Safety comprehensive evaluation method of underground coal mine ventilation system based on network analysis

Abstract

The invention relates to the technical field of coal mine safety, in particular to a comprehensive safety evaluation method for an underground coal mine ventilation system based on network analysis, which comprises the following steps: performing air network calculation on a ventilation network corresponding to a to-be-evaluated mine ventilation system to obtain theoretical parameters of each node of the ventilation network, the theoretical parameters comprising a theoretical wind direction and a theoretical air volume; based on the theoretical wind direction of each node of the ventilation network, constructing a corresponding wind volume directed reachable matrix; calculating the air volume directed reachable matrix through a network analysis method, and determining a plurality of key evaluation areas of the ventilation network; and obtaining actual ventilation quantities corresponding to the plurality of key evaluation areas, and carrying out dynamic evaluation analysis processing on the to-be-evaluated mine ventilation system based on the theoretical ventilation quantities corresponding to the plurality of key evaluation areas. The problems that mine ventilation evaluation is high in cost, low in efficiency and long in consumed time are solved.

Description

Technical Field

[0001] This application relates to the field of coal mine safety technology, and more specifically, to a comprehensive safety evaluation method for underground ventilation systems in coal mines based on network analysis. Background Technology

[0002] The task of a mine ventilation system is to use ventilation power to provide high-quality and sufficient fresh air to various ventilation locations underground in the most economical way, so as to ensure the survival, safety and good working environment of underground workers.

[0003] Current mine ventilation system monitoring primarily involves installing gas extraction equipment, gas detectors, and fire monitoring systems to monitor parameters such as gas concentration and temperature within the mine. Once an anomaly is detected, an alarm is triggered promptly, and appropriate safety measures are taken to prevent accidents. However, this method cannot provide targeted assessments for different areas. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and medium for comprehensive safety evaluation of underground ventilation systems in coal mines based on network analysis, which can solve the problems of high cost, low efficiency, and long time consumption in mine ventilation evaluation. The technical solution is as follows:

[0005] Firstly, a comprehensive safety evaluation method for underground ventilation systems in coal mines based on network analysis is provided, the method comprising:

[0006] The ventilation network of the mine ventilation system to be evaluated is calculated to obtain the theoretical parameters of each node of the ventilation network, including theoretical wind direction and theoretical air volume.

[0007] Based on the theoretical wind direction of each node in the ventilation network, a corresponding directed reachability matrix for air volume is constructed.

[0008] The directed reachability matrix of air volume is calculated using network analysis to identify several key evaluation areas of the ventilation network.

[0009] The actual ventilation volume corresponding to multiple key evaluation areas is obtained, and the dynamic evaluation and analysis of the mine ventilation system to be evaluated is carried out based on the theoretical air volume corresponding to each of the multiple key evaluation areas.

[0010] Secondly, a comprehensive safety evaluation device for underground ventilation systems in coal mines based on network analysis is provided, the device comprising:

[0011] The ventilation network calculation module is used to calculate the ventilation network corresponding to the ventilation system of the mine to be evaluated, and obtain the theoretical parameters of each node of the ventilation network, including theoretical wind direction and theoretical air volume.

[0012] The reachability matrix determination module is used to construct the corresponding directed reachability matrix of air volume based on the theoretical wind direction of each node in the ventilation network.

[0013] The key area identification module is used to calculate the directed reachability matrix of air volume using network analysis to identify multiple key evaluation areas of the ventilation network.

[0014] The ventilation system evaluation module is used to obtain the actual ventilation volume corresponding to multiple key evaluation areas, and to perform dynamic evaluation and analysis of the mine ventilation system under evaluation based on the theoretical air volume corresponding to each of the multiple key evaluation areas.

