the i-th segment in the multi-segment line generated by connecting according to the ordering solution.

[0143] Then initialize the position of the grey wolf population. According to the set population size p, use the shuffle algorithm to generate p sets of feasible ordering solutions to ensure that the same point does not appear in a set of solutions. Then calculate the fitness values of all grey wolves after initialization according to formula 4.

[0144] In order to improve the search ability of the algorithm, the improved discrete grey wolf optimization algorithm first performs variable neighborhood search on the part of the grey wolf individuals with the top m% fitness values before determining the identities of the alpha, beta, and theta wolves.

[0145]

[0146] In the formula, Iter now is the current iteration number, and Iter max is the maximum iteration number set.

[0147] The variable neighborhood search algorithm introduced in the method includes three operations of reverse order, exchange and insertion as shown in Figure 11 The reverse order is to invert the randomly selected part of the sorted solution; the exchange is to exchange the positions of the randomly selected two dimensions in the sorted solution; and the insertion is to move one dimension in the randomly selected two dimensions to the other dimension. The three operations are randomly selected to improve the diversity of the neighborhood structure.

[0148] Taking the determination of the new position of the nth wolf in the population as an example, the improved grey wolf position updating algorithm is described in detail. First, the exchange order SS of the grey wolf n and the wolves α, β and θ is calculated according to formula 6:

[0149] SS i-n =(X i -X n )(Formula 6)

[0150] In the formula, SS i-n is a series of position transformation operations required when the nth grey wolf approaches the ith grey wolf, so SS i-n is composed of multiple exchange operators SO representing a single transformation operation:

[0151] SS i-n ={SO n ,SO m ,...SO k ,SO j}(Formula 7)

[0152] In the formula, j, k, m, etc. are intermediate positions of the nth grey wolf and the ith grey wolf. Taking the transformation from solution X1=(1, 2, 3, 4) to solution X2=(1, 3, 2, 4) as an example, the 2nd and 3rd dimensions of X1 are exchanged to obtain the intermediate position X temp =(1, 2, 3, 4), and then the 3rd and 4th dimensions of the intermediate position are exchanged, so SS 2-1 =(X2-X1)={SO(2, 3), SO(3, 4)}.

[0153] By introducing the exchange order SS and the exchange operator SO, the position updating order D can be calculated according to formula 8:

[0154] D=c1×SS α-n +c2×SS β-n +c3×SS θ-n (Formula 8)

[0155] In the formula, c1, c2 and c3 are random numbers in [0, 1], SS α-n , SS β-n and SS θ-n are the exchange orders of the grey wolf n to the wolves α, β and θ, respectively.

[0156] The target updated position X of the gray wolf n in this iteration tar may be expressed as formula 9, that is, according to the commutator in the position update sequence D, the original position X is exchanged one by one n The exchange operation is as follows:

[0157] X tar = X n + D (formula 9)

[0158] In order to consider the optimal position that may appear in the change process, this method introduces a local search strategy, records all intermediate positions and their fitness during the transformation process, and when a certain intermediate position X tbest is better than the target position X tar , then X tbest is directly taken as the final determined new position of the gray wolf n after this iteration, that is:

[0159]

[0160] Repeat the variable neighborhood search on the part of the gray wolf individuals with the fitness value of the top m% respectively until the iteration number reaches the upper limit, at this time the position of the alpha wolf in the population is the optimal solution searched, and the right subset Set R after intelligent sorting is reversed, and then it is spliced with the left subset Set L after sorting to form a complete and ordered control point set Set new :

[0161]

[0162] Taking an actual case as an example, 75 unordered control points in Figure 8 are one-dimensionally clustered by k-means according to their x coordinates, which can be effectively divided into left and right subsets as shown in Figure 12 . The clustering centers of the left and right sides are-5.325 and 19.015 respectively, the left subset contains 44 points in total, and the maximum x coordinate is 5.933, and the right subset contains 31 points in total, and the minimum x coordinate is 6.932. The points farthest from the clustering centers in the left and right subsets are searched as the starting points for sorting the subsets, and the sorting starting point P sL of the left subset is (5.93, 40.91, 390.40), and the sorting starting point P sR of the right subset is (6.93, 40.73, 390.26).

