A Mixed Reality Mine Ventilation Data Visualization Method

Abstract

This application belongs to the field of mine ventilation visualization technology, specifically providing a mixed reality mine ventilation data visualization method. The method mainly includes: acquiring an original ventilation dataset; performing spatial association processing on the original ventilation dataset to generate a primary bound dataset; performing topology modeling processing on the primary bound dataset to generate a remapped ventilation dataset; performing visualization processing on the dynamic parameters in the remapped ventilation dataset to generate an engineering visualization element set; and finally generating an updated primary fusion scene. This application can intuitively present the spatial relationships and real-time changing trends of ventilation elements, eliminating information lag and helping managers quickly obtain comprehensive and dynamic ventilation system operating status. It provides immediate and accurate data support for ventilation optimization and risk prediction, significantly improving the response speed and scientific decision-making of mine safety production management.

Description

Technical Field

[0001] This application belongs to the field of mine ventilation visualization technology, and specifically relates to a mixed reality mine ventilation data visualization method. Background Technology

[0002] In the field of mine ventilation management, the traditional data processing method is to collect raw ventilation data such as wind speed, wind pressure, and gas concentration separately, and then display them simply through two-dimensional charts or static models.

[0003] Traditional methods of processing mine ventilation data separate the data from the mine's spatial environment, failing to intuitively present the spatial relationships and dynamic connections between various elements of the ventilation system. When ventilation data changes, the relevant visualization content cannot be updated in a timely manner, resulting in data lag. Managers find it difficult to quickly and comprehensively grasp the operational status of the mine ventilation system, lacking effective data support for ventilation system optimization and risk prediction, which is detrimental to ensuring safe production and efficient management in the mine. Summary of the Invention

[0004] This application provides a mixed reality method for visualizing mine ventilation data. It effectively solves the problem in existing technologies that separate data from the mine's spatial environment, making it difficult for managers to quickly and comprehensively grasp the operational status of the mine ventilation system. This lack of effective data support hinders ventilation system optimization and risk prediction, which is detrimental to ensuring safe production and efficient management in the mine. The method can intuitively present the spatial relationships and real-time trends of ventilation elements, eliminate information lag, and help managers quickly obtain a comprehensive and dynamic view of the ventilation system's operational status, providing timely and accurate data support for ventilation optimization and risk prediction.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] Firstly, this application provides a mixed reality mine ventilation data visualization method, including:

[0007] Obtain the raw ventilation dataset.

[0008] Spatial association processing is performed on the original ventilation dataset to generate a primary binding dataset.

[0009] Perform topology modeling processing based on the primary binding dataset to generate a remapped ventilation dataset.

[0010] Visualization processing is performed based on the dynamic parameters in the remapped ventilation dataset to generate a set of engineering visualization elements.

[0011] Perform mixed reality fusion processing based on the spatial model and engineering visualization element set in the remapped ventilation dataset to generate a preliminary fusion scene.

[0012] In response to changes in the original ventilation dataset, a linked update process is performed to refresh the primary bound dataset, remap the ventilation dataset, and the engineering visualization element set, generating an updated primary fusion scene.

[0013] Furthermore, the original ventilation dataset includes: the original segmented air volume set, the original segmented resistance set, and the original roadway key coordinate set.

[0014] Further, spatial association processing is performed on the original ventilation dataset to generate a primary binding dataset, including:

[0015] A set of roadway connection lines is generated based on the original set of key roadway coordinates.

[0016] The original segmented air volume set is associated with the roadway connection line set through segment numbering to obtain the coordinate-bound air volume set.

[0017] The original segmented resistance set is associated with the roadway connection line set through segment numbering to obtain the coordinate-bound resistance set.

[0018] Generate a primary bound dataset containing coordinate-bound airflow and coordinate-bound resistance sets.

[0019] Further, a set of tunnel connection lines is generated based on the original key coordinate set of the tunnels, including:

[0020] Extract the sequence of roadway intersections from the original roadway key coordinate set.

[0021] Traverse the sequence of roadway intersections and connect each intersection to its next topologically adjacent intersection.

[0022] Each connected line segment is assigned a unique segment number.

[0023] Generate a set of lane connection lines containing all line segments between adjacent intersections.

