A coal mine underground ventilation volume determination method, system, device and medium

Abstract

The application discloses a kind of coal mine underground ventilation air volume determination method, system, equipment and medium, it is related to coal mine ventilation management technical field, the present application is when looking for minimum loop, with the level of tree node in breadth-first spanning tree as weight factor, determine each branch priority weight, start searching and build multiple loops from the weight minimum branch, extract the closed loop of least branch quantity;Simultaneously according to the number of branch, set dynamic weight, select the minimum of the sum of branch weight in loop as minimum loop, ensure that the roadway air volume calculated is consistent with actual value.In addition, the direction of air flow is determined by edge relationship, the sign of air volume is adjusted and the abnormal direction is corrected, so that the calculated direction of air flow is consistent with actual value.

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 coal mine underground ventilation air volume determination method, system, device and medium, which can solve the problem that in the prior art, when the minimum loop of the current underground roadway relationship is searched, the result of the searched minimum loop is highly dependent on the weight of the edge, if the weight information is inaccurate or has errors, the generated minimum spanning tree is not optimal, and when the weight information of the edge is set, it is usually randomly set, so that the searched minimum loop is not the minimum loop of the current underground roadway relationship, thereby causing a large error between the calculated air volume and the actual air volume.

[0006] The embodiment of the present application provides a coal mine underground ventilation air volume determination method, system, device and medium, which can solve the problem that in the prior art, when the minimum loop of the current underground roadway relationship is searched, the result of the searched minimum loop is highly dependent on the weight of the edge, if the weight information is inaccurate or has errors, the generated minimum spanning tree is not optimal, and when the weight information of the edge is set, it is usually randomly set, so that the searched minimum loop is not the minimum loop of the current underground roadway relationship, thereby causing a large error between the calculated air volume and the actual air volume.

[0007] Collect the positions and connection relationships of all roadways in the coal mine underground, and establish a roadway relationship topology graph; the minimum spanning tree algorithm is used to construct the topology graph 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 to which the branch belongs;

[0008] Taking the branch with the minimum priority weight as the starting point, the connected branches in the tree are searched in turn, and after multiple rounds of iteration, the starting point is returned, forming a one-way loop; the process is repeated to obtain multiple loops containing the branch with the minimum weight;

[0009] The closed loop with the least number of branches and equal number of branches is extracted from the multiple loops, and the weight of each branch in the loop is dynamically set according to the number of appearances, and the sum of the weights of each branch is selected as the minimum loop of the roadway.

[0010] Determine the air flow direction matrix representing the positive and negative directions of the air flow in combination with the connection of the roadways and the positions of the ventilation equipment; adjust the air volume signs 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 of the coal mine underground.

[0011] Preferably, the priority weight of each branch in the breadth-first spanning tree is determined, comprising:

[0012] The roadway relationship topology graph is constructed into a breadth-first spanning tree, and the number of layers of each vertex in the breadth-first spanning tree is determined;

[0013] The priority of the branch in the breadth-first spanning tree is defined as the sum of the number of layers of the vertex, and the number of layers of the vertex v is set as L ( v ), and for the branch e=(u,v), the priority weight is , wherein represents the number of layers of the 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 , and the priority weight of the branch is set asW e )ascending order of the branches, obtaining the priority weight of each branch in the breadth-first spanning tree.

[0014] Preferably, the minimum circuit obtaining comprises:

[0015] extracting a plurality of closed circuits with the least number of branches and equal number of branches in the plurality of circuits;

[0016] For any branch e=(u,v) in the Sorge closed circuit, the branch dynamic weight is defined as wherein , is an adjustment parameter, Degree v is the degree of vertex v , Degree u is the degree of vertex u ;

[0017] The closed circuit with the smallest sum of branch weights in the plurality of closed circuits is taken as the minimum circuit in the roadway.

