Mine ventilation control method and system, electronic device, readable storage medium

Abstract

The application provides a mine ventilation control method and system, an electronic device and a readable storage medium, and belongs to the technical field of mine engineering. The method comprises the following steps: determining a first risk value based on the number of working faces and the mining depth, and determining a second risk value based on the coal seam thickness and the coal seam temperature and humidity; if the mining stage type is tunneling, a first weight coefficient matrix is selected; if the mining stage type is stoping, a second weight coefficient matrix is selected; the first risk value and the second risk value are weighted and summed based on the corresponding weight coefficient matrix to obtain a safety risk coefficient; the ventilation control mode is determined based on the safety risk coefficient; mine environment data are obtained based on the ventilation control mode; a target adjustment strategy is determined based on the mine environment data, the ventilation control mode and the ventilation equipment operation parameters; and the ventilation equipment operation parameters are controlled based on the target adjustment strategy. The application can realize fine adjustment and control of mine ventilation equipment to further reduce energy consumption.

Description

Technical Field

[0001] This application belongs to the field of mining engineering technology, and more specifically, relates to mine ventilation control methods and systems, electronic equipment, and readable storage media. Background Technology

[0002] In mining operations, ventilation systems are crucial, as their effectiveness directly impacts worker safety and smooth production. However, existing mine ventilation control technologies largely rely on fixed rules and experience, using single control logic. This makes them unable to adapt quickly to changes in mining stages and complex, variable coal seam conditions, leading to low ventilation efficiency, increased energy consumption, and even safety accidents. While some intelligent ventilation systems can monitor data, they still lack refined adjustment mechanisms for equipment parameters, resulting in generally high energy consumption for ventilation equipment. Therefore, a new mine ventilation control method is needed to achieve refined adjustment and control of mine ventilation equipment to further reduce energy consumption. Summary of the Invention

[0003] The purpose of this application is to provide a mine ventilation control method and system, electronic equipment, and readable storage medium to achieve fine adjustment and control of mine ventilation equipment, thereby further reducing energy consumption.

[0004] A first aspect of this application provides a mine ventilation control method, comprising:

[0005] The first risk value is determined based on the number of working faces and the mining depth, and the second risk value is determined based on the coal seam thickness and coal seam temperature and humidity. If the mining stage type is tunneling, the target weight coefficient matrix is ​​determined as the first weight coefficient matrix; if the mining stage type is longwall mining, the target weight coefficient matrix is ​​determined as the second weight coefficient matrix. The first and second risk values ​​are weighted and summed based on the target weight coefficient matrix to obtain the safety risk coefficient. The target ventilation control mode is determined based on the safety risk coefficient.

[0006] In the first weighting coefficient matrix, the weighting coefficient of the first risk value is greater than the weighting coefficient of the second risk value; in the second weighting coefficient matrix, the weighting coefficient of the first risk value is not greater than the weighting coefficient of the second risk value.

[0007] Mine environmental data is acquired based on the target ventilation control mode; target adjustment strategies are determined based on the mine environmental data, target ventilation control mode, and ventilation equipment operating parameters; ventilation equipment operating parameters include the number of fans in operation, fan frequency, and fan opening degree;

[0008] The operating parameters of ventilation equipment are controlled based on the target adjustment strategy.

[0009] A second aspect of this application provides a mine ventilation control system, comprising:

[0010] The control mode division module is used to determine the first risk value based on the number of working faces and mining depth, and the second risk value based on coal seam thickness and coal seam temperature and humidity. If the mining stage type is tunneling, the target weight coefficient matrix is ​​determined as the first weight coefficient matrix; if the mining stage type is longwall mining, the target weight coefficient matrix is ​​determined as the second weight coefficient matrix. The first and second risk values ​​are weighted and summed based on the target weight coefficient matrix to obtain the safety risk coefficient. The target ventilation control mode is determined based on the safety risk coefficient.

[0011] In the first weighting coefficient matrix, the weighting coefficient of the first risk value is greater than the weighting coefficient of the second risk value; in the second weighting coefficient matrix, the weighting coefficient of the first risk value is not greater than the weighting coefficient of the second risk value.

[0012] The control strategy determination module is used to acquire mine environmental data based on the target ventilation control mode; and to determine the target adjustment strategy based on the mine environmental data, the target ventilation control mode, and the operating parameters of the ventilation equipment; the operating parameters of the ventilation equipment include the number of fans in operation, the fan frequency, and the fan opening degree.

[0013] The control module is used to control the operating parameters of the ventilation equipment based on the target adjustment strategy.

[0014] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the above-described mine ventilation control method.

[0015] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described mine ventilation control method.

[0016] The beneficial effects of the mine ventilation control method and system, electronic equipment, and readable storage medium provided in this application are as follows: This application, by combining mine mining data and coal seam data to determine the safety risk coefficient, and then selecting the target ventilation control mode, can accurately match the actual operating conditions of the mine, providing a scientific basis for subsequent ventilation control and effectively ensuring mine operation safety. This application, based on the target ventilation control mode, acquires mine environmental data and comprehensively considers environmental data, the target mode, and ventilation equipment operating parameters to determine the target adjustment strategy. This comprehensive approach, taking into account multiple factors, enables refined adjustment of ventilation equipment. Compared to traditional extensive control, this application can flexibly adjust parameters such as the number, frequency, and opening degree of fans according to real-time conditions, avoiding excessive ventilation and energy waste, thus achieving the goal of energy consumption control. This not only ensures mine operation safety but also reduces mine operating costs, conforms to the environmental protection concept of energy conservation and emission reduction, and is of great significance to the sustainable development of mine engineering technology. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A schematic flowchart of a mine ventilation control method provided in an embodiment of this application;

[0019] Figure 2 A structural block diagram of a mine ventilation control system provided in an embodiment of this application;

[0020] Figure 3 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0021] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0023] Please refer to Figure 1 , Figure 1This is a schematic flowchart of a mine ventilation control method provided in an embodiment of this application. The method can be executed by an electronic device. Specifically, the method may include S101 to S103.