[0024] Further, topology modeling processing is performed based on the primary binding dataset to generate a remapped ventilation dataset, including:

[0025] By uniformly inserting dividing points into each connecting line in the set of roadway connecting lines, a subdivision point sequence is obtained.

[0026] Connect all points in the subdivided point sequence to obtain a high-precision tunnel line model.

[0027] Based on the coordinate-bound air volume set, air volume interpolation calculation is performed on each point in the subdivided point sequence to obtain air volume linear density data.

[0028] The average resistance of each connecting line in the roadway connecting line set is calculated based on the coordinate-bound resistance set to obtain the average resistance data of the sub-lines.

[0029] Based on the average value of the resistance data, resistance levels are divided, and resistance level labels are obtained.

[0030] The output includes a high-precision roadway line model, air volume linear density data, mean data of branch resistance, and a remapped ventilation dataset with branch resistance level labels.

[0031] Furthermore, visualization processing is performed based on the dynamic parameters in the remapped ventilation dataset to generate an engineering visualization element set, including:

[0032] A gradually changing pipe diameter model is generated based on the air volume linear density data to obtain a visualized air volume pipeline.

[0033] Based on the resistance level label of the branch line, a warning graphic is generated on the connecting line of the roadway connection line set to obtain a graded resistance warning body.

[0034] Furthermore, based on the spatial model and engineering visualization element set in the remapped ventilation dataset, mixed reality fusion processing is performed to generate a preliminary fusion scene, including:

[0035] By binding the visualized air volume pipeline to the position of the subdivided point sequence, a pipeline overlay scene is obtained; the graded resistance warning body is located at the midpoint of the concentrated connection line of the roadway connection line.

[0036] By merging the pipeline overlay scene with the high-precision tunnel line model, a primary fused scene is obtained.

[0037] Furthermore, by fusing the pipeline overlay scene with the high-precision tunnel line model, a preliminary fused scene is obtained, including:

[0038] The corresponding line segments of the high-precision roadway line model are marked with the level of the resistance level label of the branch line to generate a resistance marking model.

[0039] Based on the marking results of the resistance marking model, the length of the high-resistance segment is extended according to the numerical proportion of the airflow linear density data to generate an airflow resistance deformation model.

[0040] By applying the path coordinates of the airflow resistance deformation model, the vertex distribution of the visualized airflow pipeline in the pipeline overlay scenario is adjusted to generate a deformation-adapted pipeline.

[0041] Based on the path distribution of the deformation-adaptive pipeline, the coordinates of the midpoint of the connecting line of the roadway connection line set are recalculated, and the graded resistance warning body is located at these coordinates.

[0042] The process involves sequentially drawing the airflow resistance deformation model, overlaying the deformation-adapted pipeline, and overlaying the positioned graded resistance warning body to generate a primary fusion scene.

[0043] Furthermore, in response to changes in the original ventilation dataset, a linked update process is performed to refresh the primary bound dataset, remap the ventilation dataset, and the engineering visualization element set, generating an updated primary fusion scene, including:

[0044] Monitor the numerical changes of the original segmented air volume set and the original segmented resistance set.

[0045] When the original segmented air volume set changes: update the coordinate binding air volume set; recalculate the air volume linear density data; refresh the air volume visualization pipeline.

[0046] When the original segmented resistance set changes: update the coordinate-bound resistance set; recalculate the average resistance data of the segmented lines; update the resistance level labels of the segmented lines; refresh the graded resistance warning body.

[0047] The pipeline overlay scene and the high-precision tunnel line model are re-integrated to obtain an updated primary fused scene.

[0048] Secondly, this application provides a mixed reality mine ventilation data visualization system, which includes:

[0049] Raw data acquisition module: Acquires raw ventilation dataset.

[0050] Spatial Association Binding Module: Performs spatial association processing on the original ventilation dataset to generate a primary binding dataset.

[0051] Topology modeling and mapping module: Performs topology modeling processing based on the primary binding dataset to generate a remapped ventilation dataset.

[0052] Dynamic visualization generation module: Performs visualization processing based on the dynamic parameters in the remapped ventilation dataset to generate a set of engineering visualization elements.

[0053] Mixed Reality Fusion Module: Performs mixed reality fusion processing based on the spatial model and engineering visualization element set in the remapped ventilation dataset to generate a primary fusion scene.

