Method, system, equipment and medium for determining underground coal mine ventilation volume

Abstract

The invention discloses a method, a system, equipment and a medium for determining underground coal mine ventilation volume, and relates to the technical field of coal mine ventilation management.The method comprises the steps that when a minimum loop is searched, the priority weight of each remaining branch is determined with the level of a breadth-first spanning tree of a tree node as a weight factor, searching is started from the remaining branch with the minimum weight, and a plurality of loops are constructed; extracting a closed loop with the least residual branches; meanwhile, dynamic weights are set according to the number of remaining branches, the loop with the minimum sum of the weights of the remaining branches is selected as the minimum loop, and it is ensured that the calculated roadway air volume is consistent with the actual value. In addition, the air flow direction is judged through the edge relation, the air volume symbol is adjusted, the abnormal direction is corrected, and the calculated air flow direction fits the reality.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal mine ventilation management, and in particular relates to a coal mine underground ventilation air volume determination method, system, device and medium. BACKGROUND

[0002] The advantages and disadvantages of the coal mine underground ventilation system are directly related to production safety. With the continuous increase of coal mining depth, the underground roadway layout becomes complex. Traditional ventilation calculation relies on empirical data and manual calculation, which not only has large errors, but also is low in efficiency, and is difficult to meet the strict requirements of current coal mine efficient and safe mining.

[0003] In view of the problems existing in manual calculation, Scott-Hinsley algorithm and minimum spanning tree algorithm are usually applied to obtain the ventilation flow at present. The Scott-Hinsley algorithm has certain advantages in air volume calculation, and the minimum spanning tree algorithm helps to analyze the relationship of underground roadway and find the minimum loop, which provides key support for air volume calculation. However, the effective combination of the two algorithms for accurate and rapid calculation of underground ventilation system, especially in complex mine environment, still lacks a practical solution. In addition, in the determination of air flow direction, the traditional method mainly relies on artificial experience or simple measuring equipment, which is low in efficiency and poor in accuracy, and cannot realize real-time and accurate detection of abnormal conditions of air flow direction. Once the air flow direction is abnormal, for example, the air flow is reversed due to roadway blockage, which is easy to cause serious safety accidents such as gas accumulation, and the traditional determination method is difficult to find and give early warning in time, which seriously threatens the life safety of underground workers.

[0004] In view of the problems in the above description, the most important thing in the analysis of air volume is the determination of the minimum loop in the relationship of underground roadway. At present, when the minimum spanning tree algorithm (Minimum Spanning Tree, MST) is used to find the minimum loop of the relationship of underground roadway, the result of the minimum loop highly depends on the weight of the edge. If the weight information is inaccurate or has errors, the generated minimum spanning tree is not optimal. At present, the weight information of the edge is usually set randomly, which makes the minimum loop found not the minimum loop of the current relationship of underground roadway, so that the calculated air volume has large error with the actual air volume. SUMMARY

[0005] The embodiment of the present application provides a kind of coal mine underground ventilation air volume determination method, system, equipment and medium, can solve the existing technology, there is the minimum loop of present stage in finding underground roadway relationship, the result of its finding minimum loop is highly dependent on the weight of edge, if weight information is inaccurate or has error, then lead to the minimum spanning tree generated is not optimal, and currently for the weight information setting of edge, it is usually randomly set, resulting in the minimum loop finally sought is not the minimum loop of current underground roadway relationship, so that the air volume finally calculated and actual air volume error is large.

[0006] The embodiment of the present application provides a kind of coal mine underground ventilation air volume determination method, system, equipment and medium, can solve the existing technology, there is the minimum loop of present stage in finding underground roadway relationship, the result of its finding minimum loop is highly dependent on the weight of edge, if weight information is inaccurate or has error, then lead to the minimum spanning tree generated is not optimal, and currently for the weight information setting of edge, it is usually randomly set, resulting in the minimum loop finally sought is not the minimum loop of current underground roadway relationship, so that the air volume finally calculated and actual air volume error is large. Collect the position and connection relationship of all roadways in the coal mine underground, and establish a roadway relationship topology graph; using the minimum spanning tree algorithm, the topology graph is constructed into a breadth-first spanning tree with multiple layers and each layer containing multiple branches, and then the priority weight is determined according to the layer level of the branches; Taking the branch with the minimum priority weight as the starting point, search the connected branches in the tree in turn, and form a one-way loop through multiple iterations until returning to the starting point; repeat the process to obtain multiple loops containing the branch with the minimum weight; Extract the closed loop with the least number of branches from the multiple loops, and dynamically set the weight according to the number of occurrences of each branch in the loop, and select the minimum sum of the weights of each branch as the minimum loop of the roadway. Determine the air flow direction matrix representing the positive and negative directions of the air flow by combining the roadway connection and the position of the ventilation equipment; adjust the air volume sign of each roadway in the minimum loop according to the matrix, correct the abnormal air flow direction through iterative calculation, ensure that it conforms to the actual ventilation state, calculate the air volume of the minimum loop, and obtain the ventilation air volume of the coal mine underground.