[0018] Preferably, after obtaining the ventilation volume of the underground coal mine, the air flow direction of each roadway is determined, comprising:

[0019] A directed graph G=(V,E) is constructed, wherein the vertex set V is the intersection point 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, the graph G is traversed by depth-first search to generate a traversal path stack P and mark the spanning tree edge set T and the branch set R=E\T;

[0020] The current edge of the roadway is set as e i ( v a , v b ), the next edge is e j ( v c , v d ), and the positive and negative of the current air flow direction of the roadway is determined by judging the relationship of the two edges; the relationship value t ij is:

[0021] ;

[0022] An initial air volume sign matrix S is defined, and the sign is updated according to t ij , so that Q i '=Q i ×S i ​​​; calculate self-consistency index for each closed loop C , if (pre-set threshold) triggers correction, r i represents wind resistance, t i represents the relationship value, when Qi'<0, the wind flow direction is reversed and the edge attribute is updated until ;

[0023] For the remaining branch e=(u,v)∈R, according to the layer difference in the spanning tree Check the direction, ΔL=1 should be u→v, ΔL=-1 should be v→u, and if there is a contradiction, the wind volume sign is forced to be corrected and the exception is recorded.

[0024] Preferably, after the wind flow direction of each roadway is determined, a 2D wind flow map of the underground coal mine is generated, wherein the nodes represent the intersection points of the roadways, the edges represent the connections of the roadways, and the edge attribute dynamically maps the wind volume data; the wind flow direction is indicated by the directional edge arrow, and the abnormal wind flow is displayed by high brightness.

[0025] The embodiment of the present application also provides a coal mine underground ventilation air volume determination system, comprising:

[0026] A data acquisition module is configured to acquire the positions and connection relationships of all the roadways in the underground coal mine, 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 to which the remaining branches belong;

[0027] 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.

[0028] The remaining branches with the least number and equal number of closed loops are extracted from the multiple loops, the weights of the remaining branches are dynamically set according to the number of occurrences of each remaining branch in the loop, and the minimum loop of the roadways is selected as the remaining branch with the minimum sum of weights.

[0029] An air volume calculation module is configured to determine a wind flow direction matrix representing the positive and negative directions of the wind flow in combination with the connection of the roadways and the positions of the ventilation equipment; adjust the wind volume signs of the roadways in the minimum loop according to the matrix, correct the abnormal wind 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 of the underground coal mine.

[0030] The embodiment of the present application also provides an electronic device comprising a memory and a processor.

[0031] The memory is configured to store a computer program.

[0032] The processor is used for realizing the steps of the coal mine underground ventilation volume determination method when executing the computer program stored in the memory.

[0033] The embodiment of the present application further provides a computer readable storage medium for storing a computer program, and the computer program is executed by the processor to realize the steps of the coal mine underground ventilation volume determination method.

[0034] The embodiment of the present application provides a coal mine underground ventilation volume determination method, system, device and medium, and has the following beneficial effects compared with the prior art.

[0035] When the minimum loop of the coal mine underground roadway relationship is searched, the present application uses the branch priority function based on the layer weight to determine the branch priority of the breadth-first spanning tree after the breadth-first spanning tree is generated by using the minimum spanning tree algorithm, and simultaneously adjusts the dynamic weight of the branch with the minimum dynamic weight to be preferentially selected to search and construct the loop, so that the minimum loop is obtained. When the minimum loop of the underground roadway relationship is searched, the present application determines the priority weight of each branch in the breadth-first spanning tree by taking the layer of the tree node in the breadth-first spanning tree as the weight factor, starts the loop search from the branch with the minimum priority weight and constructs multiple loops including the branch with the minimum priority weight, extracts multiple closed loops with the minimum branch number and the equal branch number from the multiple loops, sets the dynamic weight of the branch according to the size of the branch number during the loop search, and takes the loop with the minimum sum of the weights of the branches in the loop as the minimum loop in the roadway, so that the dynamic weight adjustment and optimization of the branch in the breadth-first spanning tree are realized, the obtained loop is the minimum loop of the current underground roadway relationship, and thus the calculated ventilation volume of the coal mine underground roadway is consistent with the actual ventilation volume. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 The present application provides a coal mine underground ventilation volume determination method, and the overall flowchart of the coal mine underground ventilation volume determination method is shown in the figure.