[0054] Data linkage update module: In response to changes in the original ventilation dataset, it performs linkage update processing to refresh the primary bound dataset, remap the ventilation dataset, and the engineering visualization element set, generating an updated primary fusion scene.

[0055] Thirdly, this application provides a mixed reality mine ventilation data visualization device, which includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program to implement the steps of the mixed reality mine ventilation data visualization method as described in the first aspect.

[0056] Fourthly, this application provides a storage medium storing computer program instructions, which are read and executed by a processor to perform the steps of the mixed reality mine ventilation data visualization method described in the first aspect.

[0057] The beneficial effects of this application are:

[0058] This application constructs a data-mine spatial environment linkage system, integrating ventilation data into a spatial topology model. Using mixed reality technology, it dynamically presents the spatial distribution and logical relationships of ventilation elements. Simultaneously, a linked update mechanism ensures that the visualized content reflects data changes in real time. This effectively solves the problem in existing technologies where data is separated from the mine spatial environment, making it difficult for managers to quickly and comprehensively grasp the operational status of the mine ventilation system. This lack of effective data support hinders ventilation system optimization and risk prediction, negatively impacting mine safety production and efficient management. The application intuitively presents the spatial relationships and real-time trends of ventilation elements, eliminating information lag and helping managers quickly obtain comprehensive and dynamic ventilation system operational status. This provides immediate and accurate data support for ventilation optimization and risk prediction, significantly improving the response speed and scientific basis of mine safety production management.

[0059] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description and the accompanying drawings. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0061] Figure 1 A schematic diagram of a mixed reality mine ventilation data visualization method according to this application is shown. Detailed Implementation

[0062] To address the problems raised in the background technology, this application constructs a data-mine spatial environment linkage system, integrates ventilation data into a spatial topology model, and uses mixed reality technology to dynamically present the spatial distribution and logical relationships of ventilation elements. At the same time, a linkage update mechanism ensures that the visualized content reflects data changes in real time, which can intuitively present the spatial relationships and real-time trends of ventilation elements, eliminate information lag, help managers quickly obtain comprehensive and dynamic ventilation system operation status, and provide timely and accurate data support for ventilation optimization and risk prediction.

[0063] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0064] In some embodiments, such as Figure 1 As shown, this application provides a mixed reality mine ventilation data visualization method, including:

[0065] S1. Obtain the original ventilation dataset.

[0066] S2. Perform spatial association processing on the original ventilation dataset to generate a primary binding dataset.

[0067] S3. Perform topology modeling processing based on the primary binding dataset to generate a remapped ventilation dataset.

[0068] S4. Perform visualization processing based on the dynamic parameters in the remapped ventilation dataset to generate an engineering visualization element set.

[0069] S5. Perform mixed reality fusion processing based on the spatial model and engineering visualization element set in the remapped ventilation dataset to generate a primary fusion scene.

[0070] S6. In response to changes in the original ventilation dataset, perform a linked update process to refresh the primary bound dataset, remap the ventilation dataset, and the engineering visualization element set, generating an updated primary fusion scene.

[0071] In some embodiments, the original ventilation dataset includes: an original segmented air volume set, an original segmented resistance set, and an original roadway key coordinate set.

[0072] The original segmented air volume set represents the set of measured air volume data for each ventilation segment underground. The original segmented resistance set records the frictional resistance coefficient and local resistance coefficient of each ventilation segment. The topological key points in the three-dimensional point cloud of the roadway include intersections, turning points, and branch points.

[0073] In some embodiments, spatial association processing is performed on the original ventilation dataset to generate a primary binding dataset, including:

[0074] S21. Generate a set of roadway connection lines based on the original roadway key coordinate set.

[0075] The lane connection set contains the line segments between all adjacent intersections.

[0076] S22. Associate the original segmented air volume set with the roadway connection line set through segment numbering to obtain a coordinate-bound air volume set.

[0077] By traversing each segment of the tunnel connection line set and extracting its original segment number field, the air volume value with the same segment number can be found in the original segment air volume set.

[0078] S23. Associate the original segmented resistance set with the roadway connection line set through segment numbering to obtain a coordinate-bound resistance set.

[0079] The frictional resistance coefficient and local resistance coefficient of the original segmented resistance concentration are combined into an equivalent resistance value: ,in, Represents the coefficient of frictional resistance. Represents the local drag coefficient. This represents the length of the line segment.