[0007] Preferably, the priority weight of each branch in the breadth-first spanning tree is determined, comprising: construct the roadway relationship topology graph into a breadth-first spanning tree, and determine the layer number of each vertex in the breadth-first spanning tree; define the priority of the branch in the breadth-first spanning tree as the sum of the layer numbers of the vertices, set the layer number of vertex v as L ( v ), for branch e=(u, v), its priority weight , wherein represents the layer number of vertex u in the breadth-first spanning tree; in the breadth-first spanning tree, the length of the closed loop formed by any branch e=(u, v) is higher than , arrange the branches in ascending order according to W ( e ), and obtain the priority weight of each branch in the breadth-first spanning tree.

[0008] Preferably, the obtaining of the minimum circuit comprises: extracting a plurality of closed circuits with the least number of stubs and equal number of stubs from the plurality of circuits; defining a stub dynamic weight for any stub e=(u,v) in the Sorge closed circuit as wherein , is an adjustment parameter, Degree ( v ) is the degree of vertex v , Degree ( u ) is the degree of vertex u ; taking the closed circuit with the smallest sum of stub weights in the plurality of closed circuits as the minimum circuit in the roadway.

[0009] Preferably, after obtaining the ventilation volume of the underground coal mine, the wind flow direction of each roadway is determined, comprising: constructing a directed graph G=(V,E), wherein the vertex set V is the intersection of the roadway, the edge set E is the connection of the roadway and each edge contains the (source,target,windVolume) attribute, starting from the air inlet V0 and traversing the graph G by depth-first search to generate a traversal path stack P and mark the generated tree edge set T and the stub set R=E\T; setting the current edge of the roadway as e i =( v a , v b ), the next edge as e j =( v c , v d ), and determining the positive and negative of the current roadway wind flow direction by judging the relationship of the two edges; the relationship value t ij is: ; defining an initial wind volume sign matrix S, updating the sign according to t ij to make Q i '=Q i ×S i ; calculating a self-consistency index for each closed loop C, if (preset threshold) then triggering correction, r i represents the wind resistance, t i represents the relationship value, and when Qi'<0, reversing the wind flow direction and updating the edge attribute until ; For the remaining branch e=(u,v)∈R, according to the layer difference in the spanning tree The check direction should be u→v when ΔL=1 and v→u when ΔL=-1, and the air volume sign is forced to be corrected and the abnormality is recorded when there is a contradiction.

[0010] Preferably, after the air flow direction of each roadway is determined, a 2D air flow graph is generated underground, wherein the nodes represent the intersection points of the roadways, the edges represent the connection of the roadways, the edge attribute dynamically maps the air volume data, the air flow direction is indicated by the directional edge arrow, and the abnormal air flow is highlighted.

[0011] The embodiment of the present application also provides a coal mine underground ventilation air volume determination system, comprising: A data acquisition module is configured to acquire the position and connection relationship of all the roadways underground, establish a roadway relationship topological graph, use a minimum spanning tree algorithm to construct the topological graph into a breadth-first spanning tree with multiple layers and each layer containing multiple remaining branches, and determine the priority weight according to the layer level of the remaining branches. A loop judgment module is configured to take the remaining branch with the minimum priority weight as a starting point, search the connected remaining branches in the tree in sequence, form a one-way loop through multiple rounds of iteration until returning to the starting point, and repeat the process to obtain multiple loops containing the remaining branch with the minimum weight. A closed loop with the least number of remaining branches is extracted from the multiple loops, and the weight of each remaining branch is dynamically set according to the number of occurrences of the remaining branch in the loop, and the minimum loop of the roadways is selected as the minimum loop of the roadways with the minimum sum of the weights of the remaining branches. An air volume calculation module is configured to determine an air flow direction matrix representing the positive and negative directions of the air flow in combination with the connection of the roadways and the position of the ventilation equipment, adjust the air volume sign of each roadway in the minimum loop according to the matrix, correct the abnormal air flow direction through iterative calculation, ensure that the actual ventilation state is met, calculate the air volume of the minimum loop, and obtain the ventilation air volume underground.

