Method for automatically drawing mine ventilation network diagram

Abstract

The invention relates to the field of mine ventilation, in particular to an automatic drawing method for a mine ventilation network diagram. Comprising the following steps: S100, performing cyclic de-duplication operation on elements of an initial node and a tail node of a directed edge set to realize longitudinal sequencing on acquired network diagram nodes; s200, traversing all nodes once from the intake shaft node to the return shaft node according to the direction of the directed graph, and calculating all paths from the intake shaft node to the return shaft node; s300, on the premise that the connectivity of the network diagram and the node topological relation are not affected, the network diagram is simplified and beautified from the two aspects of reducing the number of nodes and uniformly arranging the positions of the nodes; s400, classifying all the paths, dividing the network diagram into a plurality of sub-networks, and dividing a trunk and branches according to the sub-networks; s500, drawing a trunk and branches of the network diagram; and S600, optimizing the branch positions of the ventilation network diagram. The method solves the problem that the longest path layering algorithm cannot sort the air return shafts to the same layer.

Description

Technical Field

[0001] The invention relates to the field of mine ventilation, and in particular to a method for automatically drawing a mine ventilation network diagram. Background Art

[0002] As one of the important drawings of mine ventilation, the mine ventilation network diagram is a graphical tool for representing and analyzing the mine ventilation system. It can intuitively display the layout of various ventilation routes, wind flow directions, ventilation equipment and node tunnels in the mine, and help ventilation engineers analyze and optimize the ventilation system, which plays an important role in mine ventilation management. The "Coal Mine Safety Regulations 2022" stipulates that a three-dimensional schematic diagram of the mine ventilation system and a mine ventilation network diagram should be drawn. Therefore, designing an automatic drawing method for mine ventilation network diagrams that meets the requirements is an important content in the field of mine ventilation.

[0003] At present, the method of drawing mine ventilation network diagram is mainly manual drawing. Some people try to study the automatic generation of mine ventilation network diagram. These studies mainly focus on algorithms such as the longest path method, depth-first search method and genetic algorithm, and use quadratic functions to draw network diagrams, and conduct secondary development on software platforms such as AutoCAD, MineMap, VB, and Matlab. However, there are problems such as network diagram drawing not meeting the requirements of regulations, low drawing efficiency, and inability to draw complex network diagrams. Among them, the longest path sorting algorithm determines the node hierarchy by calculating the longest path from each node to the source node. When processing complex mine ventilation network diagrams, this method has the problem that the sorting takes a long time and the return air shaft nodes in the sorting results are not located in the same layer, making it difficult for the algorithm to play a role in practical applications. Depth-first search (DFS) needs to backtrack to find untraversed nodes, which requires repeated traversal of repeated tunnels. Therefore, it takes a long time to find all paths from the air intake shaft node to the return air shaft node in the mine ventilation network diagram. The longest path parallel method determines the branch by finding the longest path between two nodes with a large difference in the number of layers. This method does not consider the division of sub-networks and is only applicable to the drawing of simple network diagrams. When processing complex network diagrams, it will cause the network curves to be messy, affecting the clarity and readability of the graph. The genetic algorithm reduces the number of branch intersections by taking nodes as optimization objects, but when the number of nodes is too large, the time required for optimization will increase significantly. In addition, when using quadratic functions to draw network diagrams, the curvature of branches with similar layers is small. The branch curves that fork at the same node are easy to gather and a large area of ​​blank area appears, which affects the readability of the drawings and is not conducive to the actual application of the project. In summary, in order to realize the automatic drawing of mine ventilation network diagrams, there are currently main problems that need to be overcome, such as the return air shafts are not on the same layer and the stratification time is long, the path finding time is long, too many drawing intersections affect readability, the optimization algorithm effect is not significant and increases time consumption, and the blank area of ​​the quadratic function drawing is too large. Summary of the invention

[0004] In order to solve the problems that the drawing of network diagrams does not meet the requirements of regulations, the drawing efficiency is low, and complex network diagrams cannot be drawn, the present invention provides a method for automatically drawing a mine ventilation network diagram.

