Mine roadway parameterized entity model construction method
By constructing a parametric solid model of mine roadways, the problem of difficulty in integrating multi-source data and long model update cycle in traditional roadway modeling is solved. It achieves efficient and flexible visualization and low-cost model updates, supporting digital management and 3D modeling of mines.
Patent Information
- Application Number
- CN202511024543.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-24
- Publication Date
- 2025-11-07
AI Technical Summary
Existing traditional tunnel modeling methods suffer from difficulties in integrating multi-source data, adjusting visualization attributes, long model update cycles, and high costs, making them unable to meet the needs of mine digital management and digital twin systems.
A method for constructing a parametric solid model of a mine roadway is provided, including acquiring modeling data, automatically configuring parameters, preprocessing and solid modeling, constructing a high-precision roadway model through coordinate transformation, roadway splitting and three-dimensional Boolean operations, and optimizing the model by merging geometric objects, compressing vertex data and compressing textures.
It achieves efficient fusion of multi-source data, flexibly adjusts visualization attributes, shortens the model update cycle, reduces costs, and improves the efficiency of digital design and 3D modeling of mining engineering.
Smart Images
Figure CN120912810A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of intelligent mine construction and three-dimensional modeling, and more particularly to a mine roadway parameterized entity model construction method. BACKGROUND
[0002] As the "lifeline" of underground resource exploitation, the precision and real-time performance of the three-dimensional model of mine roadway directly affect the efficiency of digital mine management. Under the background of intelligent mine construction, roadway modeling is not only a geometric expression of spatial form, but also a core data carrier for realizing mine digital twin system. Its key role is reflected in the integration of geological, engineering, equipment and other multi-source data in the roadway model, providing a unified visual decision-making platform for resource scheduling, safety monitoring and production planning. At the same time, high-precision models support roadway ventilation simulation, equipment layout optimization and other scenarios, reducing the cost of manual inspection and improving management efficiency. However, the existing traditional roadway modeling method has significant defects in supporting digital management or mine digital twin application, such as difficulty in integrating multi-source data, difficulty in adjusting the visual properties of the model such as color and transparency for local or different components of the roadway, long model update cycle and high cost. Therefore, how to provide a mine roadway parameterized entity model construction method is a problem that needs to be solved by those skilled in the art. SUMMARY
[0003] Therefore, the present application provides a mine roadway parameterized entity model construction method, which realizes entity modeling based on roadway parameters to provide more accurate model spatial position, more flexible model data organization to support rich visualization effects and more efficient model update efficiency.
[0004] To achieve the above purpose, the present application provides the following technical scheme:
[0005] A mine roadway parameterized entity model construction method, comprising the following steps:
[0006] S1, obtaining modeling data for mine roadway entity modeling;
[0007] S2, configuring the automatic modeling parameters of the modeling data;
[0008] S3, preprocessing the modeling data, including coordinate conversion and roadway splitting;
[0009] S4, automatically constructing roadway entity modeling based on the preprocessed modeling data.
[0010] Optionally, S1 is specifically: acquiring the geometric data of the roadway, including the roadway center line and section information, the information extracted by the roadway center line being the spatial coordinates at the inflection points of the roadway center line, and the data after extraction being constructed into a coordinate system according to the actual spatial position of the roadway and saved in a geographic information spatial data format; the section shape information including the shape and size of the section.
[0011] Optionally, the automatic modeling parameters in S2 include the roadway center line data, section information, and custom roadway wall thickness, roadway texture data, and curve segmentation number parameters of circular and arched section roadways; when the roadway wall thickness parameter is greater than 0, a double-layer roadway is constructed, otherwise a single-layer roadway; the texture data of the roadway includes the inner and outer textures of the roadway, which are used to distinguish the inside and outside of the roadway; the curve segmentation number of the circular and arched section roadways is used to control the fineness of the curved surface model.
[0012] Optionally, the coordinate conversion in S3 is specifically: checking whether the coordinate systems of all roadway center line data are consistent, if not, converting through the conversion parameters between the coordinate systems, unifying to the same coordinate system, then calculating the bounding box using all the vertex coordinates of the roadway center line after unifying the coordinate system, obtaining the bounding box center point coordinates, and traversing the center line vertex coordinates and the bounding box center point coordinates to calculate the local coordinates of the center line and save them.