[0012] The embodiment of the present application also provides an electronic device comprising a memory and a processor. The memory is configured to store a computer program. The processor is configured to execute the computer program stored in the memory to implement the steps of the coal mine underground ventilation air volume determination method.

[0013] The embodiment of the present application also provides a computer readable storage medium for storing a computer program, wherein the computer program is executed by a processor to implement the steps of the coal mine underground ventilation air volume determination method.

[0014] The embodiment of the present application provides a coal mine underground ventilation air volume determination method, system, device and medium, which has the following advantages compared with the prior art: The present application finds the minimum loop of the relationship of the underground roadway of the coal mine, generates the breadth-first spanning tree by using the minimum spanning tree algorithm, determines the priority of the remaining branch of the breadth-first spanning tree by using the remaining branch priority function based on the layer weight, simultaneously adjusts the dynamic weight of the priority selection of the remaining branch with the minimum dynamic weight to search and construct the loop, and obtains the minimum loop; when finding the minimum loop of the relationship of the underground roadway, the present application takes the layer of the tree node in the breadth-first spanning tree as the weight factor to determine the priority weight of each remaining branch in the breadth-first spanning tree, starts the loop search from the remaining branch with the minimum priority weight, constructs multiple loops including the remaining branch with the minimum priority weight, extracts multiple closed loops with the minimum number of remaining branches and the equal number of remaining branches, sets the dynamic weight of the corresponding remaining branch by the size of the number of different remaining branches during the loop search, and takes the loop with the minimum sum of the weights of each remaining branch in the loop as the minimum loop in the roadway, so as to realize the dynamic weight adjustment and optimization of the remaining branch in the breadth-first spanning tree, make the obtained loop the minimum loop of the current relationship of the underground roadway, and thus the calculated air volume of the underground roadway of the coal mine is consistent with the actual air volume. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 A whole flowchart of a coal mine underground ventilation air volume determination method provided by the embodiment of the present application is shown. Figure 2 A system architecture diagram of a coal mine underground ventilation air volume determination method provided by the embodiment of the present application is shown. DETAILED DESCRIPTION

[0016] In order to make the above objectives, features and advantages of the present application more apparent, the specific embodiments of the present application are described in detail below with reference to the drawings. In the following description, a lot of specific details are set forth in order to fully understand the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present application, so the present application is not limited by the specific embodiments disclosed below.

[0017] Referring to Figure 1 The embodiment of the present application provides a coal mine underground ventilation air volume determination method, which comprises the following steps: Step S1: establishing the relationship topological graph between the underground roadways and marking the main airway.

[0018] The relationship topological graph of the underground coal mine roadway is constructed, the relationship of each roadway node and the connected channel is marked, and the position of the main airway is determined; the topological graph of the underground roadway is constructed by manual marking data, combined with the geographical position calibration of the roadway, to ensure that the established topological relationship has accurate spatial position association.

[0019] Step S2: The minimum spanning tree algorithm finds all the minimum loops in the relationship of the underground roadway; specifically including: Step S21: The priority function of the remaining branch based on the layer weight. First, after the relationship topology graph of the underground roadway is constructed and the breadth-first spanning tree is obtained, the layer number of each vertex is determined; the priority of the remaining branch is defined as the sum of the layer numbers of the vertices, and the layer number of vertex v is L ( v ), and for the remaining branch e=(u, v), the priority weight is , wherein represents the layer number of vertex u in the breadth-first spanning tree; this is because in the breadth-first spanning tree, the length of the closed loop formed by any remaining branch e=(u, v) is at least ; since the BFS tree expands by layer, the layer difference between u and v is at most 1, the closed loop path needs to pass through the common ancestor, and the loop length is positively correlated with the layer number; therefore, the remaining branches are arranged in ascending order of W ( e ), and the remaining branches with small weights are processed first, so that the minimum length closed loop can be found first, and the search depth can be effectively reduced.