[0015] A third aspect of this application discloses an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0016] A fourth aspect of this application discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0017] This application embodiment calculates the ventilation network corresponding to the ventilation system of the mine to be evaluated by performing wind network calculation, obtaining the theoretical parameters of each node in the ventilation network, including theoretical wind direction and theoretical air volume. Based on the theoretical wind direction of each node in the ventilation network, a corresponding directed reachability matrix of air volume is constructed. Through network analysis, multiple key evaluation areas of the ventilation network are determined using the directed reachability matrix of air volume, thereby obtaining the actual ventilation volume corresponding to each of the multiple key evaluation areas. Based on the theoretical air volume corresponding to each of the multiple key evaluation areas, the ventilation system of the mine to be evaluated is dynamically evaluated and analyzed. This method of obtaining the theoretical parameters of each area of ​​the mine to be evaluated by wind network calculation provides a theoretical basis for dynamic evaluation to compare with actual data. By using reference data and performing network analysis on the constructed directed reachability matrix of air volume to obtain key evaluation areas, the key evaluation areas are dynamically analyzed, making the evaluation results more targeted, shortening the time for dynamic evaluation of the ventilation system of the mine to be evaluated, and improving the safety of the ventilation system of the mine to be evaluated. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below.

[0019] Figure 1 A schematic diagram of the structure of the safety comprehensive evaluation method for underground ventilation systems in coal mines based on network analysis provided in this application embodiment;

[0020] Figure 2A schematic diagram of the ventilation network corresponding to the mine ventilation system to be evaluated, provided in an embodiment of the safety comprehensive evaluation method for underground ventilation systems in coal mines based on network analysis, as provided in this application.

[0021] Figure 3 A schematic diagram of the structure of the safety comprehensive evaluation device for underground ventilation system in coal mines based on network analysis provided in this application embodiment. Detailed Implementation

[0022] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0023] This application provides a comprehensive safety evaluation method for underground ventilation systems in coal mines based on network analysis, such as... Figure 1 As shown, the method includes steps S101 to S104.

[0024] Step S101: Perform ventilation network calculation on the ventilation network corresponding to the ventilation system of the mine to be evaluated, and obtain the theoretical parameters of each node of the ventilation network. The theoretical parameters include theoretical wind direction and theoretical air volume.

[0025] In this embodiment, each branch of the ventilation network represents a roadway and is defined by two nodes, each node representing the intersection of underground mine roadways. The direction of the branch indicates the direction of airflow, and its initial direction can be arbitrarily set. If a device for adjusting airflow is installed on a branch, it should be marked at the corresponding location on the diagram, such as... Figure 2 As shown. Furthermore, branch and node numbers should all start from 1 and increment sequentially in integer order.

[0026] Specifically, the ventilation network corresponding to the mine ventilation system to be evaluated can be determined by searching a pre-defined network lookup table containing the correspondence between mine ventilation systems and theoretical ventilation networks using the system's identification number. Alternatively, the ventilation network drawn by the user for the mine ventilation system to be evaluated can be obtained through a pre-defined interface.

[0027] Step S102: Based on the theoretical wind direction of each node in the ventilation network, construct the corresponding directed reachability matrix of air volume.

[0028] Step S103: Calculate the directed reachability matrix of air volume using network analysis to determine several key evaluation areas of the ventilation network.

[0029] Specifically, the directed reachability matrix of airflow can be calculated by loading a pre-compiled network analysis algorithm.

[0030] Step S104: Obtain the actual ventilation volume corresponding to multiple key evaluation areas, and perform dynamic evaluation and analysis on the ventilation system of the mine to be evaluated based on the theoretical air volume corresponding to each of the multiple key evaluation areas.

[0031] Specifically, the actual air volume and theoretical air volume of the key evaluation area are compared to determine whether there are any anomalies in the key evaluation area. For example, if the actual air volume and theoretical air volume of the key evaluation area are consistent, it indicates that there are no anomalies in the key evaluation area; otherwise, there are anomalies.