[0005] The present invention adopts the following technical scheme: a method for automatically drawing a mine ventilation network diagram, comprising: S100: performing a cyclic deduplication operation on the start node and the end node elements of the directed edge set, thereby realizing vertical sorting of the acquired network graph nodes; S200: Traverse all nodes from the air intake shaft node to the air return shaft node according to the directed graph direction, and calculate all paths from the air intake shaft node to the air return shaft node; S300: Simplify and beautify the network diagram by reducing the number of nodes and evenly arranging the node positions without affecting the connectivity of the network diagram and the node topology relationship; S400: Classify all paths, divide the network graph into multiple sub-networks, and divide trunks and branches according to the sub-networks; S500: Draw the trunk and branch of the network diagram; S600: Optimize the branch positions of the ventilation network diagram.

[0006] Step S100 includes: S101: For ventilation system diagrams ,in Represents a collection of nodes. Represents a set of directed edges. Input the start node set and the end node set , concatenating them into a directed edge set ; S102: Remove collection and Duplicate nodes will exists and Node that does not exist in Determined as the l Layer, where ; S103: Remove collection Contains nodes Directed edge and , and obtain a new set of directed edges , while removing the set and Nodes in and, *, and The connected nodes, ; S104: Judgment Set Is it empty? If it is empty, then The remaining nodes in the last layer are nodes. If they are not empty, repeat step S103 and onwards until the set Empty, ending the loop.

[0007] Step S200 includes: S201: Put all n nodes into the empty queue and record it as , and mark it as read; S202: Initialize n auxiliary queues. Put them into n empty queues in turn; S203: Then pop up the queue head item , traverse in sequence arrive Adjacent points, judge Is the number of adjacent nodes j greater than 1? If j is greater than 1, it will contain The auxiliary queue is copied into j pieces. If j is equal to 1 and all the head items are traversed, the traversed adjacent points that are not marked as read are put into the queue and marked as read; S204: Determine whether the queue is empty. If it is, the algorithm ends. If it is not empty, traverse each node of the head item of the queue to determine whether it is connected to the tail item of the jth auxiliary queue. If it is connected, put the node into the auxiliary queue until the algorithm ends. All paths will be obtained, where .

[0008] Step S300 includes: S301: For a network graph containing n nodes and m directed edges , convert the nodes that are only connected to the two adjacent nodes before and after into virtual nodes; S302: After the nodes are sorted, virtual nodes are added to positions where empty nodes exist in certain layers to achieve uniform distribution.

[0009] Step S302 includes: The real nodes and layers of the known branches and a collection of virtual nodes and layers , where v represents a node, is the layer number of the real node v, is the layer number of the virtual node v, V represents the set of all nodes, i is the serial number of the real node, j is the maximum serial number of the real node, k is the maximum number of layers of the mine network diagram, o is the serial number of the virtual node, p is the maximum serial number of the virtual node, which is also the number of layers of the branch; First, determine the size of j and pj. , then calculate the integer divisor u of j and pj, and arrange them in such a way that every u real nodes are followed by one virtual node; like , then calculate the integer divisor u of pj and j, and arrange them in the way that each real node is followed by u virtual nodes, and finally get the real nodes and layers of the mine after arrangement and a collection of virtual nodes and layers .

[0010] Step S400 includes: S401: Divide the ventilation system diagram including a return air shaft and b intake air shaft into Subnetwork diagram; S402: Draw an “elliptical” network diagram according to the two longest paths in the sub-network diagram; S403: After obtaining all the paths in the sub-network diagram after sorting the air intake shaft nodes and the air return shaft nodes, the network diagram is divided into trunks and branches.

[0011] Step S401 includes: Step 1: Sort the longest paths of each return air shaft node from large to small to determine the position of the return air shaft node from left to right; Step 2: Based on the total number of paths from the air intake shaft node to each return air shaft node, the return air shaft node with the largest number of paths and its associated lane set and the corresponding air intake shaft node are divided into a sub-network; Step 3: Sort the air intake shaft nodes under the same return air shaft node again, and sort them from small to large according to the total number of paths from these air intake shaft nodes to other return air shaft nodes on the right to determine their positions from left to right.