[0020] Step S22: Dynamic weight adjustment and greedy strategy. After determining the initial priority of the remaining branch based on the layer number weight, in order to further optimize the search order, a dynamic weight function is introduced; for the remaining branch e=(u, v), the dynamic weight is defined as , wherein , are adjustment parameters, Degree ( v ) is the degree of vertex v , Degree ( u ) is the degree of vertex u ; considering that a high number vertex may be connected to more potential loops, by adjusting the priority in this way, combined with the greedy algorithm, the remaining branches with small dynamic weights are selected for processing, so that the search process is more targeted, and the search efficiency is further improved.

[0021] Step S23: Closed loop uniqueness determination and normalized representation. After processing the remaining branches according to the adjusted priority and finding the closed loop by using the depth-first search (DFS), in order to avoid repeated calculation, the closed loop is determined for uniqueness and normalized representation; for the closed loop C ={v0,v1,…,v k-1}, the normalized form is defined as , wherein Rotate ( C, θ) represents the arrangement after rotating the ring clockwise by θ steps, and the lexicographically smallest arrangement is selected as the unique identifier; mathematical proof shows that the canonical form of any closed ring is unique and independent of the starting point and direction; in actual code implementation, rotation and inversion operations are used to ensure the unique representation of the ring, so that the found closed ring can be automatically deduplicated when stored in the set.

[0022] Step S24: Algebraic topology-based ring space decomposition. In the process of continuously finding and normalizing closed loops, the algebraic topology-based ring space decomposition theory is used to ensure that the found closed loops are comprehensive and accurate; the concept of ring space in algebraic topology is introduced, and the cycle space of a graph is a linear space of edge sets, whose basis is composed of independent closed loops; let the set of residual branches be T, the spanning tree be S, and each residual branch e∈T correspond to a unique ring Ce ∈Cycle Space, the set of independent closed loops ; through algebraic independence, it is proved that this set constitutes a basis of the ring space, which guarantees that all the found closed loops are independent and can cover all the smallest independent closed loops.

[0023] Step S25: Algorithm convergence and time complexity analysis. In the process of searching for the smallest independent closed loop, the mathematical induction method is used to prove the convergence of the algorithm; the induction basis is that when the number of residual branches is 1, the algorithm finds the unique closed loop through DFS; the induction hypothesis is that the algorithm can correctly find all independent closed loops for n residual branches; the induction step is to process each residual branch according to the above adjusted priority for n+1 residual branches, and use DFS to search for closed loops; since each residual branch belongs to only one independent loop (by the spanning tree property), the algorithm gradually reduces the number of unprocessed residual branches; according to the spanning tree property, each residual branch belongs to only one independent loop, so as the processing process advances, all independent closed loops can be covered; in terms of the time complexity of the algorithm, let the graph have V vertices and E edges, the spanning tree have V-1 edges, and the number of residual branches be E-V+1, then the time complexity of the algorithm is ; compared with the exponential complexity of traditional DFS, this algorithm limits the search depth to O(V) by sorting the residual branches and controlling the number of layers, which significantly improves the efficiency.

[0024] Step S3: Substitute the found minimum loop into the Scott-Hinsley algorithm for iterative calculation of air volume. The Scott-Hinsley algorithm uses an improved iterative method, imports the minimum loop data in the S2 step, supports optimization calculation combined with mine safety standards and dynamic updating of air volume calculation model, can adjust the air volume calculation according to the real-time air flow data, ensures the accuracy and real-time of the calculation results, and ensures the safety and reliability of underground ventilation. This algorithm can accurately calculate the underground coal mine ventilation air volume, compared with the traditional method, it improves the accuracy and calculation rate of air volume calculation, and reduces the error.

[0025] Step S4: Air flow direction determination.

[0026] From the air inlet of the underground ventilation system, traverse all the subsequent roadways, mark the positive direction of the air flow, for each roadway, check its air volume relationship with the next roadway; if the air flow direction flows from the air inlet roadway to the air used roadway and finally to the air return roadway, and meets the expectation, the air flow direction is normal; otherwise, the air flow direction is abnormal. Specifically includes: Step S41: Initial direction marking and air inlet traversal: starting from the air inlet (such as “auxiliary shaft mouth”), traverse all roadways level by level, mark the air flow direction; first, define the data structure: let G=(V,E) represent the node set (roadway intersection point or end) and the edge set (roadway connection relationship); each edge e E contains attributes source and target, representing the start and end of the edge; starting from the air inlet v0 E, traverse the graph G through depth-first search (DFS), construct the generated tree T, and record all the branches E\T for subsequent closed loop detection; through recursive traversal, ensure that all roadways are covered, and at the same time prevent circular traversal through the path stack.