[0032] This application embodiment calculates the ventilation network corresponding to the ventilation system of the mine to be evaluated by performing wind network calculation, obtaining the theoretical parameters of each node in the ventilation network, including theoretical wind direction and theoretical air volume. Based on the theoretical wind direction of each node in the ventilation network, a corresponding directed reachability matrix of air volume is constructed. Through network analysis, multiple key evaluation areas of the ventilation network are determined using the directed reachability matrix of air volume, thereby obtaining the actual ventilation volume corresponding to each of the multiple key evaluation areas. Based on the theoretical air volume corresponding to each of the multiple key evaluation areas, the ventilation system of the mine to be evaluated is dynamically evaluated and analyzed. This method of obtaining the theoretical parameters of each area of ​​the mine to be evaluated by wind network calculation provides a theoretical basis for dynamic evaluation to compare with actual data. By using reference data and performing network analysis on the constructed directed reachability matrix of air volume to obtain key evaluation areas, the key evaluation areas are dynamically analyzed, making the evaluation results more targeted, shortening the time for dynamic evaluation of the ventilation system of the mine to be evaluated, and improving the safety of the ventilation system of the mine to be evaluated.

[0033] In some embodiments, step S103 further includes:

[0034] Based on the data of each node in the directed reachability matrix of air volume, the degree centrality of each node in the ventilation network is determined.

[0035] The importance coefficient of each node is determined based on the product of its degree centrality and its corresponding theoretical air volume.

[0036] The nodes are sorted in descending order according to their respective importance coefficients, and a predetermined number of nodes at the top of the sort are designated as key evaluation areas.

[0037] Specifically, the directed reachability matrix for airflow can be shown in Table 1. The table elements represent the reachable airflow from the starting point to the ending point; "-" indicates unreachable, and "0" indicates that the reachable airflow from the node to itself is 0. The node reachability relationships include: M3->M6, M5->M7, M8->M7, and M8->M6.

[0038] Table 1 - Directed Reachability Matrix of Nodal Airflow

[0039]

[0040] In this embodiment, degree centrality is used to characterize the number of edges a node is connected to in an associated ventilation network, which can reflect the node's activity and influence in the network.

[0041] Specifically, the formula for calculating degree centrality is: ,in, For nodes In-degree (number of air currents flowing towards the node). For nodes The outflow degree (the number of airflow streams exiting the node), where N is the number of nodes in the ventilation network. Figure 2 For example, the degree centrality of each node is shown in Table 2. It can be seen that... Figure 2 The in-degree and out-degree of nodes M1-M5 are both 1; the in-degree of nodes M6 and M7 is 2 and the out-degree is 1; the in-degree of node M8 is 1 and the out-degree is 2.

[0042] Table 2 - Nodal Degree Center Comparison Table

[0043]

[0044] Specifically, the importance coefficient of each node is obtained by combining the degree centrality (DC) of each node with its airflow. The importance coefficient... The calculation formula is: ,in, The importance coefficient of the Nth node. For the degree centrality of the Nth node, Let N be the theoretical air volume of the Nth node.

[0045] Specifically, this can be achieved by sorting the importance coefficients of each node in descending order and selecting the top 20% of nodes as the key evaluation areas (nodes), thus obtaining the key evaluation area list DM. , where k 0.2m corresponds to an importance coefficient of DI. The air volume data list is in DN. , where k 0.2m, where m is the total number of nodes and k 0.2m indicates that the top 20% of nodes with high degree centrality are selected.

[0046] In some embodiments, step S104 further includes:

[0047] Step S1041 (not shown in the figure): Obtain the real-time wind speed corresponding to multiple key evaluation areas;

[0048] Step S1042 (not shown in the figure): Calculate the product of the cross-sectional area and the corresponding real-time wind speed for each of the multiple key evaluation areas to obtain the actual air volume for each of the multiple key evaluation areas.

[0049] Step S1043 (not shown in the figure): When the actual air volume corresponding to any key evaluation area is inconsistent with the theoretical air volume of the corresponding node, calculate the corresponding relative air volume difference rate.

[0050] Step S1044 (not shown in the figure): Classify any key evaluation area according to the relative difference rate of air volume.

[0051] Specifically, after identifying the key evaluation areas, wind speed sensors can be deployed and installed in these areas for real-time wind speed monitoring. The wind speed is positive when the detected real-time wind direction matches the theoretical wind direction; otherwise, it is negative. The cross-sectional area at the deployment location of the wind speed and direction sensors is DA. , where k 0.2m, where m is the total number of nodes and k 0.2m indicates that the top 20% of nodes with high degree centrality are selected.