[0037] Figure 2 The system architecture diagram of the coal mine underground ventilation volume determination method is shown in the figure. DETAILED DESCRIPTION

[0038] In order to make the above objects, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described in detail below. In the following description, a large number 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 concept of the present application, so the present application is not limited to the specific embodiments disclosed below.

[0039] Referring to Figure 1 , the embodiment of the present application provides a coal mine underground ventilation volume determination method, comprising the following steps:

[0040] Step S1: establishing a relationship topology graph between underground roadways and marking a main airway.

[0041] The relationship topology 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 topology graph of the underground roadway is constructed by manual marking data, combined with the calibration of the geographical position of the roadway, to ensure that the established topology relationship has accurate spatial position association.

[0042] Step S2: finding all minimum loops in the relationship of the underground roadway by a minimum spanning tree algorithm; specifically comprising:

[0043] Step S21: a remaining branch priority function based on 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 ), for the remaining branch e=(u,v), the priority weight of the remaining branch 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 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 preferentially, so that the minimum length closed loop can be found preferentially, and the search depth can be effectively reduced.

[0044] Step S22: dynamic weight adjustment and greedy strategy. After determining the initial priority of the remaining branch based on the layer 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 can be connected to more potential loops, by this way of dynamically adjusting the priority, combined with the greedy algorithm, the remaining branches with small dynamic weights are preferentially selected for processing, so that the search process is more targeted, and the search efficiency is further improved.

[0045] Step S23: Closed loop uniqueness judgment and canonical representation. After processing the branches according to the adjusted priority and finding the closed loop by DFS, the uniqueness judgment and canonical representation are performed on the closed loop to avoid repeated calculation; for a closed loop C = {v0, v1, …, v k-1}, its canonical form is defined as , where Rotate ( C, θ ) represents the arrangement after rotating the loop 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 loop 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 loop, so that the found closed loop can be automatically de-duplicated when stored in the set.

[0046] Step S24: Loop space decomposition based on algebraic topology. In the process of continuously finding and normalizing the closed loop, the loop space decomposition theory based on algebraic topology is used to ensure that the found closed loop is comprehensive and accurate; the concept of loop space in algebraic topology is introduced, and the loop space of a graph is the linear space of the edge set, whose basis is composed of independent closed loops; let the branch set be T and the spanning tree be S, each branch e∈T corresponds to a unique loop Ce ∈Cycle Space, and the independent closed loop set ; by proving algebraic independence, it is ensured that the set constitutes a basis of the loop space, theoretically guaranteeing that all found closed loops are independent and can cover all minimum independent closed loops.

[0047] Step S25: Algorithm convergence and time complexity analysis. In the process of searching for the minimum independent closed loop, the convergence of the algorithm is proved by mathematical induction; the induction basis is that when the number of branches is 1, the algorithm finds a unique closed loop by DFS; the induction hypothesis is that the algorithm can correctly find all independent closed loops for n branches; the induction step is to process each branch according to the above adjusted priority and search for closed loops using DFS for n+1 branches; since each branch belongs to only one independent loop (by the spanning tree property), the algorithm gradually reduces the number of unprocessed branches; according to the spanning tree property, each branch belongs to only one independent loop, so the algorithm can eventually cover all independent closed loops as the process progresses; in terms of time complexity, let the graph have V vertices and E edges, the spanning tree have V-1 edges, and the number of 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 branches and controlling the number of layers, significantly improving the efficiency.

[0048] 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 combined algorithm can accurately calculate the underground coal mine ventilation air volume, compared with the traditional method, improves the accuracy and calculation rate of air volume calculation, and reduces the error.