[0027] Step S42: Air flow direction relationship determination: check the connection relationship between the current roadway and the next roadway to determine the positive and negative of the air flow direction; let the current edge be e i =( v a , v b ), the next edge be e j =( v c , v d ), determine the positive and negative of the air flow direction by judging the relationship between the two edges; define the relationship value t ij as: .

[0028] Through this method, the system can accurately determine the positive and negative relationship of the air flow direction, providing a basis for subsequent air volume correction.

[0029] Step S43: Airflow direction correction and anomaly detection.

[0030] Adjust the airflow sign based on the relationship value, and detect and correct abnormal directions. Let the current airflow in the roadway be... Q i ,like Q i <0 indicates that the airflow direction is opposite to the expected direction, and its sign needs to be corrected; .

[0031] Step S44: Verification of the self-consistency of closed loops: Ensure that the airflow direction of all closed loops (independent loops) is self-consistent to avoid contradictions; let the closed loop C = {e1, e2, ..., e k}, where each edge e i The air volume is Q i Wind resistance is r i The relation value is t i The backtracking algorithm is used to traverse all possible edge combinations to verify whether their airflow and direction satisfy the self-consistency condition. The self-consistency condition is that the algebraic sum of the airflow of all edges within the closed loop approaches zero (considering floating-point precision error), and the formula is: .

[0032] This method allows the system to verify the physical consistency of the airflow direction within the closed loop, ensuring the correctness of the airflow direction.

[0033] The airflow direction determination is achieved by establishing an airflow detection model to ensure that the ventilation direction of each roadway matches the expected airflow direction, and to provide alarm prompts for abnormal situations. Through step S4, compared with traditional methods, not only can the ventilation direction of each roadway be ensured to meet expectations, but alarm prompts can also be provided for abnormal situations, which helps to promptly detect and resolve ventilation problems and ensure underground ventilation safety.

[0034] Step S5: Front-end display.

[0035] The calculated downhole ventilation data is imported into a Java-based air network calculation platform, and visualized using a front-end 3D model and three.js. This allows for real-time monitoring of downhole ventilation and the generation of airflow diagrams in real-time using the AntV visualization platform's G6 engine. Specifically, this includes: Step S51: Incremental Data Encoding and Transmission: To achieve real-time updates and efficient transmission of downhole ventilation data, differential encoding technology is used, transmitting only the changed data portions, rather than the entire dataset. The mathematical representation of differential encoding is: Let the current dataset be D...t The previous time data set is D t-1 The difference data transmitted is Through this incremental encoding method, the network transmission load can be significantly reduced, and the real-time performance can be improved. In addition, combined with time series analysis, the encoding granularity is dynamically adjusted (such as increasing the sampling rate when the frequency of change is high), and a compression algorithm (such as LZ77) is introduced to further optimize the transmission efficiency. This technology not only reduces the amount of data transmission, but also ensures the real-time performance and integrity of the data, and is particularly suitable for the scene of the dynamic and frequent change of the underground ventilation system.

[0036] Step S52: three.js-based 3D model data mapping: In order to map the underground ventilation data to the pre-established 3D model, use the three.js framework for data binding and rendering; three.js is a WebGL-based JavaScript 3D graphics library that can efficiently render complex 3D scenes; In this step, the pre-established 3D model already contains the geometric structure and spatial position information of the underground roadway, and the nodes (roadway intersection points) and edges (roadway connections) have been defined in the model; By binding the nodes and edges data generated by the backend with the corresponding parts in the 3D model, dynamically update the air volume, airflow direction and other attributes in the model; For example, air volume data can be visually displayed in the 3D model through color gradient or line width change, and airflow direction is represented by dynamic particle effect; In order to improve the rendering efficiency and user experience, introduce the level of detail (LOD) technology, dynamically adjust the rendering details of the model according to the viewing distance; For example, when the user is far away from a certain area, a simplified model is rendered; When the user is close, a more detailed model is rendered; In addition, support user interactive operations (such as rotation, scaling, clicking to view roadway details), so that the operator can more intuitively understand the layout and ventilation of the underground roadway.