[0024] S101: Determine the first risk value based on the number of working faces and mining depth, and determine the second risk value based on coal seam thickness and coal seam temperature and humidity; if the mining stage type is tunneling, then determine the target weight coefficient matrix as the first weight coefficient matrix; if the mining stage type is longwall mining, then determine the target weight coefficient matrix as the second weight coefficient matrix; perform a weighted summation of the first and second risk values ​​based on the target weight coefficient matrix to obtain the safety risk coefficient; determine the target ventilation control mode based on the safety risk coefficient.

[0025] In the first weighting coefficient matrix, the weighting coefficient of the first risk value is greater than the weighting coefficient of the second risk value; in the second weighting coefficient matrix, the weighting coefficient of the first risk value is not greater than the weighting coefficient of the second risk value.

[0026] In this embodiment, a first risk value is determined based on the number of working faces and the mining depth, and a second risk value is determined based on the coal seam thickness and the coal seam temperature and humidity, specifically including:

[0027] Based on the number of working faces and the mining depth, the first risk value is determined using the first formula.

[0028] The first formula is:

[0029]

[0030] in, The first risk value is N, where N is the number of work surfaces. Where D is the preset maximum number of working faces, and D is the mining depth. The preset target maximum mining depth is defined by a and b, where a and b are weighting coefficients, and a+b=1.

[0031] The second risk value is determined using the second formula based on the coal seam thickness and coal seam temperature and humidity.

[0032] The second formula is:

[0033]

[0034]

[0035] in, The second risk value is H, where H is the coal seam thickness. The preset target maximum coal seam thickness, The values ​​represent the temperature and humidity of the coal seam, where c and d are weighting coefficients, c+d=1, and T is the coal seam temperature. The upper limit of the safe temperature, M is the humidity of the coal seam. To ensure the upper limit of safe humidity, due to The sum of temperature and humidity is used to calculate the second risk value, which is then divided by 2 to obtain the average value.

[0036] In this embodiment, mining progress, mining depth, and the number of working faces are all mine mining data, which can reflect the dynamic situation of mining activities. The number of working faces refers to the number of working faces operating simultaneously; the deeper the mining depth, the higher the ground pressure and gas emission. Coal seam thickness and coal seam temperature and humidity are both coal seam data, which describes the physical characteristics of the coal seam. Coal seam data may also include permeability and gas content. Coal seam thickness affects mining efficiency and gas storage capacity; thicker coal seams release more gas. Coal seam temperature and humidity reflect the internal environment of the coal seam; high temperatures accelerate gas desorption or trigger spontaneous combustion, while high humidity hinders gas diffusion and increases the risk of gas accumulation. Tunneling and longwall mining are both mining stage types, and different mining stage types have different risk characteristics. The first risk value is a risk indicator calculated based on mining activities, mainly positively affected by the number of working faces and mining depth; the greater the number and depth, the higher the risk value. The second risk value is a risk indicator calculated based on coal seam characteristics; the thicker the coal seam and the higher the temperature and humidity, the higher the risk value. The number of working faces and mining depth are positively correlated with the first risk value, while coal seam thickness and coal seam temperature and humidity are positively correlated with the second risk value. The target weight coefficient matrix is ​​a set of preset weighted parameters used to quantify the contribution of mining data and coal seam data to safety risk, reflecting their relative importance in risk assessment.

[0037] The safety risk coefficient in mining operations is a comprehensive indicator that quantifies the potential hazards during mining operations. It is used to assess the safety pressures that the ventilation system needs to handle. The target ventilation control mode is a ventilation system operation strategy determined based on the safety risk coefficient to meet ventilation requirements at different risk levels. The target ventilation control mode includes preset ventilation equipment operating parameters, preset mine data monitoring strategies, and adjustment and control strategies for the ventilation equipment. Different safety risk coefficients correspond to different target ventilation control modes for the mine.

[0038] This embodiment first categorizes and processes mining data and coal seam data, calculating a first risk value and a second risk value respectively. In the mining data, multiple working faces indicate concentrated personnel and equipment, and high ventilation demands; deeper mining results in higher gas pressure and increased ground temperature, leading to a larger first risk value. In the coal seam data, thicker coal seams have larger gas reserves, and abnormal temperature and humidity indicate active gas or a risk of spontaneous combustion, leading to a larger second risk value. Finally, this embodiment uses different weighting coefficient matrices corresponding to different mining stages to weight and sum the two types of risk values, comprehensively deriving a safety risk coefficient. This balances the impact of different data on risk, ensuring that the assessment results accurately reflect the actual safety situation.

[0039] This embodiment ensures that the risk assessment is adapted to the core risk characteristics of different mining stages. For the tunneling stage, priority is given to its high-risk factors (such as the first risk value), and for the mining stage, priority is given to the key risks of that stage (such as the second risk value). This makes the weight allocation more realistic, improves the accuracy of the safety risk coefficient calculation, and makes the ventilation control mode more targeted, thereby improving the safety and efficiency of mine ventilation.

[0040] For example, in a coal mine operation, this embodiment obtains the following data through real-time monitoring: During the tunneling stage, there are two working faces, a mining depth of 600 meters, a coal seam thickness of approximately 3 meters, a coal seam temperature of 28°C, and a humidity of 75%. Based on the number of working faces and the mining depth, this embodiment calculates a first risk value exceeding a preset threshold because multiple working faces are tunneling simultaneously at a considerable depth, making ventilation and gas management difficult. Based on the coal seam thickness and temperature and humidity, this embodiment calculates a second risk value at a moderate level. Since the mining stage is tunneling, this embodiment automatically determines the target weighting coefficient matrix as a preset first weighting coefficient matrix, where the weighting coefficient for the first risk value is 70%, and the weighting coefficient for the second risk value is 30%. This embodiment weights and sums the first and second risk values ​​according to their corresponding weighting coefficients to obtain a safety risk coefficient. The safety risk coefficient is compared with a preset risk threshold. If the safety risk coefficient is higher than the preset risk threshold, it is determined that the obtained safety risk coefficient is in a high-risk range. This embodiment then activates a strong ventilation mode, increases the number of operating fans, and assigns dedicated personnel to strengthen gas concentration monitoring.