[0163] Table 4: Control points and numbers in the left subset:

[0164]

[0165] Table 5: Control points and numbers in the right subset:

[0166]

[0167]

[0168] The starting points of the left and right subsets are extracted, and the remaining scattered points are intelligently sorted and optimized. Taking the sorting and optimization of the right subset as an example, the population size of the discrete grey wolf optimization algorithm is set to 300, the maximum number of iterations is set to 200, the variable dimension is set to 35, the basic mutation ratio v min is 0.1, and the maximum mutation ratio v max is 0.5. 300 grey wolves are randomly generated by using a shuffle algorithm, and the fitness value corresponding to the position (i.e., the connection order of the points in the subset) of each grey wolf is calculated according to formula 4. Taking the 82nd grey wolf in the first iteration as an example, the position updating process of the grey wolf is explained. Before the iteration starts, the grey wolves need to be sorted in ascending order of fitness, and then the variable neighborhood search is performed on the first 49.6% of the grey wolves. For the 82nd grey wolf, its original position is {18, 14, 21, 26, 20, 11, 17, 12, 13, 27, 28, 1, 0, 15, 10, 22, 24, 4, 3, 8, 7, 25, 16, 29, 6, 19, 5, 9, 23, 2}, and the fitness value is 407.22. By randomly determining the variable neighborhood operation as reversing the order of the 27th to 29th positions, the position of the grey wolf after the variable neighborhood operation is updated to {18, 14, 21, 26, 20, 11, 17, 12, 13, 27, 28, 1, 0, 15, 10, 22, 24, 4, 3, 8, 7, 25, 16, 29, 6, 19, 23, 9, 5, 2}. After the variable neighborhood search of the specified grey wolves is completed, the fitness values are calculated again according to the new positions, and the three smallest ones are determined as the alpha, beta, and theta wolves. After the variable neighborhood search, the position of the alpha wolf is {5, 7, 4, 0, 22, 21, 2, 13, 8, 16, 28, 29, 18, 17, 26, 1, 6, 25, 15, 24, 19, 3, 27, 12, 10, 11, 23, 9, 14, 20}, so the exchange between the 82nd grey wolf and the alpha wolf is SS α-82The sequence is {SO(0, 28), SO(1, 20), SO(2, 17), SO(3, 12), SO(4, 15), SO(5, 17), SO(6, 29), SO(7, 8), SO(8, 19), SO(9, 22), SO(11, 23), SO(12, 28), SO(13, 29), SO(14, 28), SO(15, 23), SO(16, 24), SO(17, 21), SO(18, 29), SO(19, 24), SO(20, 25), SO(21, 29), SO(23, 24), SO(24, 28), SO(25, 29), SO(28, 29)}, and the random number c1 is 0.81. Similarly, SS β-82 , SS θ-82 and c2, c3 can be calculated respectively, and the three are spliced to obtain the position update sequence D. Each SO operator in the position update sequence D is executed one by one for the 82nd wolf, so that it continuously approaches the target position. In order to consider local search, the intermediate position and the corresponding fitness value are recorded after each exchange is executed, and then the fitness value with the optimal fitness value is selected from the record as the local search result after all exchanges are executed. After the local search is completed, the final position of the 82nd wolf is determined as {18, 7, 4, 0, 22, 21, 2, 13, 8, 16, 28, 29, 26, 15, 10, 20, 24, 11, 3, 12, 14, 25, 27, 1, 6, 19, 23, 9, 5, 17}, and the fitness value is 332.06.

[0169] The above iteration process is repeated, and the positions of all gray wolves are updated in each iteration until the maximum number of iterations 200 is reached, and the best ordering of the right subset is obtained as {18, 29, 28, 27, 17, 16, 26, 25, 15, 14, 24, 13, 12, 11, 23, 22, 10, 21, 9, 8, 7, 20, 6, 5, 4, 19, 3, 2, 1, 0}, and the fitness value is 52.99. Similarly, the best ordering of the left subset can be obtained as {8, 2, 3, 1, 4, 5, 0, 6, 7, 10, 9, 11, 17, 12, 14, 16, 13, 21, 15, 20, 38, 39, 22, 23, 18, 19, 25, 26, 27, 32, 28, 24, 36, 37, 33, 34, 35, 40, 41, 29, 30, 42, 31}, and the fitness value is 58.19. The fitness convergence process when the right and left subsets are sorted by the improved discrete gray wolf algorithm is shown in FIGS. 1 and 2. Figure 13 Figure 14

[0170] In order to obtain a three-dimensional curve in a counterclockwise direction, the right subset after intelligent sorting is reversed, and the right sorting starting point P​​sR , right side sorting start point P sL and the right side subset of intelligent sorting, constitute a complete, ordered final sorting results, as shown in Table 6.