[0080] S24. Generate a primary bound dataset containing coordinate-bound airflow sets and coordinate-bound resistance sets.

[0081] In some embodiments, S21 generates a set of tunnel connection lines based on the original tunnel key coordinate set, including:

[0082] S211. Extract the sequence of roadway intersections from the original roadway key coordinate set.

[0083] The original key coordinate set of the tunnel includes segment number, coordinate type (e.g., 0 represents the starting point, 1 represents the ending point), and three-dimensional coordinates (X, Y, Z).

[0084] Lane intersections represent lane topology connection nodes. Multiple segment records of the same physical point can be aggregated according to spatial location; for example, if the coordinates (285.73, 143.26, -356.8) are marked as intersections in all three segments, they are merged into a single node.

[0085] The sequence of roadway intersections includes node IDs and coordinates.

[0086] S212. Traverse the sequence of roadway intersections and connect each intersection to its next topologically adjacent intersection.

[0087] Construct a topology mapping table, which includes the current node and a list of neighboring nodes. Traverse each node and connect it to any unprocessed nodes in the list of neighboring nodes.

[0088] S213. Assign a unique segment number to each line segment formed by the connection.

[0089] For example, the encoded data structure generated for each line segment can be: start point ID, end point ID, and hash value.

[0090] S214. Generate a set of lane connection lines containing all line segments between adjacent intersections.

[0091] In some embodiments, S3 performs topology modeling processing based on the primary binding dataset to generate a remapped ventilation dataset, including:

[0092] S31. Insert dividing points evenly into each connecting line in the set of roadway connecting lines to obtain a subdivision point sequence.

[0093] Calculate the length L of the connecting line, and insert the dividing points evenly at fixed intervals. The dividing points can be determined based on the minimum bending radius of the tunnel.

[0094] Obtain the point sequence for each connecting line, including the starting point, ending point, and dividing point.

[0095] S32. Connect all points in the subdivided point sequence to obtain a high-precision tunnel line model.

[0096] Connect the dividing points within the same connecting line in topological order to form a continuous polyline. At the intersection of the tunnels, merge the endpoints of adjacent connecting lines. If there is a large height difference between adjacent points, smoothing can be performed to obtain a seamless 3D tunnel wireframe model.

[0097] S33. Based on the coordinate-bound air volume set, perform air volume interpolation calculation on each point in the subdivided point sequence to obtain air volume linear density data.

[0098] Within a single line segment, all points inherit the air volume value of that line segment as the air volume linear density data. For line segment connection points (intersections), the arithmetic mean of the air volume values ​​of adjacent line segments is taken as the air volume linear density data.

[0099] S34. Calculate the average resistance of each connecting line in the roadway connecting line set based on the coordinate-bound resistance set to obtain the average resistance data of the sub-lines.

[0100] The equivalent resistance value of the bonded resistance concentration can be directly obtained. The average resistance of this connecting line is marked as the average resistance data of the branch line.

[0101] S35. Divide the resistance levels according to the average value in the average resistance data of the sub-line and obtain the sub-line resistance level label.

[0102] A set of resistance level labels for each connecting line is provided to visually represent the ventilation resistance status of the tunnel.

[0103] For example, resistance values ​​≤ 0.003 can be marked as Class I low resistance, resistance values ​​between 0.003 and 0.006 can be marked as Class II medium resistance, and resistance values ​​> 0.006 can be marked as Class III high resistance.

[0104] S36. The output includes a high-precision roadway line model, air volume linear density data, mean data of branch resistance, and a remapped ventilation dataset with branch resistance level labels.

[0105] In some embodiments, S4 performs visualization processing based on the dynamic parameters in the remapped ventilation dataset to generate an engineering visualization element set, including:

[0106] S41. Generate a gradually changing pipe diameter model based on the air volume linear density data to obtain a visualized air volume pipeline.

[0107] Based on the airflow linear density value of each subdivision point, the pipeline radius at the corresponding location is dynamically calculated. The airflow linear density value is directly proportional to the pipeline radius, that is, the higher the density, the larger the radius. A smoothly transitioning gradual pipeline diameter model is generated between adjacent points and marked as an airflow visualization pipeline.