[0052] In some embodiments, step S1044 further includes:

[0053] If the relative difference rate of air volume in any key evaluation area is greater than the preset first threshold, then the key evaluation area is marked as having excessive air volume difference and added to the list of areas to be warned, so as to generate corresponding investigation suggestions.

[0054] If the relative difference rate of air volume in any key evaluation area is greater than the preset second threshold but not greater than the first threshold, then that key evaluation area is added to the preset list of areas to be optimized, so as to generate corresponding optimization suggestions.

[0055] Specifically, the real-time wind speed data for each key evaluation area obtained through wind speed sensors is RV. The real-time air volume, RN, is calculated based on the cross-sectional area of ​​each key evaluation area. ,in, .

[0056] Specifically, the real-time air volume of each key evaluation area is checked against the corresponding theoretical air volume for directional consistency. That is, if the actual wind direction is the same as the theoretical wind direction, the wind speed is positive; otherwise, it is negative. Therefore, the actual air volume calculated by multiplying the wind speed by the cross-sectional area can have positive or negative values. If the actual air volume and the theoretical air volume have opposite signs, it is identified as a major hidden danger and marked as an abnormal wind direction. When the conditions are met, the subsequent difference rate is calculated. The smaller the difference between the actual air volume and the theoretical air volume, the closer the ventilation effect is to the ideal effect.

[0057] Specifically, the relative difference rate of air volume can be calculated using the following formula: .

[0058] Specifically, it can be The key evaluation areas will be included in the list of areas to be warned (EW) and marked as having excessively large air volume differences; The key evaluation areas are included in the list of areas to be optimized (EO).

[0059] In some embodiments, after step S104, the method further includes:

[0060] Step S105 (not shown in the figure): Determine the importance coefficients corresponding to the multiple key evaluation areas and perform normalization processing to obtain the weight coefficients corresponding to the multiple key evaluation areas.

[0061] Step S106 (not shown in the figure): Based on the weight coefficients corresponding to the multiple key evaluation areas and their corresponding relative air volume differences, a weighted calculation is performed to obtain the overall difference rate of ventilation effect of the mine ventilation system to be evaluated.

[0062] In this embodiment of the application, the overall difference rate of ventilation effect is used to represent the difference rate between the theoretical air volume and the actual air volume of each key evaluation area (node) in the coal mine. The closer the overall difference rate of ventilation effect E is to 0, the closer the actual air volume is to the theoretical air volume; the larger the overall difference rate of ventilation effect E is, the larger the difference rate is.

[0063] Specifically, the importance coefficient (DI) of the key evaluation areas can be normalized using Softmax to obtain the weight coefficients. For example, the weight coefficients... ,and The relative difference rate of air volume in each key evaluation area is weighted and calculated with weighting coefficients to obtain the overall difference rate E of ventilation effect of the mine ventilation system under evaluation. .

[0064] In some embodiments, step S106 further includes:

[0065] The overall difference rate of ventilation effect of the mine ventilation system to be evaluated is classified into two categories using a preset algorithm, and the overall ventilation effect score of the mine ventilation system to be evaluated is determined based on the results of the binary classification.

[0066] The overall ventilation evaluation and analysis results for the mine ventilation system to be evaluated are determined based on the ventilation effect score.

[0067] To output the overall ventilation effectiveness score, the overall difference rate E of ventilation effectiveness needs further processing. First, a sigmoid function is performed on E to convert it into a value between 0 and 1. The calculation formula is as follows: Since absolute value logic already exists when calculating E, the range of values ​​for E is... Therefore, the range of values ​​for ES is Further transformation , This is the final output score for the overall ventilation effect of the mine ventilation system being evaluated. Between between, The larger the value, the better the overall ventilation effect of the coal mine.

[0068] Specifically, the analysis results corresponding to different overall ventilation effect scores can be preset.

[0069] Specifically, in addition to providing an overall ventilation effectiveness score for the mine ventilation system to be evaluated, an alert is required if the alert area list (EW) is not empty. The alert area list (EW) generally includes key areas with abnormal wind direction and excessively large air volume differences. When issuing an alert, the reason for the alert is indicated, and graph structure reasoning is performed using the directed reachability matrix of air volume to find the nodes affecting the current alert node, and investigation suggestions are provided.