[0049] Step S4: Air flow direction determination.

[0050] Starting from the air inlet of the underground ventilation system, all subsequent roadways are traversed, and the positive direction of the air flow is marked. 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, it includes:

[0051] Step S41: Initial direction marking and air inlet traversal: starting from the air inlet (such as “auxiliary shaft mouth”), all roadways are traversed level by level, and the air flow direction is marked; 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 the attributes source and target, representing the start and end of the edge; starting from the air inlet v0∈V, traverse the graph G through depth-first search (DFS), construct the spanning 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.

[0052] 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 ), and 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:

[0053] .

[0054] 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.

[0055] Step S43: Air flow direction correction and anomaly detection.

[0056] According to the relationship value, adjust the air volume symbol, detect and correct the abnormal direction. Set the current air volume of the roadway as Q i , if Q i <0, it means that the air flow direction is opposite to the expected one, and the symbol needs to be corrected;

[0057] .

[0058] Step S44: Verification of self-consistency of closed loop: Ensure the air flow direction of all closed loops (independent circuits) is self-consistent, avoiding contradictions; set the closed loop C = {e1, e2, …, en}, where the air volume of each edge e k i is Q i , the air resistance is r i , and the relationship value is t i ; through the backtracking algorithm, traverse all possible edge combinations to verify whether the air volume and direction meet the self-consistency condition; the self-consistency condition is that the algebraic sum of the air volume of all edges in the closed loop tends to zero (considering the floating point precision error), and the formula is:

[0059] .

[0060] Through this method, the system can verify the physical consistency of the air flow direction in the closed loop, ensuring the correctness of the air flow direction.

[0061] The air flow direction determination establishes an air flow detection model to ensure that the ventilation direction of each roadway conforms to the expected air flow direction, and to alarm and prompt abnormal situations; through step S4, compared with the traditional method, not only can the ventilation direction of each roadway conform to the expectation, but also can alarm and prompt abnormal situations, which helps to discover and solve ventilation problems in time, ensuring the safety of underground ventilation.

[0062] Step S5: Front-end display.

[0063] Import the calculated underground ventilation data into the wind network solving platform developed based on Java, and cooperate with the front-end 3D model and three.js for visual display, real-time monitoring of underground ventilation, and real-time generation of air flow chart using the G6 engine of the AntV visualization platform; specifically including:

[0064] ​Step S51: Incremental data encoding and transmission: To achieve real-time updating and efficient transmission of downhole ventilation data, the Delta Encoding technique is used, which only transmits the changed data part instead of the full data. The mathematical representation of Delta Encoding is as follows: Let the current data set be D t , the last time data set be D t-1 , then the transmitted difference data is D ; Through this incremental encoding method, network transmission load can be significantly reduced, and 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 compression algorithms (such as LZ77) are introduced to further optimize transmission efficiency; This technology not only reduces the amount of data transmission, but also ensures the real-time and integrity of the data, especially suitable for the scene of downhole ventilation system which changes frequently.

[0065] Step S52: 3D model data mapping based on three.js: To map the downhole 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 downhole tunnel, and the nodes (tunnel intersection points) and edges (tunnel 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, air flow 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 changes, and air flow direction is represented by dynamic particle effects; In order to improve rendering efficiency and user experience, introduce 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 tunnel details), so that the operator can more intuitively understand the layout and ventilation of the downhole tunnel.

[0066] Step S53: AntV G6-based air flow chart generation: in order to generate a downhole air flow chart in real time, show the air volume distribution and air flow direction, use the AntV G6 engine to generate a 2D air flow chart; AntV G6 is a JavaScript library focusing on graph visualization, which can efficiently render complex graph structures; in this step, nodes represent roadway intersections, edges represent roadway connections, and edge attributes (such as line width, color) dynamically map air volume data; air flow direction is indicated by directional edge arrows, and abnormal air flow (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 , where k and b are mapping coefficients; in this way, the operator can quickly identify the roadway with a large air volume and adjust the ventilation system in a timely manner; in addition, dynamic updating of the air flow chart is supported, which reflects the downhole ventilation state in real time, ensuring the real-time and accuracy of monitoring.