[0171] Table 6 complete control point set intelligent sorting results:

[0172]

[0173]

[0174] According to the coordinates and intelligent sorting sequence provided in Table 6, the edge slope excavation control points are connected in turn, and are fitted with a spatial B-spline curve, so that the edge slope excavation three-dimensional boundary line shown in Figure 6 can be generated. Figure 15

[0175] The embodiment solves the problem that the computer cannot directly connect the scattered control points to generate the boundary line, and needs to highly rely on manual recognition and sorting, by segmenting the unordered point set through k-means clustering, intelligently sorting in each subset by using the improved discrete grey wolf algorithm, and performing reverse order and splicing operations on the sorted subsets to generate an ordered complete point set.

[0176] In addition, the embodiment of the present application also provides a storage medium, and the storage medium stores a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program. When the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program is executed by a processor, the steps of the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method described above are realized.

[0177] Referring to Figure 16 , Figure 16 is a structural block diagram of the first embodiment of the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device of the present application.

[0178] As shown in Figure 16 , the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving device provided by the embodiment of the present application comprises:

[0179] The solving preparation module 10 is configured to establish a tunnel portal local coordinate system, and generate a tunnel portal three-dimensional route and a terrain model according to the tunnel portal local coordinate system.

[0180] The cross section solving module 20 is configured to generate an edge and slope design cross section based on the tunnel portal three-dimensional route and the terrain model, and determine excavation parameters.

[0181] The curve solving module 30 is further configured to calculate terrain feature points of the edge and slope design cross section according to the projection method, and generate a natural ground line of the edge and slope design cross section according to the feature points.

[0182] ​The coordinate determination module 40 is configured to generate a surface line of the side / overhanging slope after excavation according to the side / overhanging slope design section and the excavation parameters thereof, and obtain a coordinate set of the control points of the excavation boundary according to the intersection of the surface line of the side / overhanging slope after excavation and the natural ground line.

[0183] The coordinate sorting module 50 is configured to sort the coordinates of the control points according to the clustering-improved discrete grey wolf algorithm, and obtain an ordered control point coordinate set.

[0184] The result output module 60 is configured to fit a three-dimensional excavation boundary line according to the three-dimensional spline curve and the ordered control point coordinate set.

[0185] The embodiment can establish a local coordinate system of the tunnel portal, generate a three-dimensional line and a terrain model of the tunnel portal according to the local coordinate system of the tunnel portal, generate a side / overhanging slope design section based on the three-dimensional line and the terrain model of the tunnel portal, determine excavation parameters, calculate feature points of the side / overhanging slope design section according to the projection method, generate a natural ground line of the side / overhanging slope design section according to the feature points, generate a surface line of the side / overhanging slope after excavation according to the excavation parameters and the side / overhanging slope design section, obtain coordinates of control points according to the surface line of the side / overhanging slope after excavation, sort the coordinates of the control points according to the clustering-improved discrete grey wolf algorithm, obtain an ordered control point coordinate set, and fit a three-dimensional excavation boundary line according to the three-dimensional spline curve and the ordered control point coordinate set, so that the efficiency and the accuracy of solving the side / overhanging slope excavation boundary line can be greatly improved.

[0186] In an embodiment, the section solving module 20 is further configured to determine a control mileage in the tunnel portal, take a line coordinate of the control mileage as an origin, take a plane perpendicular to the line as a side slope control design section, and determine excavation parameters of the side slope control design section, the excavation parameters of the side slope control design section at least including a temporary side slope height, a slope rate, a permanent side slope height, a slope rate, and a step width; take a light-dark boundary mileage as an origin, take a plane parallel to the line as an overhanging slope control design section, and determine excavation parameters of the overhanging slope control design section, the excavation parameters of the overhanging slope control design section at least including a temporary overhanging slope height, a slope rate, a permanent overhanging slope height, a slope rate, and a step width; encrypt a gap between the side slope control design section and the overhanging slope control design section according to a preset interval to obtain a side slope encrypted design section and an overhanging slope encrypted design section; and perform interpolation on the excavation parameters of the side slope control design section and the overhanging slope control design section to obtain the excavation parameters of the side slope encrypted design section and the overhanging slope encrypted design section.

[0187] In an embodiment, the curve solving module 30 is further configured to obtain a projection trace of the side-slope design section on a horizontal plane according to an origin of the side-slope design section along a direction perpendicular to the line direction; discretize the projection trace according to a preset discrete precision to obtain a plurality of segment points; obtain plane coordinates of feature points of a ground line in the design section according to a section origin coordinate, a direction vector perpendicular to the line direction, and a length of the section projection trace; make a vertical ray intersect a unit terrain surface according to the plane coordinates of the feature points of the ground line in the design section, and add an intersection point to a terrain surface intersection point list; and connect the intersection points in the terrain surface intersection point list in sequence to generate a natural ground line of the side-slope design section.