[0070] Specifically, in addition to providing evaluation and early warning information for the mine ventilation system, if the list of areas to be optimized (EO) is not empty, optimization suggestions are required. The list of areas to be optimized (EO) contains a list of key areas where ventilation effects need to be optimized. Graph structure reasoning is performed using the directed reachability matrix of airflow to find the nodes affecting the current node to be optimized, and optimization suggestions are provided.

[0071] In some embodiments, step S101 further includes:

[0072] Determine the set of ventilation network equations required to solve the ventilation network. The set of ventilation network equations includes nodal air volume equations, loop air pressure balance equations, and loop branch air pressure drop equations.

[0073] The theoretical parameters of each node in the ventilation network are obtained by solving the system of equations for the ventilation network.

[0074] For each node in a ventilation network, the sum of the airflow into the node equals the sum of the airflow out of the node. Assuming there are n branches and m nodes in the ventilation network diagram, we can obtain m-1 equations, namely the nodal airflow equations.

[0075] The nodal airflow equation is:

[0076] (1), where, This represents the airflow of the j-th branch. Let i represent the air volume coefficient of the j-th branch in the equation of the i-th node, where i = 1, 2, ..., m-1.

[0077] In each closed loop of the ventilation network, the sum of the pressure drops of each branch is zero. Based on the loop pressure balance equation, a set of different loop pressure balance equations is obtained for each branch connection.

[0078] The wind pressure drop equation is:

[0079] (2), where, This represents the wind pressure of the j-th branch. This represents the wind resistance of the j-th branch (tunnel). This represents the fan resistance of the j-th branch. This represents the wind turbine drag coefficient of the j-th branch. This represents the potential pressure caused by the elevation difference or density of the j-th branch. Indicates the wind pressure coefficient. This represents the potential pressure coefficient.

[0080] When the pressure drop of a certain loop is 0, the wind network will form n-m+1 loops or branches. Therefore, the wind pressure drop equation for the k-th loop or branch is: (3);

[0081] Where k = 1, 2, ..., n-m+1, This represents the ventilation resistance coefficient of the j-th branch in the k-th loop. , Let represent the wind pressure coefficient and potential pressure coefficient of the j-th branch in the k-th loop, respectively.

[0082] A matrix can be constructed according to equation (3). Let the air volume of each independent branch (n-m+1) be as follows: If the air volume of other branches is: , , Combining equation (1), we can obtain: (4). It can be seen that, Represents a column vector containing the airflow of all branches, consisting of the independent branch airflow. Non-independent branch components composition.

[0083] Combining equations (3) and (4), we can obtain: (5), where,

[0084] ;

[0085] ;

[0086] ;

[0087] ;

[0088] ;

[0089] N ;in, B represents the air volume of all branches; B represents the fan pressure coefficient. The matrix, where H represents the wind turbine pressure contribution vector and C represents the potential pressure coefficient. The matrix is ​​N, where N represents the potential pressure contribution vector.

[0090] By expanding equation (5) above using Taylor series and ignoring differential terms above the quadratic level, we obtain:

[0091] Therefore, we have equations (6) and (7):

[0092] (6);

[0093] (7);

[0094] in, , .

[0095] After the (k+1)th iteration, the air volume of the ventilation network is: .

[0096] The wind direction information at each node can be obtained by solving using Newton's method, as follows: Figure 2 As shown.

[0097] Another embodiment of this application provides a comprehensive safety evaluation device for underground ventilation systems in coal mines based on network analysis, such as... Figure 3 As shown, the device 30 includes: a ventilation network calculation module 301, an reachability matrix determination module 302, a key area determination module 303, and a ventilation system evaluation module 304.

[0098] The ventilation network calculation module 301 is used to calculate the ventilation network corresponding to the ventilation system of the mine to be evaluated, and obtain the theoretical parameters of each node of the ventilation network, including theoretical wind direction and theoretical air volume.

[0099] The reachability matrix determination module 302 is used to construct the corresponding directed reachability matrix of air volume based on the theoretical wind direction of each node in the ventilation network.