[0108] S42. Based on the resistance level label of the branch line, generate a warning graphic on the connecting line of the roadway connection line set to obtain a graded resistance warning body.

[0109] For example, the Level I low resistance setting is indicated by a green circular symbol; the Level II medium resistance setting is indicated by a yellow triangle symbol; and the Level III high resistance setting is indicated by a red exclamation mark.

[0110] In some embodiments, S5 performs mixed reality fusion processing based on the spatial model and engineering visualization element set in the remapped ventilation dataset to generate a primary fusion scene, including:

[0111] S51. Bind the air volume visualization pipeline to the position of the subdivided point sequence to obtain the pipeline overlay scene; locate the graded resistance warning body to the midpoint of the concentrated connection line of the roadway connection line.

[0112] A one-to-one correspondence is established between the vertices of each pipe segment of the visualized airflow pipeline and the coordinates of the subdivision point sequence. The vertex positions of the pipe diameter model are adjusted based on the three-dimensional coordinate values ​​of the subdivision point sequence to obtain the pipeline overlay scene.

[0113] For each connecting line of the roadway connection line, calculate the three-dimensional midpoint by taking the coordinates of the starting point and the ending point, and align the spatial center point of the graded resistance warning body to the calculated midpoint coordinates.

[0114] S52. The pipeline overlay scene and the high-precision tunnel line model are merged to obtain the primary fused scene.

[0115] In some embodiments, S52 fuses the pipeline overlay scene and the high-precision tunnel line model to obtain a primary fused scene, including:

[0116] S521. Apply the gear level label of the described resistance gear level to mark the corresponding line segment of the high-precision roadway line model to generate a resistance marking model.

[0117] For example, the Class III high-resistance line segment is marked with a thick red solid line, and the line width is extended to 200% of the base value. The Class II medium-resistance line segment is marked with a yellow center line, and the line width is extended to 150% of the base value. The Class I low-resistance line segment retains the default line width, thus obtaining the resistance marking model.

[0118] S522. Based on the marking results of the resistance marking model, the length of the high resistance level line segment is extended according to the numerical ratio of the air volume linear density data to generate an air volume resistance deformation model.

[0119] Calculate the deformation ratio of the high-resistance line segment using the formula: ;in, This represents the proportion of line segment length expansion, and k represents the deformation coefficient, such as 0.8. This represents the average linear density of airflow in the current line segment.

[0120] S523. Apply the path coordinates of the airflow resistance deformation model to adjust the vertex distribution of the visualized airflow pipeline in the pipeline overlay scene, and generate deformation-adapted pipelines.

[0121] Extracting the vertex coordinate sequence of the deformation model The vertex coordinates of the original pipeline model arrive Relocate to the corresponding vertex arrive By maintaining the gradual change characteristics of the pipe diameter, a deformation-adaptive pipeline is obtained.

[0122] S524. Based on the path distribution of the deformation-adaptive pipeline, recalculate the coordinates of the midpoint of the connecting line of the roadway connecting line set, and locate the graded resistance warning body to the coordinates.

[0123] Calculate the coordinates of the midpoint of the deformed line segment Precisely align the center point of the graded resistance warning body with The coordinates are used to obtain the graded resistance warning body after positioning is completed.

[0124] S525. Sequentially execute the following steps: draw the airflow resistance deformation model, overlay the deformation-adapted pipeline, and overlay the positioned graded resistance warning body to generate a primary fusion scene.

[0125] In some embodiments, in response to changes in the original ventilation dataset, step S6 performs a linked update process to refresh the primary bound dataset, remap the ventilation dataset, and the engineering visualization element set, generating an updated primary fusion scene, including:

[0126] S61. Monitor the numerical changes of the original segmented air volume set and the original segmented resistance set.

[0127] Continuously monitor the numerical changes of the original segmented airflow set and the original segmented resistance set. Specifically, this includes the following operations: monitoring the airflow value changes of each segment in the original segmented airflow set; when the airflow value change is greater than or equal to 0.1... The change is deemed valid upon verification; simultaneously, the resistance value of each segment in the original segmented resistance concentration is monitored, and when the resistance value change is greater than or equal to 0.001... The change is deemed valid at that time.

[0128] S62. When the original segmented air volume set changes: update the coordinate binding air volume set; recalculate the air volume linear density data; refresh the air volume visualization pipeline.