[0067] The present application accurately calculates the downhole coal mine ventilation air volume by combining the Scott-Hinsley algorithm and the minimum spanning tree algorithm and innovatively improving the process of finding the minimum loop of the minimum spanning tree algorithm, improves the efficiency and accuracy of air volume calculation, and the process of establishing a topological graph, performing combined algorithm calculation, determining air flow direction and visual display is coherent and simple, realizing efficient and optimized management of the downhole ventilation system; the present application not only improves the accuracy and calculation rate of air volume calculation and reduces errors, but also provides intelligent interactive operation for mine ventilation management, effectively ensuring the safety of downhole operating personnel; through the implementation of the present application, the ventilation management efficiency of the downhole coal mine can be significantly improved, the safety of the coal mine operating environment can be ensured, and the present application has a wide application prospect;

[0068] The system constructed by the present application is a mine intelligent ventilation management system; specifically comprising:

[0069] 1、System architecture and device configuration; as shown in the figure, Figure 2 , the system specifically comprises:

[0070] (1) Data acquisition layer: this layer is mainly composed of various downhole data acquisition stations 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.

[0071] (2) Data processing layer: in the data processing layer, the server is responsible for running the algorithm of the present application, including the Scott-Hinsley algorithm and the minimum spanning tree algorithm, for calculating the air volume distribution of each roadway in the downhole; this layer uses efficient data processing and storage capabilities to ensure the real-time and accuracy of large-scale data calculation.

[0072] (3) Visualization layer: use the Java-based wind network solution platform, combined with 3D model and three.js technology for data visualization; the platform can real-time display the state of underground ventilation system, including the air flow direction, air volume distribution of each roadway and the overall operation of the ventilation system.

[0073] 2. Underground roadway 3D model establishment and roadway relationship annotation.

[0074] Before air volume calculation, a detailed 3D model of underground coal mine roadway needs to be established first, and the connection relationship between roadways is annotated; by identifying each roadway node and adjacent roadway channel connection in the 3D model, the topological structure of the underground ventilation system is constructed; specifically including:

[0075] The 3D model of underground roadway is established by scanning, measuring and other means.

[0076] The position of the main airway is determined, and the connection relationship between roadways is identified, forming a complete roadway relationship topology diagram, which serves as the basis data for subsequent air volume calculation.

[0077] 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 of air volume distribution.

[0078] 3. Minimum spanning tree algorithm to obtain the minimum loop.

[0079] The minimum spanning tree algorithm is applied to analyze the roadway relationship diagram and 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.

[0080] The minimum spanning tree algorithm analyzes the connection relationship between each roadway, 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.

[0081] 4. Substitute Scott-Hinsley algorithm for iterative calculation.

[0082] Substitute the minimum loop identified by the minimum spanning tree algorithm into the Scott-Hinsley algorithm for iterative air volume calculation. The Scott-Hinsley algorithm repeatedly optimizes the air volume distribution by considering the air flow relationship.

[0083] In each iteration, the wind flow distribution is continuously adjusted according to the known wind volume and circuit conditions, and the accurate wind volume data of each roadway is finally obtained; these calculation results can help ventilation managers understand the ventilation conditions of each roadway and adjust the air volume in time.

[0084] 5. Calculate the direction of the air flow.

[0085] By judging the direction of the air flow, it is ensured that the air flow direction of each roadway underground is from the air inlet roadway to the air using roadway and finally to the air return roadway, preventing the air flow from flowing in reverse.

[0086] Starting from the air inlet, all adjacent roadways are traversed to mark the forward direction of the air flow; by checking the flow of the air volume, it is judged 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.