[0188] In an embodiment, the coordinate determining module 40 is further configured to establish a set of excavation boundary control points; calculate and draw a side / overhang slope surface line after excavation according to the excavation parameters; perform intersection operation on the side / overhang slope surface line after excavation and a natural ground line of the same section to obtain control point coordinates, and add the control point coordinates to the set of excavation boundary control points.

[0189] In an embodiment, the coordinate sorting module 50 is further configured to segment the set of excavation boundary control point coordinates by using k-means clustering to obtain a left subset and a right subset; respectively traverse the left subset and the right subset, and take a point closest to a segmentation line in each subset as a sorting starting point of the corresponding subset; sort the control point coordinates in the left subset and the right subset respectively according to the sorting starting points by using an improved discrete grey wolf algorithm; perform reverse sequence operation on the sorted right subset, and re-splice the reverse-sequenced right subset and the sorted left subset to obtain the set of ordered control point coordinates.

[0190] In an embodiment, the coordinate sorting module 50 is further configured to determine basic parameters of the improved discrete grey wolf optimization algorithm, the basic parameters including at least population size, variable dimension, search space, basic mutation ratio, maximum mutation ratio, and iteration number; according to a number of points to be sorted in the control point coordinate set, indexes of the points are taken as a group of sorting solutions; a polyline is obtained by connecting the control points in the coordinate set in an order of the sorting solutions, and a length of the polyline is taken as a fitness; a plurality of groups of feasible sorting solutions are generated based on the population size according to a shuffle algorithm, and the same point does not appear repeatedly in the same group of sorting solutions; the fitness is sorted, and a variable neighborhood search is performed on a part of which the fitness is greater than a lower limit of the variable neighborhood, the lower limit of the variable neighborhood being obtained from the basic mutation ratio, the maximum mutation ratio, a current iteration number, and a maximum iteration number; a swapping order is determined according to a direction in which a current individual moves to an optimal position in the group; a position updating order of the current individual is determined according to the swapping order and a random number; a position of the current individual is updated according to the position updating order of the current individual; and the step of sorting the fitness and performing the variable neighborhood search on the part of which the fitness is greater than the lower limit of the variable neighborhood is repeatedly executed until the iteration number reaches an upper limit.

[0191] It should be understood that the above is only illustrative, and does not constitute any limitation on the technical solutions of the present application. In specific applications, those skilled in the art can set them up as needed, and the present application does not limit this.

[0192] It should be understood that, although the steps in the flowchart in the embodiments of the present application are displayed in sequence according to the arrows, these steps are not necessarily executed in sequence according to the arrows. Unless explicitly stated herein, the execution of these steps has no strict sequence limitation, and they can be executed in other orders. Moreover, at least part of the steps in the figure can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or sub-steps or stages of other steps.

[0193] It should be noted that the above-described workflow is only illustrative and does not constitute a limitation on the scope of protection of the present application. In actual applications, those skilled in the art can select part or all of them to achieve the purpose of the embodiment scheme according to actual needs, which is not limited herein.

[0194] Moreover, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of "including" "comprising" or "having" and variations thereof herein is intended to encompass the presence of one or more recited elements or steps and not the exclusion of any other integers or steps. The use of "including", "comprising", "having" and "with" and variations thereof herein is intended to encompass the presence of one or more recited elements or steps and not the exclusion of any other integers or steps.

[0195] The above-mentioned embodiment numbers of the present application are only for description, and do not represent the advantages or disadvantages of the embodiments.

[0196] Those skilled in the art can clearly understand the above-mentioned embodiment methods from the description of the embodiments that the above-mentioned embodiment methods can be realized by software and necessary general hardware platform, of course, can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as a read only memory (ROM) / RAM, a magnetic disk, an optical disk), and includes a plurality of instructions for making a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) execute the methods described in various embodiments of the present application.

[0197] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation, or direct or indirect application in other related technical fields, which is made by using the content of the specification and drawings of the present application, is also included in the patent protection scope of the present application.