[0100] The key area identification module 303 is used to calculate the directed reachability matrix of air volume using network analysis to identify multiple key evaluation areas of the ventilation network.

[0101] The ventilation system evaluation module 304 is used to perform dynamic evaluation and analysis of air volume in multiple key evaluation areas.

[0102] This application embodiment calculates the ventilation network corresponding to the ventilation system of the mine to be evaluated by performing wind network calculation, obtaining the theoretical parameters of each node in the ventilation network, including theoretical wind direction and theoretical air volume. Based on the theoretical wind direction of each node in the ventilation network, a corresponding directed reachability matrix of air volume is constructed. Through network analysis, multiple key evaluation areas of the ventilation network are determined using the directed reachability matrix of air volume, thereby obtaining the actual ventilation volume corresponding to each of the multiple key evaluation areas. Based on the theoretical air volume corresponding to each of the multiple key evaluation areas, the ventilation system of the mine to be evaluated is dynamically evaluated and analyzed. This method of obtaining the theoretical parameters of each area of ​​the mine to be evaluated by wind network calculation provides a theoretical basis for dynamic evaluation to compare with actual data. By using reference data and performing network analysis on the constructed directed reachability matrix of air volume to obtain key evaluation areas, the key evaluation areas are dynamically analyzed, making the evaluation results more targeted, shortening the time for dynamic evaluation of the ventilation system of the mine to be evaluated, and improving the safety of the ventilation system of the mine to be evaluated.

[0103] Furthermore, the key area identification module includes:

[0104] The degree centrality calculation submodule is used to determine the degree centrality of each node in the ventilation network based on the data of each node in the directed reachability matrix of air volume.

[0105] The importance coefficient calculation submodule is used to determine the importance coefficient of each node based on the product of the degree centrality of each node and its corresponding theoretical air volume.

[0106] The key area identification submodule is used to sort nodes in descending order according to their respective importance coefficients, and to identify a predetermined number of nodes at the top of the sort as key evaluation areas.

[0107] Furthermore, the ventilation system evaluation module includes:

[0108] The actual air volume calculation submodule is used to calculate the product of the cross-sectional area and the corresponding real-time wind speed for multiple key evaluation areas, and obtain the actual air volume for each of the multiple key evaluation areas.

[0109] The air volume compliance detection submodule is used to calculate the corresponding relative air volume difference rate when the actual air volume of any key evaluation area is inconsistent with the theoretical air volume of the corresponding node.

[0110] The key area classification submodule is used to classify any key evaluation area based on the relative difference rate of air volume.

[0111] Furthermore, the key area classification submodule includes:

[0112] The first classification unit is used to mark any key evaluation area as having excessive air volume difference if the relative air volume difference rate of any key evaluation area is greater than a preset first threshold, and add it to the list of areas to be warned, so as to generate corresponding investigation suggestions.

[0113] The second classification unit is used to add any key evaluation area to the preset list of areas to be optimized if the relative difference rate of air volume in any key evaluation area is greater than a preset second threshold but not greater than a first threshold, so as to generate corresponding optimization suggestions.

[0114] Furthermore, the device also includes:

[0115] The weight coefficient calculation module is used to determine the importance coefficients corresponding to multiple key evaluation areas and perform normalization processing to obtain the weight coefficients corresponding to multiple key evaluation areas.

[0116] The overall difference rate calculation module is used to perform weighted calculations based on the weight coefficients and their corresponding relative air volume differences for multiple key evaluation areas, to obtain the overall difference rate of ventilation effect of the mine ventilation system to be evaluated.

[0117] Furthermore, the overall difference rate calculation module also includes:

[0118] The ventilation effect scoring submodule is used to perform binary classification processing on the overall difference rate of ventilation effect of the mine ventilation system to be evaluated using a preset algorithm, and to determine the ventilation effect score of the mine ventilation system to be evaluated based on the binary classification processing results.

[0119] The ventilation effect evaluation and analysis submodule is used to determine the overall ventilation evaluation and analysis results for the mine ventilation system to be evaluated based on the ventilation effect score.