[0041] This embodiment assesses risks through multi-dimensional data fusion, dynamically adjusts weights based on the mining stage, and precisely matches ventilation modes. This embodiment not only enables rapid response to high-risk scenarios, ensuring miners' safety, but also reduces energy consumption and equipment wear in low-risk situations, achieving a win-win situation for safety management and economic benefits, and effectively improving the level of intelligent and scientific mine management.

[0042] In this embodiment, a data-driven, hierarchical management approach is used to dynamically optimize the mine ventilation system. Specifically, this embodiment transforms mine mining data (mining conditions) and coal seam data (geological conditions) into risk assessments, then matches ventilation control modes according to the risks, and finally ensures underground safety and rationally controls the energy consumption of ventilation equipment by adjusting equipment parameters under different ventilation control modes.

[0043] This embodiment first acquires parameters such as mining progress and number of working faces from mining data, and gas content and permeability from coal seam data, and then comprehensively evaluates them to obtain a safety risk coefficient. For example, as mining depth increases and gas content rises, the safety risk coefficient will increase. Based on the safety risk coefficient, this embodiment can select a target ventilation control mode from a preset ventilation control mode library. For example, a strong ventilation control mode is selected for high risk, and a conventional ventilation control mode is selected for low risk. This embodiment controls and collects mine environmental data, such as real-time gas concentration, temperature, and dust volume, based on the selected target ventilation control mode. This embodiment comprehensively analyzes the environmental data with the target ventilation control mode and ventilation equipment operating parameters to formulate a target adjustment strategy. For example, if the gas concentration exceeds the standard, the strategy could be to increase the number of operating fans or increase the fan frequency. This embodiment adjusts the ventilation equipment according to the target adjustment strategy to achieve precise ventilation.

[0044] For example, in a large-scale coal mine mining project, a newly excavated working face, due to its proximity to a high-gas coal seam, was assessed as having a high safety risk coefficient based on mining and coal seam data analysis. This embodiment automatically switches to a strong ventilation control mode. During operation, this embodiment monitors a rapid increase in gas concentration from 0.5% to 0.8% (approaching the critical value of 1%). This embodiment immediately determines and executes a target adjustment strategy, increasing the number of operating fans from 4 to 6, increasing the fan frequency by 30%, and increasing the fan opening to 100%. After adjustment, the gas concentration quickly drops to a safe range, effectively preventing accidents caused by gas accumulation.

[0045] If the ventilation control mode is the conventional ventilation control mode, and during operation, this embodiment detects that the CO gas content has reached the gas safety risk threshold, then the target adjustment strategy is immediately determined and executed, increasing the number of operating fans from 4 to 5 and increasing the fan frequency by 10%. The method of formulating the target adjustment strategy differs between the conventional ventilation control mode and the strong ventilation control mode.

[0046] The difference in target adjustment strategies between conventional ventilation control mode and intensive ventilation control mode essentially stems from the different risk levels and ventilation requirements. Intensive ventilation mode is designed for high-risk scenarios, therefore the strategy needs to have stronger responsiveness and rapid response capabilities. When the gas concentration is close to the critical value, stronger responsiveness can ensure that the concentration of hazardous gases is reduced as quickly as possible to avoid accidents.

[0047] Conventional ventilation control modes are suitable for scenarios with relatively low risk, and daily ventilation can meet most safety requirements. When the detected CO gas content reaches the safety risk threshold, it indicates a local gas anomaly underground, but it has not yet reached a high-risk state. At this time, a relatively mild adjustment strategy is adopted, adding only one fan and increasing the frequency by 10%. This effectively reduces the CO gas concentration while avoiding energy waste and equipment damage caused by excessive ventilation. This tiered response mechanism in this embodiment ensures safe operation while also taking into account economy and equipment lifespan, achieving a balance between safety assurance and operating costs.

[0048] S102: Obtain mine environmental data based on the target ventilation control mode; determine the target adjustment strategy based on the mine environmental data, the target ventilation control mode, and the operating parameters of the ventilation equipment; the operating parameters of the ventilation equipment include the number of fans in operation, the fan frequency, and the fan opening degree.

[0049] In this embodiment, the mine environmental data includes information that reflects the underground safety status, such as the concentration of harmful gases, temperature, humidity, and dust concentration. Ventilation equipment operating parameters are key indicators for controlling fan operation, and these parameters may include the number of operating fans (the number of fans in operation), fan frequency (motor speed, which affects airflow), and fan opening degree.

[0050] This embodiment first collects targeted mine environmental data according to the requirements of the target ventilation control mode. For example, in the strong ventilation control mode, this embodiment can increase the monitoring frequency of methane concentration, mine temperature and humidity, and harmful gas concentration; in the conventional ventilation control mode, gas concentration and temperature and humidity can be monitored based on the basic monitoring frequency. This embodiment compares the environmental data with preset safety thresholds. If any environmental data exceeds the safety threshold, a target adjustment strategy for the ventilation equipment operating parameters is determined by combining the existing equipment operating parameters, mine environmental data, and the target ventilation control mode.

[0051] For example, in the longwall face of a large coal mine, this embodiment pre-sets the strong ventilation control mode according to the coal seam characteristics of the mining area, and increases the monitoring frequency of gas concentration, temperature and humidity and harmful gas concentration.

[0052] During the mining process, real-time monitoring data showed that the methane concentration at the working face rapidly increased from 0.4% to 0.7%, approaching the safety threshold of 0.8%, accompanied by rising temperature and carbon monoxide concentration. This embodiment immediately activated the response mechanism. Considering the current operating parameters of three fans at 70% frequency and 80% opening, and the requirements of the strong ventilation control mode, the target adjustment strategy was quickly determined: increase the number of operating fans to five, raise the fan frequency to the maximum value, and adjust the fan opening to 100%. After the adjustment, fresh airflow rapidly entered the working face, and the methane concentration dropped to 0.3% within a short time. Temperature and carbon monoxide concentrations also returned to normal levels, preventing safety hazards caused by methane accumulation and ensuring safe underground operations and stable production.