Claims

1. A method for intelligently solving the three-dimensional excavation boundary line of the side slope of a tunnel portal, characterized in that, The intelligent tunnel portal edge slope three-dimensional excavation boundary line solving method comprises: establishing a tunnel portal local coordinate system, and generating a tunnel portal three-dimensional line and a terrain model according to the tunnel portal local coordinate system; generating an edge slope design section based on the tunnel portal three-dimensional line and the terrain model, and determining excavation parameters; calculating feature points of the edge slope design section according to a projection method, and generating a natural ground line of the edge slope design section according to the feature points; generating an edge slope surface line after excavation according to the edge slope design section and the excavation parameters, and intersecting the edge slope surface line with the natural ground line to obtain a coordinate set of excavation boundary control points; sorting the coordinate set of the excavation boundary control points according to a clustering-improved discrete grey wolf algorithm to obtain an ordered control point coordinate set; fitting a three-dimensional spline curve to the ordered control point coordinate set to obtain a three-dimensional excavation boundary line; wherein the sorting the coordinate set of the excavation boundary control points according to the clustering-improved discrete grey wolf algorithm to obtain the ordered control point coordinate set comprises: segmenting the excavation boundary control point coordinate set using k-means clustering to obtain a left subset and a right subset; traversing the left subset and the right subset respectively, and taking a point closest to a segmentation line in a subset as a sorting starting point of the corresponding subset; sorting control point coordinates in the left subset and the right subset respectively according to the sorting starting point and the improved discrete grey wolf algorithm; performing a reverse sequence operation on the sorted right subset, and re-splicing the reverse-sequence right subset with the sorted left subset to obtain the ordered control point coordinate set; wherein the sorting the coordinate set of the excavation boundary control points according to the improved discrete grey wolf algorithm comprises: determining basic parameters of the improved discrete grey wolf algorithm, wherein the basic parameters at least include a population size, a variable dimension, a search space, a basic mutation ratio, a maximum mutation ratio, and an iteration number; taking an index of a point as a set of sorting solutions according to a number of points to be sorted in the control point coordinate set; connecting control points in the coordinate set in the order of the sorting solutions to obtain a multi-segment line, and taking a length of the multi-segment line as a fitness; generating a plurality of groups of feasible sorting solutions based on the population size according to a shuffle algorithm, and not repeating the same point in the same group of sorting solutions; sorting the fitness, and performing a variable neighborhood search on a part with a fitness greater than a variable neighborhood lower limit, wherein the variable neighborhood lower limit is obtained from the basic mutation ratio, the maximum mutation ratio, a current iteration number, and a maximum iteration number; determining a swapping order according to a direction in which a current individual moves to an optimal position in a group; determining a position update order of the current individual according to the swapping order and a random number; updating the position of the current individual according to the position update order; repeating the step of sorting the fitness and performing the variable neighborhood search on the part with the fitness greater than the variable neighborhood lower limit until the iteration number reaches an upper limit.

2. The method of claim 1, wherein, the generating an edge slope design section based on the tunnel portal three-dimensional line and the terrain model, and determining excavation parameters, comprises: determining a control mileage in the tunnel portal; The line coordinates of the control mileage are taken as the origin, the plane perpendicular to the line is taken as the slope control design section, and the excavation parameters of the slope control design section are determined, the excavation parameters of the slope control design section at least including temporary slope height, slope rate, and permanent slope height, slope rate, and step width; The light-dark demarcation mileage is taken as the origin, the plane parallel to the line is taken as the upslope control design section, and the excavation parameters of the upslope control design section are determined, the excavation parameters of the upslope control design section at least including temporary upslope height, slope rate, and permanent upslope height, slope rate, and step width; The gaps between the slope control design section and the upslope control design section are encrypted according to a preset interval to obtain slope encrypted design sections and upslope encrypted design sections; The excavation parameters of the slope encrypted design sections and the upslope encrypted design sections are obtained by interpolation using the excavation parameters of the slope control design section and the upslope control design section.

3. The method of claim 1, wherein, The characteristic points of the slope / upslope design section are calculated according to the projection method, and the natural ground line of the slope / upslope design section is generated according to the characteristic points, including: The projection trace of the slope / upslope design section on the horizontal plane is obtained according to the origin of the slope / upslope design section along the direction perpendicular to the line; The projection trace is discretized according to a preset discrete precision to obtain a plurality of segment points; The plane coordinates of the characteristic points of the ground line in the design section are obtained according to the section origin coordinates, the direction vector perpendicular to the line direction, and the length of the section projection trace; The vertical rays are intersected with the unit terrain surface according to the plane coordinates of the characteristic points of the ground line in the design section, and the intersection points are added to the terrain surface intersection point list; The intersection points of the terrain surface intersection point list are sequentially connected to generate the natural ground line of the slope / upslope design section.