[0120] Furthermore, the ventilation network calculation module includes:

[0121] The ventilation network equations determination submodule is used to determine the ventilation network equations required to solve the ventilation network. The ventilation network equations include nodal air volume equations, loop air pressure balance equations, and loop branch air pressure drop equations.

[0122] The ventilation network equations solution submodule is used to solve the ventilation network equations and obtain the theoretical parameters of each node in the ventilation network.

[0123] The nodal airflow equation is as follows:

[0124] ,in, This represents the airflow of the j-th branch. Let i represent the air volume coefficient of the j-th branch in the equation of the i-th node, where i = 1, 2, ..., m-1;

[0125] The wind pressure drop equation is:

[0126] ,in, This represents the wind pressure of the j-th branch. Indicates the wind resistance of the j-th branch. This represents the fan resistance of the j-th branch. This represents the wind turbine drag coefficient of the j-th branch. This represents the potential pressure caused by the elevation difference or density of the j-th branch. Indicates the wind pressure coefficient. Indicates the potential pressure coefficient;

[0127] The wind pressure drop equation is:

[0128] ;

[0129] Where k = 1, 2, ..., n-m+1, This represents the ventilation resistance coefficient of the j-th branch in the k-th loop. , Let represent the wind pressure coefficient and potential pressure coefficient of the j-th branch in the k-th loop, respectively.

[0130] The safety comprehensive evaluation device for underground ventilation systems in coal mines based on network analysis in this embodiment can execute the safety comprehensive evaluation method for underground ventilation systems in coal mines based on network analysis shown in Embodiment 1 of this application. The implementation principle is similar and will not be described again here.

[0131] Another embodiment of this application provides a terminal, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method.

[0132] Specifically, the processor can be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0133] Specifically, the processor connects to the memory via a bus, which may include a path for transmitting information. The bus can be a PCI bus or an EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc.

[0134] The memory may be ROM or other types of static storage devices that can store static information and instructions, RAM or other types of dynamic storage devices that can store information and instructions, or EEPROM, CD-ROM or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.

[0135] Optionally, the memory stores the code of a computer program that executes the scheme of this application, and the execution is controlled by a processor. The processor executes the application code stored in the memory to implement the operation of the apparatus provided in the above embodiments.

[0136] Another embodiment of this application provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the above-described method.

[0137] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0138] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0139] The above is a detailed description of the preferred embodiments of this application. However, this application is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A comprehensive safety evaluation method for underground ventilation systems in coal mines based on network analysis, characterized in that, include: The ventilation network corresponding to the ventilation system of the mine to be evaluated is calculated to obtain the theoretical parameters of each node of the ventilation network, including theoretical wind direction and theoretical air volume. Based on the theoretical wind direction of each node in the ventilation network, a corresponding directed reachability matrix for air volume is constructed. The directed reachability matrix of the air volume is calculated using network analysis to determine several key evaluation areas of the ventilation network. The actual ventilation volume corresponding to multiple key evaluation areas is obtained, and the dynamic evaluation and analysis of the mine ventilation system to be evaluated is carried out based on the theoretical air volume corresponding to each of the multiple key evaluation areas.

2. The method according to claim 1, characterized in that, The method of calculating the directed reachability matrix of airflow using network analysis determines several key evaluation areas of the ventilation network, including: Based on the data of each node in the air volume directed reachability matrix, the degree centrality of each node in the ventilation network is determined. The importance coefficient of each node is determined based on the product of its degree centrality and its corresponding theoretical air volume. The nodes are sorted in descending order according to their respective importance coefficients, and a predetermined number of nodes at the top of the sort are designated as key evaluation areas.

3. The method according to claim 1, characterized in that, The process of obtaining the actual ventilation volume corresponding to multiple key evaluation areas, and performing dynamic evaluation and analysis of the mine ventilation system to be evaluated based on the theoretical air volume corresponding to each of the multiple key evaluation areas, includes: Calculate the product of the cross-sectional area and the corresponding real-time wind speed for each of the multiple key evaluation areas to obtain the actual air volume for each of the multiple key evaluation areas; When the actual air volume corresponding to any of the key evaluation areas is inconsistent with the theoretical air volume of the corresponding node, the corresponding relative air volume difference rate is calculated. Based on the relative difference rate of air volume, the key evaluation area is classified into regional evaluation categories.