[0053] S103: Control the operating parameters of ventilation equipment based on the target adjustment strategy.

[0054] In this embodiment, the target adjustment strategy is a ventilation equipment control plan formulated comprehensively based on mine safety risks, environmental data, etc. The target adjustment strategy may include: increasing or decreasing the number of fans, increasing or decreasing the fan frequency, and adjusting the fan opening degree, etc.

[0055] In this embodiment, after determining the target adjustment strategy, it is converted into control commands for specific parameters of the ventilation equipment and sent to the corresponding ventilation equipment. The automated control system then operates the fan to adjust the operating parameters. This embodiment can achieve on-demand air supply by precisely controlling equipment parameters, ensuring the safety of underground air quality while avoiding energy waste.

[0056] For example, if a hazardous gas concentration is detected at a fully mechanized mining face in a mine and reaches a dangerous threshold, this embodiment can generate a strategy to increase the number of operating fans and increase their frequency. This embodiment sends control commands corresponding to the target adjustment strategy to the ventilation equipment in the mine to control the equipment to make adjustments, for example, increasing the number of operating fans from 3 to 5 and increasing the fan frequency to 80%.

[0057] As can be seen from the above, this embodiment determines the safety risk coefficient by combining mine mining data and coal seam data, and then selects the target ventilation control mode. This accurately matches the actual operating conditions of the mine, providing a scientific basis for subsequent ventilation control and effectively ensuring mine operation safety. This embodiment acquires mine environmental data based on the target ventilation control mode and determines the target adjustment strategy by comprehensively considering environmental data, the target mode, and ventilation equipment operating parameters. This multi-factor-oriented approach enables precise adjustment of ventilation equipment. Compared to traditional extensive control, this embodiment can flexibly adjust parameters such as the number, frequency, and opening degree of fans according to real-time conditions, avoiding energy waste caused by excessive ventilation and achieving the goal of energy consumption control. This not only ensures mine operation safety but also reduces mine operating costs, conforms to the environmental protection concept of energy conservation and emission reduction, and is of great significance to the sustainable development of mine engineering technology.

[0058] In one embodiment of this application, determining the target ventilation control mode based on the safety risk coefficient includes: if the safety risk coefficient is greater than the risk threshold, then determining the target ventilation control mode as a first control mode; if the safety risk coefficient is less than or equal to the risk threshold, then determining the target ventilation control mode as a second control mode.

[0059] The data acquisition frequency corresponding to the first control mode is greater than the data acquisition frequency corresponding to the second control mode; the fan frequency adjustment step size and fan opening adjustment step size corresponding to the first control mode are greater than the fan frequency adjustment step size and fan opening adjustment step size corresponding to the second control mode, respectively.

[0060] In this embodiment, the mine environment data includes mine gas data and mine temperature and humidity; acquiring mine environment data based on the target ventilation control mode specifically includes: if the target ventilation control mode is a first control mode, then acquiring mine environment data based on a first data acquisition strategy; the first data acquisition strategy is to acquire mine gas data based on a first frequency and mine temperature and humidity based on a second frequency.

[0061] If the target ventilation control mode is the second control mode, then the mine environment data is acquired based on the second data acquisition strategy; the second data acquisition strategy is to acquire mine gas data based on the third frequency and mine temperature and humidity based on the fourth frequency; the first frequency is greater than the third frequency, and the second frequency is greater than the fourth frequency.

[0062] In this embodiment, the risk threshold is a preset safety critical value used to classify the levels of ventilation control modes. The first control mode corresponds to the strong ventilation control mode for high-risk scenarios, characterized by high-frequency data acquisition and rapid equipment response. The second control mode corresponds to the conventional ventilation control mode for low-risk scenarios, with relatively low data acquisition frequency and equipment adjustment range. The data acquisition frequency is the time interval at which the sensor acquires mine environmental data. For example, the first frequency can be once every 3 minutes for gas data acquisition, and the third frequency can be once every 10 minutes for gas data acquisition. The second frequency can be once per minute for mine temperature and humidity, and the fourth frequency can be once every 3 minutes for mine temperature and humidity.

[0063] The fan frequency adjustment step size refers to the magnitude of each adjustment to the fan speed. For example, in the first control mode, the maximum fan frequency can be increased by 20% each time, and in the second control mode, the maximum fan frequency can be increased by 10% each time. The fan opening adjustment step size refers to the magnitude of adjustment to the degree of opening of the fan vent. It can be adjusted significantly in high-risk situations (first control mode) and slightly in low-risk situations (second control mode).

[0064] This embodiment first assesses the mine's risk level using a safety risk coefficient. If the safety risk coefficient exceeds the risk threshold, it is determined to be high-risk, and the first control mode is activated. In this mode, the frequency of gas data and temperature / humidity acquisition is increased to capture subtle changes in real time. At the same time, relatively higher initial ventilation equipment operating parameters and fan frequency and fan opening adjustment steps are used in advance to ensure that the ventilation system can respond quickly to emergencies.

[0065] If the safety risk coefficient is below the threshold, the second control mode is adopted. This mode can reduce the frequency of gas data and temperature and humidity acquisition, reduce the sensor operating load and data processing pressure; at the same time, it adopts relatively lower initial ventilation equipment operating parameters and fan frequency and fan opening adjustment step size in advance to avoid frequent and excessive adjustments that lead to equipment wear and energy waste, and achieve energy-saving operation under the premise of ensuring safety.