[0013] Optionally, the roadway splitting in S3 is specifically: traversing all the vertex coordinates of the roadway center line, splitting the roadway center line into point and line data structures according to the rule that two points form a line, and removing duplicate points in the splitting process by using the rule that the distance between two points is 0 to ensure the unique correspondence of points and lines; the point represents a tunnel node TunnelNode, the line represents a tunnel segment TunnelLine, the data structure of the point records a unique number pid, associated line segments relationLines and point coordinates, the line segment data structure records a unique number lid, the start point startPoint and the end point endPoint of the line segment, the roadway texture data textures, the section information sectionInfo, the roadway wall thickness thickness, and the curve segmentation number segment; the split points are stored in the tunnel node array, and the line data are stored in the relationLines array of the point data.
[0014] Optionally, S4 is specifically:
[0015] S41, traverse the tunnel node array, in the traversal process, the current tunnel node is recorded as Nodei, if the number of relationLines of Nodei is less than 3, Nodei is only used to build a tunnel segment model, otherwise Nodei needs to build a turning point model and a tunnel segment model; traverse the associated line segment Linej of each node Nodei in the tunnel node array used to generate the turning point model, if Nodei is the starting point of Linej, and the number of line segments associated with the terminal point of Linej is greater than 2, the starting point and the terminal point of Linej are calculated by cutting a specified distance in the opposite direction respectively, which are used to build a new tunnel segment model and saved to the tunnel segment array TunnelLines, and the vertex calculated from the starting point or the terminal point is used to build a turning point model; if Nodei is the terminal point of Linej, and the number of line segments associated with the starting point of Linej is greater than 2, the starting point and the terminal point of Linej are calculated by cutting a specified distance in the opposite direction respectively, which are used to build a new tunnel segment model and saved to the tunnel segment array TunnelLines, and the vertex calculated from the starting point or the terminal point is used to build a turning point model;
[0016] S42, calculate the tunnel starting point and terminal section contour line using the starting point and terminal point of the line segment and the section information respectively, then connect the starting point and terminal contour line to form a closed polygon, use the polygon triangulation algorithm to build a triangular mesh model, save the model to array 1, at the same time, build a closed body model greater than the section size at the starting point and terminal point of the line segment according to the section information, save it to array 2, traverse the model in array 1, and take the model with index 0 as the reference, and perform a three-dimensional Boolean operation with the subsequent index model, the new model after each traversal processing is taken as the reference model for subsequent traversal model calculation, and the model after traversal is recorded as Model1; take Model1 as the reference, and perform a three-dimensional Boolean operation difference calculation on each model in array 2, and take the model after each traversal processing as the reference for subsequent traversal model calculation;
[0017] S43, specify that each tunnel is divided into upper, lower, left and right four parts, which are marked with additional attributes in the geometric data to distinguish different parts of the tunnel, traverse the relationLines and TunnelLines arrays used to build tunnel segment model nodes, first calculate the starting point and terminal section contour line of the four parts of the tunnel using the starting point and terminal point of the tunnel segment and the section information respectively, then connect the starting point and terminal contour line of the four parts to form a closed polygon, use the polygon triangulation algorithm to build a triangular mesh model, and finally merge the triangular mesh data of the four parts to form an entity model of each tunnel segment;
[0018] S44, the entity model is optimized, the model optimization strategy comprises three parts of geometric object merging, vertex data compression and texture compression, texture information of all inflection point models and roadway section model geometric data is traversed, geometric object merging processing of the same texture value is specified, and the merging process is that vertex coordinates and additional attribute arrays of geometric data of the same material are respectively merged into new arrays, which are used for constructing new geometric objects, the new geometric objects can maintain the original model shape, and the roadway network model data is formed.
[0019] Compared with the prior art, the technical scheme has the following beneficial effects: the method solves the problems of difficulty in multi-source data fusion, long visual attribute adjustment period, long model updating period and high cost in traditional roadway modeling, and is applied to the field of mine engineering digital design and three-dimensional modeling technology, and remarkable effects are achieved in intelligent mine construction. BRIEF DESCRIPTION OF DRAWINGS
[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute a part of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of the provided drawings.
[0021] Figure 1 The method for constructing the mine roadway parametric entity model according to the present application is shown in the following flow chart.