[0012] Step S402 includes: Step 1: All paths of the known subnetwork are collected ,First, each sub-network path set is merged according to the order of the air intake shaft node and the return air shaft node. Specifically, the paths containing the same air intake shaft node and the same return air shaft node are classified into a subset, and each subset is a sub-network; Step 2: In the first subnetwork, select the longest path as the left arc of the "ellipse" network diagram, and In a subnetwork, select a path that does not overlap with the left arc and is the longest in this subnetwork as the right arc of the "elliptical" network diagram.

[0013] Step S403 includes: Find explicit branches, i.e. branches with more than two nodes; Step 1: First mark the left arc main road as , and traverse all the remaining paths in turn ; Step 2: Calculation minus Get the node set ; Step 3: Found The front and back adjacent nodes of the middle node are concatenated into a set ,in ; Step 4: Set The neutron subsets are spliced ​​together. If there is a After If the nodes are repeated, they can be spliced ​​together until they cannot be spliced ​​together, and the spliced ​​set is obtained. ; Step 5: Determine the set Whether the neutron set exists in the set If it exists, then the subset is an explicit branch set, otherwise it is not; Find implicit branches, i.e. branches that contain only two nodes; Step 1: Mark the left arc main road as , and traverse all the remaining path sets in turn ; Step 2: Calculation minus Get the node set ; Step 3: Found The front and back adjacent nodes of the middle node are concatenated into a set ,in ; Step 4: Set The neutron subsets are spliced ​​together. If there is a After If the nodes are repeated, they can be spliced ​​together until they cannot be spliced ​​together, and the spliced ​​set is obtained. ; Step 5: Assemble Take the first and last nodes of the subset and put them into a new set middle; Step 6: Determine the set Whether the neutron set exists in the set If it exists, then the subset is an implicit branch set, otherwise it is not; In the process of finding branches, if there are repeated branches between sub-networks, they will be assigned to the sub-network with the highest ranking.

[0014] Step S500 includes: Drawing the trunk and branch of the ventilation network diagram includes: drawing the left arc and the right arc of the network diagram, and using the circular function to draw the branch; in the drawing process, the air inlet shaft node in the left arc and the right arc trunk path is used as the head node of the elliptical arc, and the return air shaft node is used as the tail node of the elliptical arc. Therefore, the distance between the head node and the tail node is , where k is the length of the sorted node set, ; The elliptic function is: The circular function is used to perform transformation operations such as scaling, translation and rotation, and special shapes are applied to the branch connections in the ventilation network diagram, making the ventilation network diagram more neat and beautiful as a whole.