[0066] For example, during a coal mine mining operation, this embodiment calculates a safety risk coefficient of 0.8 based on the number of working faces, mining depth, and coal seam characteristics. This coefficient exceeds the preset threshold of 0.7, and the system immediately switches to the first ventilation control mode. This embodiment increases the gas concentration monitoring frequency from once every 5 minutes to once per minute, and the temperature and humidity monitoring frequency from once every 10 minutes to once every 3 minutes. During operation, this embodiment monitors the gas concentration rising from 0.3% to 0.6% within 10 minutes, approaching the critical value of 0.8%. Since the fan frequency adjustment step size and fan opening adjustment step size are both 30% in the first control mode, this embodiment immediately controls the ventilation equipment to increase the fan frequency from 60% to 90% and the fan opening from 70% to 100%, rapidly diluting the gas concentration and reducing it to a safe range within a short time. All percentages above correspond to actual baseline values; the specific baseline values ​​are subject to the equipment parameters used in the actual situation.

[0067] Once mining in the area reaches a stable phase, the reassessed safety risk factor is 0.4, and this embodiment switches to the second ventilation control mode. Gas data acquisition frequency is restored to once every 5 minutes, and temperature and humidity are collected once every 10 minutes; simultaneously, the fan frequency adjustment step is set to 10%, and the opening adjustment step is set to 15%. This reduces energy consumption and extends equipment lifespan while ensuring safety.

[0068] This embodiment uses a dynamic switching mode based on risk coefficients. During high-risk periods, it employs high-frequency monitoring and rapid response to promptly mitigate potential hazards such as excessive gas levels. During low-risk periods, it reduces frequency and equipment adjustment range, saving energy, reducing consumption, and extending equipment lifespan. This embodiment balances safety and economic benefits, significantly improving the scientific rigor and reliability of mine ventilation management.

[0069] In one embodiment of this application, determining a target adjustment strategy based on mine environmental data, a target ventilation control mode, and ventilation equipment operating parameters includes: determining a parameter adjustment sequence based on mine environmental data and ventilation equipment operating parameters; the parameter adjustment sequence includes at least one of the number of operating fans, fan frequency, and fan opening degree; determining a target adjustment direction for the ventilation equipment operating parameters in the parameter adjustment sequence based on mine environmental data; determining a target adjustment value based on the target ventilation control mode and the target adjustment direction; and determining a target adjustment strategy based on the target adjustment direction and the target adjustment value.

[0070] In this embodiment, the mine environment data includes mine gas data and mine temperature and humidity; determining the target adjustment direction of the ventilation equipment operating parameters in the parameter adjustment sequence based on the mine environment data includes: if the mine environment data does not meet the first condition, then determining the target adjustment direction of the ventilation equipment operating parameters in the parameter adjustment sequence as a positive direction; if the mine environment data meets the first condition, then determining the target adjustment direction as a negative direction or unchanged.

[0071] Positive directions include increasing the number of operating fans, increasing the fan frequency, and increasing the fan opening degree; the first condition is that the mine gas data does not exceed the gas safety threshold and the mine temperature and humidity do not exceed the temperature and humidity safety threshold; negative directions include reducing the number of operating fans, reducing the fan frequency, and reducing the fan opening degree, while "unchanged" means not adjusting the number of operating fans, fan frequency, and fan opening degree.

[0072] In this embodiment, the parameter adjustment sequence includes the number of operating fans, fan frequency, and fan opening degree; determining the target adjustment value based on the target ventilation control mode, target adjustment direction, and parameter adjustment sequence includes:

[0073] The target adjustment step size is determined based on the target ventilation control mode; the target adjustment step size includes the fan frequency adjustment step size and the fan opening adjustment step size;

[0074] The adjustment value for the number of operating fans is determined based on the target adjustment direction, the number of operating fans, and the total number of fans; the adjustment value for the fan frequency is determined based on the target adjustment direction, the fan frequency, and the fan frequency adjustment step size; and the adjustment value for the fan opening is determined based on the target adjustment direction, the fan opening degree, and the fan opening adjustment step size.

[0075] In this embodiment, the parameter adjustment sequence is a preliminary selection of equipment parameter combinations that need adjustment based on environmental data. This may include a single parameter (e.g., adjusting only the fan frequency) or multiple parameters (e.g., adjusting the number of fans and fan opening simultaneously, or all parameters). The target adjustment direction determines whether the equipment parameter should be increased (positive direction), decreased (negative direction), or remain unchanged. The target adjustment value refers to the specific parameter adjustment range, calculated jointly by the adjustment step size determined by the target ventilation control mode and the current ventilation equipment operating parameters.

[0076] This embodiment achieves precise control of the ventilation system through data comparison and dynamic analysis. It collects real-time mine environmental data such as carbon monoxide concentration, sulfur dioxide concentration, temperature, and humidity, and compares these data with preset safety thresholds. If any data exceeds the threshold, it is considered abnormal. This embodiment can then combine the severity and trend of the data anomaly with the current operating parameters of the ventilation equipment to selectively identify the parameter combinations that need adjustment, forming a parameter adjustment sequence.

[0077] Considering the varying impacts of different types of data anomalies on ventilation requirements—for example, a slight exceedance of carbon monoxide concentration only requires adjusting the fan frequency; a severe exceedance necessitates simultaneously increasing the number and opening of fans—this embodiment, by adjusting existing equipment parameters, avoids excessive adjustments that could lead to energy waste and equipment damage. It also ensures a rapid response from the ventilation system, efficiently resolving environmental anomalies and achieving economical and efficient operation of the ventilation system while guaranteeing safety during underground operations.

[0078] In this embodiment, the parameter adjustment sequence is determined based on mine environmental data and ventilation equipment operating parameters. Specifically, this includes: calculating the parameter adjustment margin of the ventilation equipment operating parameters; wherein, the parameter adjustment margin corresponding to the number of fans operating is the first margin, the parameter adjustment margin corresponding to the fan frequency is the second margin, and the parameter adjustment margin corresponding to the fan opening degree is the third margin; the first margin, the second margin, and the third margin are arranged from largest to smallest to obtain the candidate adjustment sequence.

[0079] If the mine gas data does not exceed the gas safety threshold and the mine temperature and humidity do not exceed the temperature and humidity safety threshold, then add the ventilation equipment operating parameter corresponding to the last parameter adjustment margin in the candidate adjustment sequence to the parameter adjustment sequence.