[0022] Figure 2 The automatic construction process of the roadway entity model according to the present application is shown in the following schematic diagram. DETAILED DESCRIPTION
[0023] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.
[0024] The embodiment of the present application discloses a method for constructing a mine roadway parametric entity model, as shown in the following figure, comprising the following steps: Figure 1
[0025] S1, obtaining modeling data for mine roadway entity modeling;
[0026] S2, configuring automatic modeling parameters of the modeling data;
[0027] S3, pre-processing the modeling data, including coordinate conversion and roadway splitting;
[0028] S4, automatically constructing roadway entity modeling based on the pre-processed modeling data.
[0029] Further, S1 is specifically: obtaining the geometric data of the roadway, including the roadway center line and the cross section information, the information extracted by the roadway center line is the spatial coordinates at the inflection point of the roadway center line, and the extracted data is constructed into a coordinate system according to the actual spatial position of the roadway and saved as a geographic information spatial data format; the cross section shape information includes the shape and size of the cross section.
[0030] In the embodiment of the application, the roadway center line can be extracted according to the roadway design drawing or the measurement data in the CAD (computer aided design) software, and the cross section shape information can be extracted according to the roadway cross section design drawing and recorded as a text file according to the roadway name.
[0031] Further, the automatic modeling parameters in S2 include roadway center line data, cross section information and self-defined roadway wall thickness, roadway texture data, and curve segmentation number parameters of circular and arched cross section roadways; when the roadway wall thickness parameter is greater than 0, a double-layer roadway is constructed, otherwise a single-layer roadway; the texture data of the roadway includes the inner and outer textures of the roadway, which is used for distinguishing the inside and outside of the roadway; the curve segmentation number of the circular and arched cross section roadways is used to control the fineness of the curved surface model.
[0032] Further, the coordinate conversion in S3 is specifically: checking whether the coordinate systems of all roadway center line data are consistent, if not, converting through the conversion parameters between the coordinate systems, unifying to the same coordinate system, then calculating the bounding box using all the roadway center line vertex coordinates after the unified coordinate system, obtaining the bounding box center point coordinates, traversing the center line vertex coordinates and the bounding box center point coordinates to calculate the local coordinates of the center line and save them.
[0033] Further, the tunnel splitting in S3 is specifically: traversing all the vertex coordinates of the tunnel center line, splitting the tunnel center line into point and line data structures according to the rule that two points constitute a line, and removing duplicate points in the splitting process by using the rule that the distance between two points is 0 to ensure the unique correspondence of points and lines; the point represents a tunnel node TunnelNode, and the line represents a tunnel segment TunnelLine; the data structure of the point records a unique number pid, a line segment relationLines associated therewith, and a point coordinate; the data structure of the line segment records a unique number lid, a start point startPoint and an end point endPoint of the line segment, tunnel texture data textures, section information sectionInfo, tunnel wall thickness thickness, and a curved surface segmentation number segment; the split points are stored in a tunnel node array, and the line data is stored in the relationLines array of the point data.
[0034] Further, S4 is specifically:
[0035] S41, traversing the tunnel node array, and in the traversal process, the current tunnel node is recorded as Nodei; if the number of relationLines of Nodei is less than 3, Nodei is only used to construct a tunnel segment model, otherwise Nodei needs to construct both a corner point model and a tunnel segment model; traversing each node Nodei in the tunnel node array used to generate a corner point model, if Nodei is the start point of Linej, and the number of line segments associated with the end point of Linej is greater than 2, the start point and the end point of Linej are respectively taken as the starting points and the new start point and the new end point are calculated by cutting a specified distance in the opposite direction, which are used to construct a new tunnel segment model and saved to a tunnel segment array TunnelLines, and the start point or the end point to the newly calculated vertex is used to construct a corner point model; if Nodei is the end point of Linej, and the number of line segments associated with the start point of Linej is greater than 2, the start point and the end point of Linej are respectively taken as the starting points and the new start point and the new end point are calculated by cutting a specified distance in the opposite direction, which are used to construct a new tunnel segment model and saved to a tunnel segment array TunnelLines, and the start point or the end point to the newly calculated vertex is used to construct a corner point model;
[0036] In the embodiment of the application, the specified distance can be calculated by multiplying the maximum section size value of the tunnel by 1.1;