[0015] Step S600 includes: Step 1: Create a circular function in , , X is the x-parameter equation considering all cases of conversion to the network graph curve function, and Y is the y-parameter equation considering all cases of conversion to the network graph curve function; Step 2: Using the number of intersections and uniformity as evaluation indicators, the ventilation network diagram is made more beautiful and optimized through the circular function; Step 3: Generate the finalized network structure A with the finalized nodes and directed edges; Step 4: According to the location distribution of mine structures, insert the structure-related icons into the network structure A to automatically generate the final ventilation network diagram that can be used.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention realizes the vertical sorting of the network graph nodes by cyclically removing the start and end node elements of the directed edge set, solves the problem that the longest path hierarchical algorithm cannot sort the return air shaft to the same layer, and shortens the sorting time. By searching the directed graph nodes once to find all the paths from the air intake shaft node to the return air shaft node, the running time of the path-finding algorithm code is shorter than that used in other studies. The network graph is simplified and beautified from the two aspects of reducing the number of nodes and uniform branch nodes, which meets the requirements of network graph drawing. By dividing the subnetwork after path classification, the main road and branch of the network graph are obtained, which solves the problem that the longest path parallel method does not consider dividing the subnetwork and only obtains the longest branch, resulting in a large blank area. The network graph is drawn by the variable circular equation of the elliptic function and the circular function, which solves the problem that the branch curves of the same node bifurcation are aggregated when the network graph is drawn by the quadratic function. Finally, the network graph is iteratively optimized by the variable circular function of the variable circular equation to obtain a network graph with fewer intersections and greater uniformity. The present invention can draw a beautiful ventilation network graph and realize the automatic drawing of the mine ventilation system graph. It takes about 10 minutes to draw a network diagram with nearly 200 edges by optimizing the genetic algorithm, while this method only takes about 20 seconds to draw a network diagram with nearly 300 edges; compared with the longest path hierarchical algorithm, this method can divide the return air shaft into the same layer and save 1 / 3 of the time; compared with the DFS pathfinding algorithm, this method can save more than half of the time; compared with quadratic function drawing, the uniformity is increased and the blank area is reduced; compared with the longest path parallel method, the sub-network can be clearly divided and the number of intersections can be reduced. This method is suitable for the automatic drawing of mine ventilation network diagrams, which improves the drawing efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 Automatically draw a schematic diagram of a ventilation network diagram according to an embodiment of the present invention; Figure 3 A diagram of a mine ventilation system according to an embodiment of the present invention; Figure 4 A network diagram framework drawn based on a variable circle equation according to an embodiment of the present invention; Figure 5 The optimized mine ventilation network diagram framework of the embodiment of the present invention; Figure 6 This is a diagram of the optimized mine ventilation network according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] An embodiment of the present invention provides a method for automatically drawing a mine ventilation network diagram, aiming to solve the problems existing in the prior art when drawing a mine ventilation network diagram, such as time-consuming and low efficiency of code running and lack of clear structure of the generated network diagram.

[0019] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. The preferred embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0021] See also Figure 1 The present invention provides an embodiment of a method for automatically drawing a mine ventilation network diagram, wherein the flow diagram and the drawing diagram are shown in Figure 1 and Figure 2 ,include: S100: By performing a cyclic deduplication operation on the start node and the end node elements of the directed edge set, the obtained network graph nodes are vertically sorted.

[0022] The nodes and networks of the ventilation network diagram include: inputting the actual ventilation system diagram, converting the two-dimensional CAD ventilation system diagram into a three-dimensional stereogram, and automatically extracting the node number of each directed edge.

[0023] In step S100, based on the Hasse diagram principle, the nodes in the network diagram are sorted to achieve vertical sorting of the nodes in the network diagram.

[0024] In this embodiment, the mine ventilation system diagram is shown in Figure 3 ,First, the node numbers of each directed edge in the mine ventilation ,system graph are obtained, which includes 310 nodes and 412 directed edges in total. The nodes are ,divided into 72 layers to realize the vertical sorting of the nodes in the ,network graph.

[0025] S200: Traverse all nodes from the air intake shaft node to the air return shaft node according to the direction of the directed graph, and calculate all paths from the air intake shaft node to the air return shaft node.

[0026] In step S200, all nodes in the network diagram are searched once to calculate all paths from the air intake shaft node to the return air shaft node. Specifically, in combination with the sorted nodes in the mine ventilation system diagram in S100, all paths that need to be traversed from the air intake shaft node to the return air shaft node are determined through a path finding algorithm.

[0027] In this embodiment, a path-finding algorithm is used to determine all paths from the air intake shaft node to the air return shaft node in the mine in S100, totaling 59,766 paths.

[0028] S300: Without affecting the connectivity of the network diagram and the node topology, the network diagram is simplified and beautified by reducing the number of nodes and evenly arranging the node positions.

[0029] In this embodiment, the nodes are optimized from two aspects: reducing the number of nodes and evenly arranging the node positions, reducing the number of nodes from the original 310 to 193. Virtual nodes are introduced, and the positions of real nodes and virtual nodes are exchanged, so that the branch nodes of the network diagram are evenly distributed, and the distance standard deviation of the mine network diagram of the embodiment is reduced from 17.45 to 15.53, thereby improving the evenness of the network diagram.