[0080] If the mine gas data exceeds the gas safety threshold but the mine temperature and humidity do not exceed the temperature and humidity safety threshold, or if the mine gas data does not exceed the gas safety threshold but the mine temperature and humidity exceed the temperature and humidity safety threshold, then the ventilation equipment operating parameters corresponding to the first two parameter adjustment margins in the candidate adjustment sequence will be added to the parameter adjustment sequence.

[0081] If the mine gas data exceeds the gas safety threshold and the mine temperature and humidity exceed the temperature and humidity safety threshold, then add the number of operating fans, fan frequency, and fan opening degree to the parameter adjustment sequence.

[0082] In this embodiment, parameter adjustment margins are used to quantify the remaining adjustable space for ventilation equipment parameters. The first margin is the adjustment space for the number of operating fans, calculated as: First Margin = (Total number of fans - Current number of operating fans) / Total number of fans; the second margin is the adjustment space for fan frequency, calculated as: Second Margin = (Fan frequency upper limit - Current fan frequency) / Fan frequency upper limit; the third margin is the adjustment space for fan opening, calculated as: Third Margin = (Fan opening upper limit - Current fan opening) / Fan opening upper limit. The candidate adjustment sequence is a parameter adjustment priority list formed by sorting the three margin values ​​from largest to smallest; the larger the margin value, the higher the adjustment priority.

[0083] This embodiment classifies environmental risk levels based on the extent to which environmental data exceeds standards, prioritizes the adjustment of ventilation equipment operating parameters based on parameter adjustment margins, and then selects a specific parameter adjustment sequence based on the environmental risk level and parameter adjustment priority, as follows:

[0084] If all environmental data are normal, it is considered risk-free. The corresponding parameter adjustment strategies include keeping them unchanged or reducing the operating parameters of ventilation equipment to save energy. The operating parameter of ventilation equipment with the lowest adjustment margin can be selected as the parameter to be adjusted, because the lowest adjustment margin means that the parameter value is closest to the full value. For the need to reduce parameters, the adjustment margin is the highest in the opposite direction. If only one type of data, such as gas or temperature and humidity, exceeds the standard, it is considered low risk. The operating parameters of the two ventilation equipment with the highest margin can be adjusted in a coordinated manner. If both gas and temperature and humidity exceed the standard, it is considered high risk. All parameters should be forcibly adjusted. By coordinating multiple parameters, the environment can be improved quickly to avoid the escalation of the accident.

[0085] The purpose of this embodiment is to quantify the adjustment margin of ventilation equipment parameters, determine the adjustment priority by sorting the margins from largest to smallest, and implement a gradient adjustment strategy based on the environmental risk level. This embodiment can achieve equipment protection, energy-saving optimization, and efficiency improvement. Specifically, this embodiment prioritizes adjusting parameters with large margins to avoid overloading a single device. By distributing the load through the coordinated operation of multiple devices, it extends equipment life and retains emergency adjustment redundancy. High-margin parameters can quickly respond to emergency scenarios such as excessive gas levels. Combined with multi-parameter linkage, it can achieve fine adjustment, balancing response speed and adjustment accuracy, and improving the robustness of the ventilation system.

[0086] For example, when a coal mine working face enters the stable mining stage, the real-time monitoring data in this embodiment shows: mine gas data: oxygen concentration 20.5% (safe threshold is greater than or equal to 19.5%), sulfur dioxide concentration 10ppm (safe threshold is not greater than 20ppm).

[0087] Mine temperature and humidity: Temperature 24℃ (safe threshold not exceeding 26℃), humidity 65% ​​(safe threshold not exceeding 85%).

[0088] Ventilation equipment parameters: Total number of fans: 6, 4 currently in operation, fan frequency: 70%, frequency limit: 100%, fan opening: 80%, opening limit: 100%.

[0089] First margin = (6-4) / 6 = 0.33, second margin = (100-70) / 100 = 0.3, third margin = (100-80) / 100 = 0.2. Sort the first, second, and third margins from largest to smallest to obtain the candidate adjustment sequence. The candidate adjustment sequence is [number of wind turbines in operation, wind turbine frequency, wind turbine opening degree].

[0090] If the gas data and temperature / humidity are within acceptable limits, the scenario is deemed risk-free, and the fan opening corresponding to the third margin is added to the parameter adjustment sequence. At this point, the target adjustment direction for this parameter adjustment sequence can be negative or remain unchanged, depending on the environmental parameters. If it is negative, and the current fan opening is 80%, the opening adjustment step size in the target control mode is used as the specific adjustment value. The corresponding target adjustment strategy is to reduce the fan opening to (80% - opening adjustment step size).

[0091] For example, a sudden geological change occurred at a coal mine tunneling face, causing anomalies in real-time data, as detailed below:

[0092] Mine gas data: Carbon monoxide concentration 24 ppm (safe threshold is no more than 24 ppm, critical value), oxygen concentration 19.3% (safe threshold is greater than or equal to 19.5%, slightly decreased);

[0093] Mine temperature and humidity: Temperature 28℃ (safe threshold is no more than 26℃, exceeding the standard), humidity 88% (safe threshold is no more than 85%, exceeding the standard);

[0094] Because both gas and temperature / humidity data exceeded limits, the scenario was deemed high-risk. All ventilation equipment operating parameters were added to the parameter adjustment sequence, with the target adjustment direction being positive. The parameters in the adjustment sequence were then adjusted according to the target ventilation control mode (assuming it's the second control mode), as shown below:

[0095] Number of operating fans: Currently 3 fans are operating, the adjustment value is determined to be 2 fans, then the target adjustment strategy is to adjust the number of operating fans from 3 to 5.

[0096] Fan frequency: The current fan frequency is 60%. In the second control mode, the frequency adjustment step size is 20%, so the adjustment value is 20%. The target adjustment strategy is to adjust the fan frequency from 60% to 80%.

[0097] Fan opening: The current fan opening is 60%. In the second control mode, the opening adjustment step is 25%, so the adjustment value is 25%. The target adjustment strategy is to adjust the fan opening from 60% to 85%.