[0037] S42, respectively, using the starting point and end point of the line segment and section information to calculate the starting point, end section contour line of the roadway, and then connect the starting point and end contour line to form a closed polygon, and the polygon triangulation algorithm is used for triangular mesh model construction, the model is saved to array 1, and a closed body model greater than the section size is constructed at the starting point and end point of the line segment according to the section information, and saved to array 2, the model in array 1 is traversed, and the model with index 0 as the reference is used for three-dimensional Boolean operation set processing with subsequent index models, the new model after each traversal processing is used as the reference model for subsequent traversal model calculation, and the model after traversal is recorded as Model1; Model1 is used as the reference, and three-dimensional Boolean operation difference calculation is performed on each model in array 2, and the model after each traversal processing is used as the reference for subsequent traversal model calculation;
[0038] S43, each roadway is divided into four parts, namely upper, lower, left and right, and the additional attributes are used in the geometric data to mark and distinguish different parts of the roadway, and the relationLines and TunnelLines arrays used only for constructing roadway segment model nodes are traversed, the starting point and end section contour line of the four parts of the roadway are calculated using the starting point and end point of the roadway segment and the section information, then the starting point and end contour line of the four parts are connected to form a closed polygon, and the polygon triangulation algorithm is used for triangular mesh model construction to form the model of the roadway segment, and finally the triangular mesh data of the four parts is merged to form the entity model of each roadway segment;
[0039] S44, the entity model is optimized, and the model optimization strategy includes three parts of geometric object merging, vertex data compression and texture compression, the texture information of all vertex models and roadway segment model geometric data is traversed, the same texture value is specified for the geometric object merging process, the vertex coordinates and additional attribute arrays of the same material geometric data are merged into new arrays for constructing new geometric objects, the new geometric objects can maintain the original model shape, and the roadway network model data is formed.
[0040] In the embodiment of the application, the vertex data compression uses the draco compression algorithm, and the compressed data further reduces the size of the model file; the texture compression adopts the ktx2 compression format, which can be directly recognized by the GPU and can speed up the texture data analysis speed. The optimized model data can reduce the number of geometric objects, reduce the number of rendering commands, improve the rendering performance, on the other hand, through vertex compression and texture compression, the model file size is reduced, the transmission performance of the model data and the texture data interpretation speed are improved, so as to improve the rendering performance of the roadway entity model as a whole.
[0041] The various embodiments described herein are presented by way of example only and are not intended as a limitation on the scope of the disclosure. As those skilled in the art will understand, the principles and operation of the present disclosure can be applied using any number of other embodiments as well and each of the various embodiments presented herein can include modifications that fall within the scope of the disclosure.
[0042] Many modifications and variations of this application can be made in light of the above teachings. It is, therefore, to be understood that within the scope of the disclosure the application can be practiced otherwise than as specifically described. The present application includes all modifications and variations of this application that fall within the scope of the appended claims and equivalents.
Claims
1. A mine tunnel parameterized entity model construction method, characterized in that, The method comprises the following steps: S1, obtaining modeling data for mine roadway entity modeling; S2, configuring automatic modeling parameters of the modeling data; S3, preprocessing the modeling data, including coordinate conversion and roadway splitting; S4, automatically constructing roadway entity modeling based on the preprocessed modeling data.
2. The mine laneway parameterized entity model construction method according to claim 1, characterized in that, S1 is specifically: obtaining the geometric data of the roadway, including the roadway center line and section information, the information extracted from the roadway center line being the spatial coordinates at the inflection points of the roadway center line, the extracted data being constructed into a coordinate system according to the actual spatial position of the roadway and saved in a geographic information spatial data format; the section shape information including the shape and size of the section.
3. The mine laneway parameterized entity model construction method according to claim 1, characterized in that, The automatic modeling parameters in S2 include roadway center line data, section information, and custom roadway wall thickness, roadway texture data, and curve segmentation number parameters of circular and arched section roadways; when the roadway wall thickness parameter is greater than 0, a double-layer roadway is constructed, otherwise a single-layer roadway; the texture data of the roadway includes the inner and outer textures of the roadway, which are used to distinguish the inside and outside of the roadway; the curve segmentation number of circular and arched section roadways is used to control the fineness of the curved surface model.