[0129] The coordinate binding airflow set is updated by reassociating the changed airflow values ​​with the corresponding spatial coordinate positions according to the segment numbers; then the airflow linear density data is recalculated by interpolating the new airflow values ​​to obtain new airflow linear density values; finally, the airflow visualization pipeline is refreshed by regenerating the gradient pipe diameter model based on the new airflow linear density values, resulting in the updated airflow visualization pipeline that accurately reflects the latest airflow distribution.

[0130] S63. When the original segmented resistance set changes: update the coordinate-bound resistance set; recalculate the average resistance data of the segmented lines; update the resistance level labels of the segmented lines; refresh the graded resistance warning body.

[0131] The coordinate binding resistance set is updated, and the changed resistance value is re-associated with the spatial coordinates; then the average resistance data of the sub-line is recalculated to obtain a new average resistance value; next, the sub-line resistance level label is updated, and the level I low resistance, level II medium resistance, or level III high resistance level is reclassified according to the new resistance value; the graded resistance warning body is refreshed, and the warning graphic is repositioned at the midpoint of the tunnel connection line; finally, the updated graded resistance warning body is obtained, which can accurately mark the latest resistance anomaly location.

[0132] S64. Re-integrate the pipeline overlay scene with the high-precision tunnel line model to obtain an updated primary fused scene.

[0133] The pipeline overlay scene is re-integrated with the high-precision roadway line model. Specifically, this involves precisely aligning the pipeline vertices with the roadway vertices; then verifying whether the spatial position deviation is less than a specified value, such as 0.05 meters; and finally updating the scene rendering to generate the latest visualization effect, ultimately obtaining an updated primary fused scene that can reflect the latest status of the mine ventilation system in real time.

[0134] In some embodiments, this application provides a mixed reality mine ventilation data visualization system, which includes:

[0135] Raw data acquisition module: Acquires raw ventilation dataset.

[0136] Spatial Association Binding Module: Performs spatial association processing on the original ventilation dataset to generate a primary binding dataset.

[0137] Topology modeling and mapping module: Performs topology modeling processing based on the primary binding dataset to generate a remapped ventilation dataset.

[0138] Dynamic visualization generation module: Performs visualization processing based on the dynamic parameters in the remapped ventilation dataset to generate a set of engineering visualization elements.

[0139] Mixed Reality Fusion Module: Performs mixed reality fusion processing based on the spatial model and engineering visualization element set in the remapped ventilation dataset to generate a primary fusion scene.

[0140] Data linkage update module: In response to changes in the original ventilation dataset, it performs linkage update processing to refresh the primary bound dataset, remap the ventilation dataset, and the engineering visualization element set, generating an updated primary fusion scene.

[0141] In some embodiments, this application provides a mixed reality mine ventilation data visualization device, which includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program to implement the steps of the mixed reality mine ventilation data visualization method.

[0142] In some embodiments, this application provides a storage medium storing computer program instructions, which are read and executed by a processor to perform the steps of a mixed reality mine ventilation data visualization method.

[0143] Any references to memory, storage, database, or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0144] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0145] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A mixed reality method for visualizing mine ventilation data, characterized in that, include: Obtain the raw ventilation dataset; Spatial association processing is performed on the original ventilation dataset to generate a primary binding dataset; Perform topology modeling processing based on the primary binding dataset to generate a remapped ventilation dataset; Visualization processing is performed based on the dynamic parameters in the remapped ventilation dataset to generate a set of engineering visualization elements. Perform mixed reality fusion processing based on the spatial model and engineering visualization element set in the remapped ventilation dataset to generate a preliminary fusion scene; In response to changes in the original ventilation dataset, a linked update process is performed to refresh the primary bound dataset, remap the ventilation dataset, and the engineering visualization element set, generating an updated primary fusion scene; The original ventilation dataset includes: original segmented air volume set, original segmented resistance set, and original roadway key coordinate set; Spatial association processing is performed on the original ventilation dataset to generate a primary binding dataset, including: A set of tunnel connection lines is generated based on the original key coordinate set of the tunnels; The original segmented air volume set and the roadway connection line set are associated with each other through segment numbering to obtain a coordinate-bound air volume set; The original segmented resistance set and the roadway connection line set are associated with each other through segment numbering to obtain a coordinate-bound resistance set; Generate a primary bound dataset containing coordinate-bound airflow and coordinate-bound resistance sets.