[0098] As can be seen from the above, this embodiment achieves intelligent and refined management of mine ventilation by quantifying the adjustment margin of parameters and implementing gradient adjustment in combination with risk level. When there is no risk, energy saving and consumption reduction are achieved; when the risk is low, precise control is achieved; and when the risk is high, multi-parameter linkage is implemented for rapid response. This not only avoids equipment overload and extends its service life, but also takes into account ventilation efficiency and energy consumption balance.

[0099] Corresponding to the mine ventilation control method in the above embodiments, Figure 2This is a structural block diagram of a mine ventilation control system provided according to an embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. References Figure 2 The mine ventilation control system 20 includes: a control mode division module 21, a control strategy determination module 22, and a control module 23.

[0100] The control mode division module 21 is used to determine the first risk value based on the number of working faces and the mining depth, and to determine the second risk value based on the coal seam thickness and the temperature and humidity of the coal seam. If the mining stage type is tunneling, the target weight coefficient matrix is ​​determined as the first weight coefficient matrix; if the mining stage type is longwall mining, the target weight coefficient matrix is ​​determined as the second weight coefficient matrix. The first risk value and the second risk value are weighted and summed based on the target weight coefficient matrix to obtain the safety risk coefficient. The target ventilation control mode is determined based on the safety risk coefficient.

[0101] In the first weighting coefficient matrix, the weighting coefficient of the first risk value is greater than the weighting coefficient of the second risk value; in the second weighting coefficient matrix, the weighting coefficient of the first risk value is not greater than the weighting coefficient of the second risk value.

[0102] The control strategy determination module 22 is used to acquire mine environmental data based on the target ventilation control mode; and to determine the target adjustment strategy based on the mine environmental data, the target ventilation control mode, and the operating parameters of the ventilation equipment; the operating parameters of the ventilation equipment include the number of fans in operation, the fan frequency, and the fan opening degree.

[0103] Control module 23 is used to control the operating parameters of ventilation equipment based on the target adjustment strategy.

[0104] In one embodiment of this application, the control mode division module 21 is specifically used to determine a first risk value based on the number of working faces and the mining depth using a first formula;

[0105] The first formula is:

[0106]

[0107] in, The first risk value is N, where N is the number of work surfaces. Where D is the preset maximum number of working faces, and D is the mining depth. The preset target maximum mining depth is defined by a and b, where a and b are weighting coefficients, and a+b=1.

[0108] The second risk value is determined using the second formula based on the coal seam thickness and coal seam temperature and humidity.

[0109] The second formula is:

[0110]

[0111]

[0112] in, The second risk value is H, where H is the coal seam thickness. The preset target maximum coal seam thickness, The values ​​represent the temperature and humidity of the coal seam, where c and d are weighting coefficients, c+d=1, and T is the coal seam temperature. The upper limit of the safe temperature, M is the humidity of the coal seam. This is the upper limit of safe humidity.

[0113] In one embodiment of this application, the control strategy determination module 22 is specifically used to determine the target ventilation control mode as the first control mode if the safety risk coefficient is greater than the risk threshold.

[0114] If the safety risk coefficient is less than or equal to the risk threshold, then the target ventilation control mode is determined to be the second control mode;

[0115] The data acquisition frequency corresponding to the first control mode is greater than the data acquisition frequency corresponding to the second control mode; the fan frequency adjustment step size and fan opening adjustment step size corresponding to the first control mode are greater than the fan frequency adjustment step size and fan opening adjustment step size corresponding to the second control mode, respectively.

[0116] In one embodiment of this application, the mine environment data includes mine gas data and mine temperature and humidity; the control strategy determination module 22 is further configured to acquire mine environment data based on a first data acquisition strategy if the target ventilation control mode is a first control mode; the first data acquisition strategy is to acquire mine gas data based on a first frequency and mine temperature and humidity based on a second frequency.

[0117] If the target ventilation control mode is the second control mode, then mine environmental data is acquired based on the second data acquisition strategy; the second data acquisition strategy is to acquire mine gas data based on the third frequency and mine temperature and humidity based on the fourth frequency.

[0118] The first frequency is greater than the third frequency, and the second frequency is greater than the fourth frequency.

[0119] In one embodiment of this application, the control strategy determination module 22 is further configured to determine a parameter adjustment sequence based on mine environment data and ventilation equipment operating parameters; the parameter adjustment sequence includes at least one of the following: number of fans in operation, fan frequency, and fan opening degree.

[0120] Based on mine environmental data, determine the target adjustment direction for the operating parameters of ventilation equipment in the parameter adjustment sequence;

[0121] The target adjustment value is determined based on the target ventilation control mode and the target adjustment direction;

[0122] The target adjustment strategy is determined based on the target adjustment direction and target adjustment value.

[0123] In one embodiment of this application, the control strategy determination module 22 is further configured to determine the target adjustment direction of the ventilation equipment operating parameters in the parameter adjustment sequence as the positive direction if the mine environment data does not meet the first condition.

[0124] If the mine environmental data meets the first condition, then the target adjustment direction is determined to be negative or unchanged;

[0125] Positive measures include increasing the number of operating fans, increasing the fan frequency, and increasing the fan opening degree; the first condition is that the mine gas data does not exceed the gas safety threshold and the mine temperature and humidity do not exceed the temperature and humidity safety threshold.

[0126] Negative directions include reducing the number of operating fans, lowering the fan frequency, and reducing the fan opening degree. Remaining unchanged means not adjusting the number of operating fans, fan frequency, or fan opening degree.

[0127] In one embodiment of this application, the parameter adjustment sequence includes the number of fans operating, the fan frequency, and the fan opening degree; the control strategy determination module 22 is further used to determine the target adjustment step size based on the target ventilation control mode; the target adjustment step size includes the fan frequency adjustment step size and the fan opening degree adjustment step size;

[0128] The adjustment value for the number of operating fans is determined based on the target adjustment direction, the number of operating fans, and the total number of fans; the adjustment value for the fan frequency is determined based on the target adjustment direction, the fan frequency, and the fan frequency adjustment step size; and the adjustment value for the fan opening is determined based on the target adjustment direction, the fan opening degree, and the fan opening adjustment step size.