[0037] Step S53: AntV G6-based airflow chart generation: In order to generate a real-time underground airflow chart and display air volume distribution and airflow direction, use the AntV G6 engine to generate a 2D airflow chart; AntV G6 is a JavaScript library focused on graph visualization, which can efficiently render complex graph structures; In this step, nodes represent roadway intersection points, edges represent roadway connections, and edge attributes (such as line width, color) dynamically map air volume data; Airflow direction is represented by directional edge arrows, and abnormal airflow (such as reverse) is highlighted; In order to more intuitively display air volume data, introduce air volume gradient mapping, map air volume data Q to edge attributes, for example, the calculation formula of line width is Wherein k and b are mapping coefficients; in this way, the operator can quickly identify the roadway with large air volume, and timely adjust the ventilation system; in addition, the dynamic updating of the air flow map is supported, the underground ventilation state is reflected in real time, and the real-time and accuracy of monitoring are ensured.

[0038] The present application combines the Scott-Hinsley algorithm and the minimum spanning tree algorithm, and innovatively improves the process of finding the minimum loop of the minimum spanning tree algorithm, accurately calculates the underground coal mine ventilation air volume, improves the efficiency and accuracy of air volume calculation, and the process of establishing a topological graph, combining algorithm calculation, determining the air flow direction and visual display is coherent and simple, and efficient optimization management of the underground ventilation system is realized; the present application not only improves the accuracy and calculation rate of air volume calculation, reduces errors, but also provides intelligent interactive operation for mine ventilation management, effectively ensures the safety of underground operating personnel; through the implementation of the present application, the ventilation management efficiency of the underground coal mine can be significantly improved, the safety of the coal mine operating environment is ensured, and the present application has a wide application prospect; The system constructed by the present application is a mine intelligent ventilation management system; specifically comprising: 1、System architecture and device configuration; as shown in the figure, Figure 2 The system specifically comprises: (1) Data acquisition layer: this layer is mainly composed of various data acquisition stations in the mine for receiving sensor data (such as temperature, humidity, wind speed, air volume, etc.); the sensor uploads the real-time collected data to the wind network solving platform server, providing basic data for subsequent air volume calculation and monitoring.

[0039] (2) Data processing layer: in the data processing layer, the server is responsible for running the algorithm of the present application, including Scott-Hinsley algorithm and minimum spanning tree algorithm, for calculating the air volume distribution of each roadway in the mine; this layer utilizes efficient data processing and storage capacity to ensure the real-time and accuracy of large-scale data calculation.

[0040] (3) Visualization layer: the wind network solving platform based on Java development is used, and the 3D model and three.js technology are combined for data visualization display; the platform can real-time display the state of the underground ventilation system, including the air flow direction, air volume distribution of each roadway and the overall operation of the ventilation system.

[0041] 2, 3D model establishment and roadway relationship annotation of underground roadway.

[0042] Before realizing the air volume calculation, a detailed 3D model of the underground coal mine roadway needs to be established, and the connection relationship between the roadways is annotated; by identifying each roadway node and the channel connection of adjacent roadways in the 3D model, the topological structure of the underground ventilation system is constructed; specifically comprising: Through scanning, measuring and other means to establish the 3D model of the underground roadway.

[0043] The position of the main air path is determined, and the connection relationship between the roadways is identified to form a complete roadway relationship topology graph, which serves as the basis data for subsequent air volume calculation.

[0044] Through the construction of the 3D model, accurate geometric data can be provided for subsequent air flow calculation, and support can be provided for the visualization display of air volume distribution.

[0045] 3. The minimum spanning tree algorithm obtains the minimum loop.

[0046] The minimum spanning tree algorithm is applied to analyze the roadway relationship graph to find all the minimum loops in the underground ventilation system. The minimum spanning tree algorithm can identify the loops that may exist in the underground system.

[0047] The minimum spanning tree algorithm analyzes the connection relationship between the roadways, finds the lowest cost loop structure, and outputs all the minimum loops. This information provides an important basis for subsequent air volume calculation, optimizes air volume distribution, and ensures the stable operation of the ventilation system. In this step, the innovative mathematical method in the present application is fully utilized to improve the efficiency and accuracy of finding the minimum loop.

[0048] 4. Substitute into the Scott-Hinsley algorithm for iterative calculation.

[0049] The minimum loops identified by the minimum spanning tree algorithm are substituted into the Scott-Hinsley algorithm for iterative calculation of air volume. The Scott-Hinsley algorithm repeatedly optimizes the calculation of air volume distribution by considering the air flow relationship.