2. The mixed reality mine ventilation data visualization method according to claim 1, characterized in that, Based on the original key coordinate set of the tunnels, a set of tunnel connection lines is generated, including: Extract the sequence of roadway intersections from the original roadway key coordinate set; Traverse the sequence of roadway intersections and connect each intersection to its next topologically adjacent intersection. Each connected line segment is assigned a unique segment number; Generate a set of lane connection lines containing all line segments between adjacent intersections.

3. The mixed reality mine ventilation data visualization method according to claim 1, characterized in that, Perform topology modeling processing based on the primary binding dataset to generate a remapped ventilation dataset, including: By uniformly inserting dividing points into each connecting line in the set of roadway connecting lines, a subdivision point sequence is obtained; Connect all points in the subdivided point sequence to obtain a high-precision tunnel line model; Based on the coordinate-bound air volume set, air volume interpolation calculation is performed on each point in the subdivided point sequence to obtain air volume linear density data; The average resistance of each connecting line in the roadway connecting line set is calculated based on the coordinate-bound resistance set to obtain the average resistance data of the sub-lines; Based on the average value of the average resistance data of the sub-line, resistance levels are divided, and sub-line resistance level labels are obtained; The output includes a high-precision roadway line model, air volume linear density data, mean data of branch resistance, and a remapped ventilation dataset with branch resistance level labels.

4. The mixed reality mine ventilation data visualization method according to claim 3, characterized in that, Visualization processing is performed based on the dynamic parameters in the remapped ventilation dataset to generate a set of engineering visualization elements, including: A gradually changing pipe diameter model is generated based on the air volume linear density data to obtain a visualized air volume pipeline. Based on the resistance level label of the branch line, a warning graphic is generated on the connecting line of the roadway connection line set to obtain a graded resistance warning body.

5. The mixed reality mine ventilation data visualization method according to claim 3, characterized in that, Based on the spatial model and engineering visualization element set in the remapped ventilation dataset, mixed reality fusion processing is performed to generate a preliminary fusion scene, including: The air volume visualization pipeline is bound to the position of the subdivided point sequence to obtain the pipeline overlay scene; the graded resistance warning body is located at the midpoint of the concentrated connection line of the roadway connection line; By merging the pipeline overlay scene with the high-precision tunnel line model, a primary fused scene is obtained.

6. The mixed reality mine ventilation data visualization method according to claim 5, characterized in that, By fusing the pipeline overlay scene with the high-precision tunnel line model, a preliminary fused scene is obtained, including: The corresponding line segments of the high-precision roadway line model are marked with the level of the resistance level label of the branch line to generate a resistance marking model. Based on the marking results of the resistance marking model, the length of the high resistance gear segment is extended according to the numerical proportion of the air volume linear density data to generate an air volume resistance deformation model. By applying the path coordinates of the airflow resistance deformation model, the vertex distribution of the visualized airflow pipeline in the pipeline overlay scenario is adjusted to generate a deformation-adapted pipeline. Based on the path distribution of the deformation-adaptive pipeline, the coordinates of the midpoint of the connecting line of the roadway connection line set are recalculated, and the graded resistance warning body is located at these coordinates. The process involves sequentially drawing the airflow resistance deformation model, overlaying the deformation-adapted pipeline, and overlaying the positioned graded resistance warning body to generate a primary fusion scene.

7. The mixed reality mine ventilation data visualization method according to claim 5, characterized in that, In response to changes in the original ventilation dataset, a linked update process is performed to refresh the primary bound dataset, remap the ventilation dataset, and the engineering visualization element set, generating an updated primary fusion scene, including: Monitor the numerical changes of the original segmented air volume set and the original segmented resistance set; When the original segmented air volume set changes: update the coordinate-bound air volume set; recalculate the air volume linear density data; refresh the air volume visualization pipeline; When the original segmented resistance set changes: update the coordinate-bound resistance set; recalculate the average resistance data of the segmented lines; update the resistance level labels of the segmented lines; refresh the graded resistance warning body; The pipeline overlay scene and the high-precision tunnel line model are re-integrated to obtain an updated primary fused scene.

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