[0087] 6. Subsequent processing after the occurrence of reverse air.

[0088] When the system detects that the air flow direction is abnormal (such as the occurrence of reverse air phenomenon), the platform will automatically trigger the alarm mechanism and prompt the operator to adjust; specifically including:

[0089] (1) Adjust the air volume distribution of the ventilation system to correct the air flow direction.

[0090] (2) Check the air volume of the affected roadway to ensure normal air circulation.

[0091] (3) Record abnormal data and analyze to prevent similar problems from occurring again.

[0092] 7. Subsequent processing after the occurrence of roadway blockage.

[0093] When roadway blockage (such as collapse, equipment failure, etc.) occurs underground, the air flow will be affected, and the ventilation system may fail; the system can monitor and judge the blocked area in real time and respond; specifically including:

[0094] (1) Contact relevant personnel to clean the blockage.

[0095] (2) If the blockage area seriously affects ventilation, start the emergency ventilation device to ensure safe ventilation.

[0096] (3) Through the visual information provided by the system, the operator can quickly understand the blockage situation and take necessary measures.

[0097] 8. Monitoring and feedback.

[0098] 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 according to the calculation results, including air volume distribution, air flow direction and abnormal warning information, and use the G6 engine of the AntV visualization platform to generate a wind flow map in real time. Specifically, it includes:

[0099] (1) The monitoring platform can display the wind flow map and ventilation path map, helping the operator to make adjustment decisions quickly.

[0100] (2) Real-time updating and feedback of data ensure the flexibility and responsiveness of mine ventilation management, and improve the safety of underground coal mine operation.

[0101] The underground coal mine ventilation solving method based on the Scott-Hinsley algorithm and the minimum spanning tree algorithm can significantly improve the efficiency of underground coal mine ventilation management, optimize the air volume distribution of the ventilation system, and ensure the safety of the coal mine operation environment; through intelligent air flow direction determination and abnormal warning mechanism, combined with real-time monitoring and data visualization technology, the flexibility and response capability of mine ventilation management are further improved.

[0102] The above-described embodiments only express several embodiments of the present application, which are described in detail and specifically, but should not be understood as limiting 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, a number of modifications and improvements can be made, which are all 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 of determining the volume of air for underground ventilation in a coal mine, characterised by, The method comprises the following steps: Collecting the positions and connection relationships of all roadways in the coal mine underground, and establishing a roadway relationship topology graph; Using a 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 the priority weight of each branch in the breadth-first spanning tree is determined according to the level to which the branch belongs; Taking the branch with the minimum priority weight as the starting point, the connected branches are searched in the tree in turn, and a one-way loop is formed through multiple iterations until the starting point is returned; the process is repeated to obtain multiple loops containing the branch with the minimum weight; From the multiple loops, a closed loop with the least number of branches is extracted, and the weight of each branch in the loop is dynamically set according to the number of appearances of each branch in the loop, and the loop with the minimum sum of weights of each branch is selected as the minimum loop of the roadway; Combining the connection of the roadways and the positions of the ventilation equipment, a wind flow direction matrix representing the positive and negative directions of the wind flow is determined; the signs of the air volumes of the roadways in the minimum loop are adjusted according to the matrix, and the abnormal wind flow direction is corrected through iterative calculation to ensure that it conforms to the actual ventilation state, and the air volume of the minimum loop is calculated to obtain the ventilation air volume of the coal mine underground; The priority weight of each branch in the breadth-first spanning tree is determined, comprising: The roadway relationship topology graph is constructed into 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 branch in the breadth-first spanning tree is defined as the sum of the layer numbers of the vertex, and the layer number of the vertex v is set as L ( v ), and the priority weight of the remaining branch e=(u, v) is , wherein represents the layer number of the vertex u in the breadth-first spanning tree; in the breadth-first spanning tree, the length of the closed ring formed by any remaining branch e=(u, v) is higher than , and the remaining branches are arranged in ascending order according to W ( e ), and the priority weight of each remaining branch in the breadth-first spanning tree is obtained. The minimum loop is obtained, comprising: Extracting multiple closed loops with the least number of branches from the multiple loops; For any edge e = (u, v) in the SAGE closed loop, define the edge dynamic weight as where , is an adjustment parameter, Degree v is the degree of vertex v , Degree u is the degree of vertex u .​​ The closed loop with the minimum sum of weights of each branch in the multiple closed loops is selected as the minimum loop in the roadway; After obtaining the ventilation air volume of the coal mine underground, the wind flow direction of each roadway is determined, comprising: A directed graph G=(V,E) is constructed, wherein the vertex set V is the intersection of the roadways, and the edge set E is the connection of the roadways, and each edge contains the (source,target,windVolume) attribute; starting from the air inlet V0, the graph G is traversed using a depth-first search to generate a traversal path stack P and mark the spanning tree edge set T and the branch set R=E\T; The current edge of the roadway is e i =( v a , v b The next edge is e j =( v c , v d The positive and negative of the current airflow direction of the roadway is determined by judging the relationship between the two edges; the relationship value t ij is: ； Define initial air volume symbol matrix S according to t ij Update symbols to make Q i '=Q i ×S i ; For each closed loop C, calculate self-consistency index δC=Σ(t i ・r i ・(Q i ')²), if δC>ε, trigger correction, ε represents a preset threshold, r i represents wind resistance, t i represents the relationship value, when Q i '<0, reverse the air flow direction and update the edge attribute until δC≤ε; For the rest of the branches e = (u, v) ∈ R, according to the difference of the layer number in the spanning tree The check direction should be u→v when ΔL = 1 and v→u when ΔL = -1. If it is contradictory, the air volume sign is forced to be corrected and the exception is recorded.