4. The method according to claim 3, characterized in that, The process of classifying any of the key evaluation areas based on the relative difference rate of air volume includes: If the relative difference rate of air volume in any of the key evaluation areas is greater than a preset first threshold, then the key evaluation area is marked as having excessive air volume difference and added to the list of areas to be warned, so as to generate corresponding investigation suggestions. If the relative difference rate of air volume in any of the key evaluation areas is greater than a preset second threshold but not greater than the first threshold, then that key evaluation area is added to a preset list of areas to be optimized, so as to generate corresponding optimization suggestions.

5. The method according to claim 3, characterized in that, The method further includes: The importance coefficients corresponding to the multiple key evaluation regions are determined and normalized to obtain the weight coefficients corresponding to the multiple key evaluation regions. The overall difference rate of ventilation effect of the mine ventilation system to be evaluated is obtained by weighting the weight coefficients corresponding to the multiple key evaluation areas and their corresponding relative differences in air volume.

6. The method according to claim 5, characterized in that, The step of weighted calculation based on the weight coefficients corresponding to multiple key evaluation areas and their corresponding relative differences in air volume to obtain the overall difference rate of ventilation effect of the mine ventilation system to be evaluated also includes: The overall difference rate of ventilation effect of the mine ventilation system to be evaluated is classified into two categories using a preset algorithm, and the ventilation effect score of the mine ventilation system to be evaluated is determined based on the results of the two-category classification. The overall ventilation evaluation and analysis results for the mine ventilation system to be evaluated are determined based on the ventilation effect score.

7. The method according to claim 1, characterized in that, The ventilation network corresponding to the ventilation system of the mine to be evaluated is calculated to obtain the theoretical parameters of each node of the ventilation network, including: The ventilation network equation set required to solve the ventilation network is determined, which includes nodal air volume equations, loop air pressure balance equations, and loop branch air pressure drop equations. The theoretical parameters of each node in the ventilation network are obtained by solving the system of equations for the ventilation network. The nodal airflow equation is as follows: ,in, This represents the airflow of the j-th branch. Let i represent the air volume coefficient of the j-th branch in the equation of the i-th node, where i = 1, 2, ..., m-1; The wind pressure drop equation is as follows: ,in, This represents the wind pressure of the j-th branch. Indicates the wind resistance of the j-th branch. This represents the fan resistance of the j-th branch. This represents the wind turbine drag coefficient of the j-th branch. This represents the potential pressure caused by the elevation difference or density of the j-th branch. Indicates the potential pressure coefficient; The circuit wind pressure drop balance equation is: ； Where k = 1, 2, ..., n-m+1, This represents the ventilation resistance coefficient of the j-th branch in the k-th loop. , Let represent the wind pressure coefficient and potential pressure coefficient of the j-th branch in the k-th loop, respectively.

8. A comprehensive safety evaluation device for underground ventilation systems in coal mines based on network analysis, characterized in that, include: The ventilation network calculation module is used to calculate the ventilation network corresponding to the ventilation system of the mine to be evaluated, and obtain the theoretical parameters of each node of the ventilation network, including theoretical wind direction and theoretical air volume. The reachability matrix determination module is used to construct a corresponding directed reachability matrix of air volume based on the theoretical wind direction of each node in the ventilation network. The key area identification module is used to calculate the directed reachability matrix of the air volume using network analysis to identify multiple key evaluation areas of the ventilation network. The ventilation system evaluation module is used to obtain the actual ventilation volume corresponding to multiple key evaluation areas, and to perform dynamic evaluation and analysis on the mine ventilation system to be evaluated based on the theoretical air volume corresponding to each of the multiple key evaluation areas.

9. An electronic device, characterized in that, The device includes a processor and a memory, the memory storing computer-readable instructions, and the processor being configured to execute the computer-readable instructions, wherein the computer-readable instructions, when executed, perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions for performing the method according to any one of claims 1 to 7.

Images