[0030] S400: Classify all paths, divide the network graph into multiple sub-networks, and divide trunks and branches according to the sub-networks.

[0031] In step S400, the network is divided into sub-networks to determine the trunk and branches of the network diagram. The trunk includes a left arc and a right arc, and the branches are divided into explicit branches and implicit branches.

[0032] In this embodiment, the ventilation system diagram including 3 return air shafts and 4 intake air shafts is divided into 12 sub-network diagrams, and two trunks are obtained, namely 2→210→212→213→216→217→214→218→219→220→223→257→272→18→258→19→20→28→30→117→115→33→114→274→27→29→305→81→78→79→279→104→103→105→113→83→84→88→92→7→91→90→89→86→85→6→73→71→69→70→203→233→234→235→64→24 0→241→243→308 and 5→271→270→260→259→123→122→281→116→124→125→126→127→128→130→287→148→149→147→146→307→297→139→157→158→155→159→299→193→199→200→201→198→197→289→190→192→262→263→264→265→266→267→268→269→153→152→154→137→309, resulting in 105 branches, of which 63 are explicit branches and 42 are implicit branches.

[0033] S500: Draw the trunks and branches of the network diagram.

[0034] In step S500, according to the divided main roads and branches of the network diagram, the left arc, right arc and branch arc of the network diagram are drawn respectively using a circular function with the node as the starting and ending points. Through transformation operations such as scaling, translation and rotation, special shapes are applied to the branch connections in the ventilation network diagram, making the ventilation network diagram as a whole more neat and beautiful.

[0035] In this embodiment, the node close to the origin on each line is used as the reference point for movement, and the entire line is translated so that the node coincides with the origin. At the same time, the node that coincides with the origin is defined as the bottom of the branch curve shape, and the other node is the top of the branch curve shape. According to the corresponding rotation changes of the four shapes of the two nodes at the origin, the rotation diagrams of the circular equations in four different situations are obtained. Figure 4 Finally, the variable circle equations under four different conditions were derived, and the equations of 2 trunks and 105 branches were derived. The network diagram framework of the embodiment was drawn according to the equations. Figure 5 .

[0036] S600: Optimize the branch positions of the ventilation network diagram.

[0037] Step 1: Create a circular function in , , X is the x-parameter equation considering all cases of conversion to the network graph curve function, and Y is the y-parameter equation considering all cases of conversion to the network graph curve function.

[0038] Step 2: Using the number of intersections and uniformity as evaluation indicators, the ventilation network diagram is beautified and optimized through the circular function.

[0039] Step 3: Generate the finalized network structure A with the finalized nodes and directed edges.

[0040] Step 4: According to the location distribution of mine structures, insert the structure-related icons into the network structure A to automatically generate the final ventilation network diagram that can be used.

[0041] In step S600, the ventilation network diagram is optimized by using a variable circle function optimization algorithm based on a variable circle equation to obtain a more beautiful and efficient ventilation network diagram, and the beauty of the network diagram is evaluated by two indicators: the number of intersections and uniformity.

[0042] In this embodiment, the circular equation in S500 is converted into an iterative circular function, and the mine ventilation network diagram is optimized by the circular function optimization algorithm to obtain the optimized network diagram framework of the embodiment. Figure 6Before optimization, the number of intersections in the network diagram was 354, which was reduced to 184 after optimization, achieving a significant reduction in the number of intersections in the network diagram. The number of intersections and the standard deviation of distances of the mine ventilation network diagram drawn with and without the variable circular function optimization algorithm were calculated. Under this condition, the node intersection number and distance standard deviation of the mine ventilation network diagram show an overall downward trend, but the lowest point of the node intersection number and the lowest point of the distance standard deviation do not coincide. In order to determine the optimal iteration point ,Under different iteration numbers, the normalized values ​​of node crossing number and distance standard deviation are used as judgment criteria, and the iteration point corresponding to the minimum value of the normalized vector is selected. The circular function optimization algorithm can further improve the aesthetics of the mine ventilation network diagram. In summary, the results of the embodiments of the present invention verify that the provided method for automatically drawing a mine ventilation network diagram has a good automatic drawing effect.