2. The method for determining the ventilation volume of the underground coal mine according to claim 1, characterized in that, After the wind flow direction of each roadway is determined, a 2D wind flow graph of the coal mine underground is generated, wherein the nodes represent the intersections of the roadways, the edges represent the connections of the roadways, and the edge attributes dynamically map the air volume data; the wind flow direction is indicated by the arrows of the directed edges, and the abnormal wind flow is displayed by high brightness.

3. A coal mine underground ventilation volume determination system, which implements the coal mine underground ventilation volume determination method according to any one of claims 1-2, characterized in that, Comprise: A data acquisition module for acquiring the positions and connection relationships of all roadways in the coal mine underground, and establishing a roadway relationship topology graph; Using a 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 the priority weight of each branch in the breadth-first spanning tree is determined according to the level to which the branch belongs; A loop judgment module for taking the branch with the minimum priority weight as the starting point, searching the connected branches in the tree in turn, and forming a one-way loop through multiple iterations until the starting point is returned; the process is repeated to obtain multiple loops containing the branch with the minimum weight; From the multiple loops, a closed loop with the least number of branches is extracted, and the weight of each branch in the loop is dynamically set according to the number of appearances of each branch in the loop, and the loop with the minimum sum of weights of each branch is selected as the minimum loop of the roadway; The air volume solving module is used for determining an air flow direction matrix representing positive and negative directions of air flow in combination with the roadway connection and the position of the ventilation equipment; adjusting the air volume signs of each roadway in the minimum loop according to the matrix; correcting the abnormal air flow direction through iterative calculation to ensure the actual ventilation state; calculating the minimum loop air volume; and obtaining the underground mine ventilation air volume.

4. An electronic device, comprising: The method comprises the steps that: a memory and a processor are provided; the memory is used for storing a computer program; the processor is used for executing the computer program stored in the memory to realize the steps of the method for determining the underground mine ventilation air volume according to any one of claims 1-2.

5. A computer readable storage medium, characterized in that, The computer program is stored in the memory and is executed by the processor to realize the steps of the method for determining the underground mine ventilation air volume according to any one of claims 1-2.

Images