4. The mine laneway parameterized entity model construction method according to claim 1, characterized in that, The coordinate conversion in S3 is specifically: checking whether the coordinate systems of all roadway center line data are consistent, if not, converting through the conversion parameters between the coordinate systems, unifying to the same coordinate system, then calculating the bounding box using all the vertex coordinates of the roadway center line after unifying the coordinate system, obtaining the bounding box center point coordinates, and traversing the center line vertex coordinates and the bounding box center point coordinates to calculate the local coordinates of the center line and save them.
5. The mine laneway parameterized entity model construction method according to claim 1, characterized in that, The roadway splitting in S3 is specifically: traversing all the vertex coordinates of the roadway center line, splitting the roadway center line into point and line data structures according to the rule that two points form a line, and removing duplicate points in the splitting process by using the rule that the distance between two points is 0 to ensure the unique correspondence of points and lines; the point represents a tunnel node TunnelNode, the line represents a tunnel segment TunnelLine, the point data structure records the unique number pid, the associated line segment relationLines and the point coordinate, the line segment data structure records the unique number lid, the start point startPoint and the end point endPoint of the line segment, the roadway texture data textures, the section information sectionInfo, the roadway wall thickness thickness, and the curve segmentation number segment; the split points are stored in the roadway node array, and the line data are stored in the relationLines array of the point data.
6. The mine laneway parameterized entity model construction method according to claim 1, characterized in that, S4 is specifically: S41, traverse the tunnel node array, in the traversal process, the current tunnel node is recorded as Nodei, if the number of relationLines of Nodei is less than 3, Nodei is only used to build a tunnel segment model, otherwise Nodei needs to build a turning point model and a tunnel segment model; traverse the associated line segment Linej of each node Nodei in the tunnel node array used to generate the turning point model, if Nodei is the starting point of Linej, and the number of line segments associated with the terminal point of Linej is greater than 2, the new starting point and terminal point are calculated by cutting a specified distance in the opposite direction with the starting point and terminal point of Linej as the starting point respectively, which is used to newly build a tunnel segment model and saved to the tunnel segment array TunnelLines, and the vertex calculated from the starting point or terminal point to the new vertex is used to build a turning point model; if Nodei is the terminal point of Linej, and the number of line segments associated with the starting point of Linej is greater than 2, the new starting point and terminal point are calculated by cutting a specified distance in the opposite direction with the starting point and terminal point of Linej as the starting point respectively, which is used to newly build a tunnel segment model and saved to the tunnel segment array TunnelLines, and the vertex calculated from the starting point or terminal point to the new vertex is used to build a turning point model; S42, calculate the starting point and terminal section contour lines of the tunnel using the starting point and terminal point of the line segment and the section information respectively, then connect the starting point and terminal contour lines of each part to form a closed polygon, use the polygon triangulation algorithm to build a triangular mesh model, save the model to array 1, at the same time, build a closed body model greater than the section size at the starting point and terminal point of the line segment according to the section information, save it to array 2, traverse the model in array 1, and take the model with index 0 as the reference, and perform a three-dimensional Boolean operation with the subsequent index model, the new model after each traversal processing is taken as the reference model for subsequent traversal model calculation, and the model after traversal is recorded as Model1; Take Model1 as the reference, and perform a three-dimensional Boolean operation difference calculation on each model in array 2, and take the model after each traversal processing as the reference for subsequent traversal model calculation; S43, specify that each tunnel is divided into upper, lower, left and right four parts, mark them in the geometric data using additional attributes to distinguish different parts of the tunnel, traverse the relationLines and TunnelLines arrays used to build tunnel segment model nodes, first calculate the starting point and terminal section contour lines of the four parts of the tunnel using the starting point and terminal point of the tunnel segment and the section information respectively, then connect the starting point and terminal contour lines of each part to form a closed polygon, use the polygon triangulation algorithm to build a triangular mesh model, and finally merge the triangular mesh data of the four parts to form the entity model of each tunnel segment; S44, entity model optimization, model optimization strategy includes three parts of geometric object merging, vertex data compression and texture compression, traversing all the corner point model and roadway segment model geometry data texture information, specifying the same texture value of geometric object merging processing, merging process is to merge the same material geometric data vertex coordinates, additional attribute array respectively into new array, used to build new geometric object, new geometric object can maintain the original model shape, form roadway network model data.