[0043] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for automatically drawing a mine ventilation network diagram, characterized in that: include: S100: performing a cyclic deduplication operation on the start node and the end node elements of the directed edge set, thereby realizing vertical sorting of the acquired network graph nodes; S200: Traverse all nodes from the air intake shaft node to the air return shaft node according to the directed graph direction, and calculate all paths from the air intake shaft node to the air return shaft node; S300: Simplify and beautify the network diagram by reducing the number of nodes and evenly arranging the node positions without affecting the connectivity of the network diagram and the node topology relationship; S400: Classify all paths, divide the network graph into multiple sub-networks, and divide trunks and branches according to the sub-networks; S500: Draw the trunk and branch of the network diagram; S600: Optimize the branch positions of the ventilation network diagram.

2. The method for automatically drawing a mine ventilation network diagram according to claim 1, characterized in that: The step S100 includes: S101: For ventilation system diagrams ,in Represents a collection of nodes. Represents a set of directed edges. Input the start node set and the end node set , concatenating them into a directed edge set ; S102: Remove collection and Duplicate nodes will exists and Node that does not exist in Determined as the l Layer, where ; S103: Remove collection Contains nodes Directed edge and , and obtain a new set of directed edges , while removing the set and Nodes in and, *, and The connected nodes, ; S104: Judgment Set Is it empty? If it is empty, then The remaining nodes in the last layer are nodes. If they are not empty, repeat step S103 and onwards until the set Empty, ending the loop.

3. The method for automatically drawing a mine ventilation network diagram according to claim 1, characterized in that: The step S200 includes: S201: Put all n nodes into the empty queue and record it as , and mark it as read; S202: Initialize n auxiliary queues. Put them into n empty queues in turn; S203: Then pop up the queue head item , traverse in sequence arrive Adjacent points, judge Is the number of adjacent nodes j greater than 1? If j is greater than 1, it will contain The auxiliary queue is copied into j pieces. If j is equal to 1 and all the head items are traversed, the traversed adjacent points that are not marked as read are put into the queue and marked as read; S204: Determine whether the queue is empty. If it is, the algorithm ends. If it is not empty, traverse each node of the head item of the queue to determine whether it is connected to the tail item of the jth auxiliary queue. If it is connected, put the node into the auxiliary queue until the algorithm ends. All paths will be obtained, where .

4. The method for automatically drawing a mine ventilation network diagram according to claim 1, characterized in that: The step S300 includes: S301: For a network graph containing n nodes and m directed edges , convert the nodes that are only connected to the two adjacent nodes before and after into virtual nodes; S302: After the nodes are sorted, virtual nodes are added to positions where empty nodes exist in certain layers to achieve uniform distribution.

5. The method for automatically drawing a mine ventilation network diagram according to claim 3, characterized in that: The step S302 includes: The real nodes and layers of the known branches and a collection of virtual nodes and layers , where v represents a node, is the layer number of the real node v, is the layer number of the virtual node v, V represents the set of all nodes, i is the serial number of the real node, j is the maximum serial number of the real node, k is the maximum number of layers of the mine network diagram, o is the serial number of the virtual node, p is the maximum serial number of the virtual node, which is also the number of layers of the branch; First, determine the size of j and pj. , then calculate the integer divisor u of j and pj, and arrange them in such a way that every u real nodes are followed by one virtual node; like , then calculate the integer divisor u of pj and j, and arrange them in the way that each real node is followed by u virtual nodes, and finally get the real nodes and layers of the mine after arrangement and a collection of virtual nodes and layers .

6. The method for automatically drawing a mine ventilation network diagram according to claim 1, characterized in that: The step S400 includes: S401: Divide the ventilation system diagram including a return air shaft and b intake air shaft into Subnetwork diagram; S402: Draw an "ellipse" network diagram according to the two longest paths in the sub-network diagram; S403: After obtaining all the paths in the sub-network diagram after sorting the air intake shaft nodes and the air return shaft nodes, the network diagram is divided into trunks and branches.