[0050] In each iteration, the air flow distribution is continuously adjusted according to the known air volume and loop conditions, and finally the accurate air volume data of each roadway is obtained. These calculation results can help ventilation management personnel understand the ventilation conditions of each roadway and timely adjust the air flow.

[0051] 5. Calculate the air flow direction.

[0052] By judging the direction of the air flow, it is ensured that the air flow direction of each roadway in the underground is from the air inlet roadway to the air consumption roadway and finally to the air return roadway, preventing the air flow from flowing in the opposite direction.

[0053] Starting from the air inlet, all adjacent roadways are traversed to mark the forward direction of the air flow. By checking the flow of air volume, it is determined whether the air flow meets the expectations. If the air flow direction is abnormal, the system will timely alarm and trigger the corresponding processing measures.

[0054] 6. Subsequent processing after the occurrence of reverse air.

[0055] When the system detects abnormal wind flow direction (such as reverse wind phenomenon), the platform will automatically trigger the alarm mechanism and prompt the operator to make adjustments; including: (1) Adjust the air volume distribution of the ventilation system to correct the wind flow direction.

[0056] (2) Check the air volume of the affected roadway to ensure normal air circulation.

[0057] (3) Record abnormal data and analyze to prevent similar problems from recurring.

[0058] 7. Subsequent processing after the occurrence of roadway blockage.

[0059] When there is a roadway blockage (such as collapse, equipment failure, etc.) underground, the wind flow will be affected, and the ventilation system may fail; the system can monitor and judge the blocked area in real time and respond accordingly; including: (1) Contact relevant personnel to clean up the blockage.

[0060] (2) If the blockage area seriously affects ventilation, start the emergency ventilation device to ensure safe ventilation.

[0061] (3) Through the visual information provided by the system, the operator can quickly understand the blockage situation and take necessary measures.

[0062] 8. Monitoring and feedback.

[0063] Through the 3D model and real-time data of the front-end display platform, the operator can continuously monitor the status of the underground ventilation system; the system will provide real-time feedback based on the calculation results, including air volume distribution, wind flow direction, and abnormal warning information, and use the G6 engine of the AntV visualization platform to generate wind flow charts in real time. Including:

[0064] (1) The monitoring platform can display wind flow charts, ventilation path charts, etc. to help operators make quick adjustment decisions.

[0065] (2) Real-time updating and feedback of data ensure the flexibility and responsiveness of mine ventilation management, improving the safety of underground coal mine operations.

[0066] The underground coal mine ventilation solving method based on the Scott-Hinsley algorithm and the minimum spanning tree algorithm of the present invention can significantly improve the ventilation management efficiency of underground coal mines, optimize the air volume distribution of the ventilation system, and ensure the safety of the coal mine operation environment; through intelligent wind flow direction determination and abnormal warning mechanism, combined with real-time monitoring and data visualization technology, further improve the flexibility and response capability of mine ventilation management.

[0067] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be noted that for ordinary skilled persons in the art, without departing from the concept of the present application, several modifications and improvements can be made, which are within the scope of protection of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for determining ventilation volume in underground coal mines, characterized in that, Includes the following steps: Collect the location and connection relationships of all underground roadways in the coal mine, and establish a roadway relationship topology map; The minimum spanning tree algorithm is used to construct the topology graph into a multi-level breadth-first spanning tree with multiple redundant branches in each level, and then the priority weight is determined according to the level to which the redundant branches belong. Starting with the branch with the lowest priority weight, search for connected branches in the tree in turn, iterating through multiple rounds until returning to the starting point, forming a unidirectional loop; repeat this process to obtain multiple loops containing this lowest priority branch. Extract the closed loop with the fewest and equal number of redundant branches from multiple loops. At the same time, dynamically set the weights according to the number of times each redundant branch appears in the loop, and select the loop with the smallest sum of weights of each redundant branch as the minimum loop of the roadway. By combining the roadway connections and the location of ventilation equipment, a wind direction matrix representing the positive and negative directions of airflow is determined; the air volume sign of each roadway in the minimum loop is adjusted according to the matrix, and abnormal airflow directions are corrected through iterative calculation to ensure that they conform to the actual ventilation conditions. The air volume of the minimum loop is calculated to obtain the ventilation air volume in the coal mine.