4. The method of claim 1, wherein, The post-excavation slope / upslope surface line is generated according to the slope / upslope design section and the excavation parameters thereof, and the coordinate set of the excavation boundary control points is obtained according to the post-excavation slope / upslope surface line and the natural ground line, including: The excavation boundary control point set is established; The post-excavation slope / upslope surface line is calculated and drawn according to the excavation parameters; The post-excavation slope / upslope surface line is intersected with the natural ground line of the same section to obtain the control point coordinates, and the control point coordinates are added to the excavation boundary control point set.

5. A tunnel portal edge and bench three-dimensional excavation boundary line intelligent solution device according to the tunnel portal edge and bench three-dimensional excavation boundary line intelligent solution method of claim 1, characterized in that, The tunnel portal slope / upslope three-dimensional excavation boundary line intelligent solving device includes: A solving preparation module is configured to establish a tunnel portal local coordinate system and generate a tunnel portal three-dimensional line and a terrain model according to the tunnel portal local coordinate system; A section solving module is configured to generate a slope / upslope design section based on the tunnel portal three-dimensional line and the terrain model and determine excavation parameters; A curve solving module is further configured to calculate characteristic points of the slope / upslope design section according to a projection method and generate a natural ground line of the slope / upslope design section according to the characteristic points; A coordinate determining module is configured to generate a post-excavation slope surface line according to the slope / upslope design section and the excavation parameters thereof, intersect the natural ground line, and obtain a coordinate set of excavation boundary control points. The coordinate sorting module is configured to sort the coordinate set of the excavation boundary control point according to a clustering-improved discrete grey wolf algorithm, to obtain an ordered control point coordinate set. The result output module is configured to obtain a three-dimensional excavation boundary line according to a three-dimensional spline curve and the ordered control point coordinate set. The coordinate sorting module is configured to sort the coordinate set of the excavation boundary control point according to a clustering-improved discrete grey wolf algorithm, to obtain an ordered control point coordinate set. The k-means clustering is used to segment the control point coordinate set of the excavation boundary, to obtain a left subset and a right subset. The left subset and the right subset are traversed respectively, and the point closest to the segmentation line in the subset is taken as a sorting starting point of the corresponding subset. The control point coordinates in the left subset and the right subset are sorted respectively according to the sorting starting point and the improved discrete grey wolf algorithm. The right subset after sorting is subjected to a reverse sequence operation, and the right subset after the reverse sequence operation is spliced with the left subset after sorting, to obtain the ordered control point coordinate set. The coordinate sorting module is configured to sort the coordinate set of the excavation boundary control point according to a clustering-improved discrete grey wolf algorithm, to obtain an ordered control point coordinate set. The basic parameters of the improved discrete grey wolf algorithm are determined, and the basic parameters at least include a population number, a variable dimension, a search space, a basic mutation ratio, a maximum mutation ratio, and an iteration number. According to the number of points to be sorted in the control point coordinate set, the index of the point is taken as a group of sorting solutions. A multi-segment line is obtained by connecting the control points in the coordinate set in the order of the sorting solutions, and the length of the multi-segment line is taken as a fitness. A plurality of groups of feasible sorting solutions are generated according to a shuffle algorithm based on the population number, and the same point does not appear repeatedly in the same group of sorting solutions. The fitness is sorted, and the part with the fitness greater than a variable neighborhood lower limit is subjected to a variable neighborhood search, and the variable neighborhood lower limit is obtained from the basic mutation ratio, the maximum mutation ratio, the current iteration number, and the maximum iteration number. The exchange order is determined according to the direction in which the position of the current individual moves to the optimal position in the group. The position update order of the current individual is determined according to the exchange order and a random number. The position of the current individual is updated according to the position update order of the current individual. The step of sorting the fitness and subjecting the part with the fitness greater than the variable neighborhood lower limit to the variable neighborhood search is repeatedly performed until the iteration number reaches an upper limit.

6. A device for intelligently solving the three-dimensional excavation boundary line of the side slope of a tunnel portal, characterized in that, The device includes a memory, a processor, and a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program stored on the memory and executable on the processor, and the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program is configured to implement the steps of the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method according to any one of claims 1 to 4.

7. A storage medium, characterized by The storage medium stores a tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program, and the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving program implements the steps of the tunnel portal edge and slope three-dimensional excavation boundary line intelligent solving method according to any one of claims 1 to 4 when executed by the processor.

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