7. The method for automatically drawing a mine ventilation network diagram according to claim 6, characterized in that: The step S401 includes: Step 1: Sort the longest paths of each return air shaft node from large to small to determine the position of the return air shaft node from left to right; Step 2: Based on the total number of paths from the air intake shaft node to each return air shaft node, the return air shaft node with the largest number of paths and its associated lane set and the corresponding air intake shaft node are divided into a sub-network; Step 3: Sort the air intake shaft nodes under the same return air shaft node again, and sort them from small to large according to the total number of paths from these air intake shaft nodes to other return air shaft nodes on the right to determine their positions from left to right.

8. The method for automatically drawing a mine ventilation network diagram according to claim 6, characterized in that: The step S402 includes: Step 1: All paths of the known subnetwork are collected First, each sub-network path set is merged according to the order of the air intake shaft node and the air return shaft node. Specifically, the paths containing the same air intake shaft node and the same air return shaft node are classified into a subset, and each subset is a sub-network; Step 2: In the first subnetwork, select the longest path as the left arc of the "ellipse" network diagram, and In a subnetwork, select a path that does not overlap with the left arc and is the longest in this subnetwork as the right arc of the "elliptical" network diagram.

9. The method for automatically drawing a mine ventilation network diagram according to claim 8, characterized in that: The step S403 includes: Find explicit branches, i.e. branches with more than two nodes; Step 1: First mark the left arc main road as , and traverse all the remaining paths in turn ; Step 2: Calculation minus Get the node set ; Step 3: Found The front and back adjacent nodes of the middle node are concatenated into a set ,in ; Step 4: Set The neutron subsets are spliced ​​together. If there is a After If the nodes are repeated, they can be spliced ​​together until they cannot be spliced ​​together, and the spliced ​​set is obtained. ; Step 5: Determine the set Whether the neutron set exists in the set If it exists, then the subset is an explicit branch set, otherwise it is not; Find implicit branches, i.e. branches that contain only two nodes; Step 1: Mark the left arc main road as , and traverse all the remaining path sets in turn ; Step 2: Calculation minus Get the node set ; Step 3: Found The front and back adjacent nodes of the middle node are concatenated into a set ,in ; Step 4: Set The neutron subsets are spliced ​​together. If there is a After If the nodes are repeated, they can be spliced ​​together until they cannot be spliced ​​together, and the spliced ​​set is obtained. ; Step 5: Assemble Take the first and last nodes of the subset and put them into a new set middle; Step 6: Determine the set Whether the neutron set exists in the set If it exists, then the subset is an implicit branch set, otherwise it is not; In the process of finding branches, if there are repeated branches between sub-networks, they will be assigned to the sub-network with the highest ranking.

10. The method for automatically drawing a mine ventilation network diagram according to claim 1, characterized in that: The step S500 includes: Use ellipse function to draw the left and right arcs of the network diagram, and use circular function to draw the branches; During the drawing process, the air inlet shaft node in the left arc and right arc trunk paths is used as the head node of the elliptical arc, and the return air shaft node is used as the tail node of the elliptical arc. Therefore, the distance between the head node and the tail node is , where k is the length of the sorting node set, ; The elliptic function is: By deforming the parameter equation of the circular function, a modified circular equation is obtained; then, through scaling, translation and rotation transformation operations, the special shape is applied to the branch connections in the ventilation network diagram, making the ventilation network diagram as a whole more neat and beautiful.

11. The method for automatically drawing a mine ventilation network diagram according to claim 1, characterized in that: The step S600 includes: Step 1: Create a circular function in , , X is the x-parameter equation considering all cases of conversion to the network graph curve function, and Y is the y-parameter equation considering all cases of conversion to the network graph curve function; Step 2: Using the number of intersections and uniformity as evaluation indicators, the ventilation network diagram is beautified and optimized through the circular function; Step 3: Generate the finalized network structure A with the finalized nodes and directed edges; Step 4: According to the location distribution of mine structures, insert the structure-related icons into the network structure A to automatically generate the final ventilation network diagram that can be used.

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