2. The method for determining ventilation volume in underground coal mines according to claim 1, characterized in that, The determination of the priority weights of each remaining branch in the breadth-first spanning tree includes: The topology of the lane relationships is constructed as a breadth-first spanning tree, and the number of layers of each vertex in the breadth-first spanning tree is determined. The priority of the remaining branches in a breadth-first spanning tree is defined as the sum of the vertex levels. Let the level of vertex v be 1. L ( v For the co-branch e=(u,v), its priority weight ,in Represents vertices u The level in the breadth-first search tree; in the breadth-first search tree, the length of the closed loop formed by any remaining branch e=(u,v) is higher than... ,according to W ( e Sort the remaining branches in ascending order and obtain the priority weight of each remaining branch in the breadth-first spanning tree.

3. The method for determining ventilation volume in underground coal mines according to claim 2, characterized in that, The acquisition of the minimum circuit includes: Extract multiple closed loops with the fewest and equal numbers of residual branches from multiple loops; For any cobranch e=(u,v) within a Sogian closed loop, the dynamic weight of the cobranch is defined as follows: ,in , To adjust the parameters, Degree ( v ) is the vertex v The degree, Degree ( u ) is the vertex u The degree; The closed loop with the smallest sum of the weights of the remaining branches among multiple closed loops is taken as the minimum loop in the roadway.

4. The method for determining ventilation volume in underground coal mines according to claim 3, characterized in that, After obtaining the ventilation volume in the coal mine, the airflow direction in each roadway is determined, including: Construct a directed graph G=(V,E), where the vertex set V is the intersection of alleyways, the edge set E is the connection between alleyways, and each edge contains the attributes (source, target, windVolume). Starting from the air inlet V0, use depth-first search to traverse the graph G, generate the traversal path stack P, and mark the spanning tree edge set T and the remaining branch set R=E\T. Set the current edge of the alleyway to e. i =( v a , v b The next edge is e. j =( v c , v d The sign of the current airflow direction in the tunnel is determined by judging the relationship between two edges; the relationship value... t ij for: ； Define an initial air volume symbol matrix S, based on t ij Update the symbol to make Q i '=Q i ×S i Calculate the self-consistency index for each closed loop C. ,like If this is the case, a correction will be triggered, where ε represents the preset threshold and r i Indicates wind resistance, t i Represents the relational value, when Q i When the airflow direction is less than 0, the edge attributes are reversed and updated until... ; For the remaining branch e=(u,v)∈R, based on the difference in the number of levels in the spanning tree Verify the direction: when ΔL=1, it should be u→v; when ΔL=-1, it should be v→u. If there is a contradiction, forcibly correct the air volume sign and record the anomaly.

5. The method for determining ventilation volume in underground coal mines according to claim 4, characterized in that, Once the airflow direction of each roadway is determined, a 2D airflow map of the coal mine is generated, where nodes represent roadway intersections, edges represent roadway connections, and edge attributes dynamically map airflow data; airflow direction is indicated by directed edge arrows, and abnormal airflow is displayed with high brightness.

6. A coal mine underground ventilation volume determination system, characterized in that, include: The data acquisition module is used to collect the location and connection relationships of all underground roadways in the coal mine and establish a roadway relationship topology map; The minimum spanning tree algorithm is used to construct the topology graph into a multi-level breadth-first spanning tree with multiple redundant branches in each level, and then the priority weight is determined according to the level to which the redundant branches belong. The loop detection module is used to start from the branch with the smallest priority weight, search for connected branches in the tree in turn, and iterate through multiple rounds until returning to the starting point to form a unidirectional loop; repeat this process to obtain multiple loops containing this branch with the smallest weight. Extract the closed loop with the fewest and equal number of redundant branches from multiple loops. At the same time, dynamically set the weights according to the number of times each redundant branch appears in the loop, and select the loop with the smallest sum of weights of each redundant branch as the minimum loop of the roadway. The air volume calculation module is used to determine the airflow direction matrix that represents the positive and negative directions of airflow by combining the roadway connection and the location of ventilation equipment; adjust the air volume sign of each roadway in the minimum loop according to the matrix, correct abnormal airflow direction through iterative calculation to ensure that it conforms to the actual ventilation state, calculate the minimum loop air volume, and obtain the ventilation air volume in the coal mine.

7. An electronic device, characterized in that, include: Memory and processor; The memory is used to store computer programs; When the processor executes the computer program stored in the memory, it implements the steps of the method for determining the ventilation volume in a coal mine as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, Used to store a computer program, which, when executed by a processor, implements the steps of a method for determining ventilation volume in a coal mine as described in any one of claims 1 to 5.

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