[0129] See Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. Figure 3 The electronic device 300 in this embodiment may include one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of the modules in the aforementioned system embodiments, for example... Figure 2 The functions of the control mode division module 21, control strategy determination module 22, and control module 23 are shown.

[0130] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0131] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display (LCD, etc.), a speaker, etc.

[0132] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store information about the ventilation device ID.

[0133] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation methods described in the embodiments of the mine ventilation control method provided in the embodiments of this application, or they can execute the implementation methods of the electronic device 300 described in the embodiments of this application, which will not be repeated here.

[0134] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0135] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, etc., equipped on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0136] Those skilled in the art will recognize that the modules / units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0137] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0138] In the embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules, units, or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces or modules / units, or it may be an electrical, mechanical, or other form of connection.

[0139] The modules / units described as separate components may or may not be physically separate. Similarly, the components shown as modules / units may or may not be physical modules / units; they may be located in one place or distributed across multiple network modules / units. Some or all of the modules / units can be selected to achieve the purpose of the embodiments in this application, depending on actual needs.

[0140] Furthermore, the functional modules / units in the various embodiments of this application can be integrated into one processing module / unit, or each module / unit can exist physically separately, or two or more modules / units can be integrated into one module / unit. The integrated modules / units described above can be implemented in hardware or as software functional modules / units.

[0141] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and such modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for controlling mine ventilation, characterized in that, include: The first risk value is determined based on the number of working faces and the mining depth, and the second risk value is determined based on the coal seam thickness and the coal seam temperature and humidity. If the mining stage type is tunneling, then the target weight coefficient matrix is ​​determined to be the first weight coefficient matrix; If the mining stage type is longwall mining, then the target weight coefficient matrix is ​​determined as the second weight coefficient matrix; based on the target weight coefficient matrix, the first risk value and the second risk value are weighted and summed to obtain the safety risk coefficient; The target ventilation control mode is determined based on the aforementioned safety risk coefficient; In the first weighting coefficient matrix, the weighting coefficient of the first risk value is greater than the weighting coefficient of the second risk value; In the second weighting coefficient matrix, the weighting coefficient of the first risk value is no greater than the weighting coefficient of the second risk value; Mine environmental data is acquired based on the target ventilation control mode; The target adjustment strategy is determined based on the mine environment data, the target ventilation control mode, and the ventilation equipment operating parameters; the ventilation equipment operating parameters include the number of fans in operation, fan frequency, and fan opening degree. The operating parameters of the ventilation equipment are controlled based on the target adjustment strategy.

2. The mine ventilation control method as described in claim 1, characterized in that, The first risk value is determined based on the number of working faces and the mining depth, and the second risk value is determined based on the coal seam thickness and the temperature and humidity of the coal seam, including: Based on the number of working faces and the mining depth, the first risk value is determined using the first formula. The first formula is: in, The first risk value is N, where N is the number of work surfaces. Where D is the preset maximum number of working faces, and D is the mining depth. The preset target maximum mining depth is defined by a and b, where a and b are weighting coefficients, and a+b=1. The second risk value is determined using the second formula based on the coal seam thickness and coal seam temperature and humidity. The second formula is: in, The second risk value is H, where H is the coal seam thickness. The preset target maximum coal seam thickness, The values ​​represent the temperature and humidity of the coal seam, where c and d are weighting coefficients, c+d=1, and T is the coal seam temperature. The upper limit of the safe temperature, M is the humidity of the coal seam. This is the upper limit of safe humidity.

3. The mine ventilation control method as described in claim 1, characterized in that, The determination of the target ventilation control mode based on the safety risk coefficient includes: If the safety risk coefficient is greater than the risk threshold, then the target ventilation control mode is determined to be the first control mode; If the safety risk coefficient is less than or equal to the risk threshold, then the target ventilation control mode is determined to be the second control mode; The data acquisition frequency corresponding to the first control mode is greater than the data acquisition frequency corresponding to the second control mode; the fan frequency adjustment step size and fan opening adjustment step size corresponding to the first control mode are respectively greater than the fan frequency adjustment step size and fan opening adjustment step size corresponding to the second control mode.

4. The mine ventilation control method as described in claim 3, characterized in that, The mine environmental data includes mine gas data and mine temperature and humidity; The acquisition of mine environmental data based on the target ventilation control mode includes: If the target ventilation control mode is the first control mode, then mine environmental data is acquired based on the first data acquisition strategy; the first data acquisition strategy is to acquire mine gas data based on a first frequency and mine temperature and humidity based on a second frequency. If the target ventilation control mode is the second control mode, then mine environmental data is acquired based on the second data acquisition strategy; the second data acquisition strategy is to acquire mine gas data based on the third frequency and mine temperature and humidity based on the fourth frequency. The first frequency is greater than the third frequency, and the second frequency is greater than the fourth frequency.

5. The mine ventilation control method as described in claim 1, characterized in that, The determination of the target adjustment strategy based on the mine environment data, the target ventilation control mode, and the operating parameters of the ventilation equipment includes: A parameter adjustment sequence is determined based on the mine environment data and the operating parameters of the ventilation equipment; the parameter adjustment sequence includes at least one of the following: the number of operating fans, the fan frequency, and the fan opening degree. Based on the mine environment data, determine the target adjustment direction for the operating parameters of the ventilation equipment in the parameter adjustment sequence; The target adjustment value is determined based on the target ventilation control mode and the target adjustment direction; The target adjustment strategy is determined based on the target adjustment direction and the target adjustment value.

6. The mine ventilation control method as described in claim 5, characterized in that, The mine environmental data includes mine gas data and mine temperature and humidity; The step of determining the target adjustment direction for the ventilation equipment operating parameters in the parameter adjustment sequence based on the mine environmental data includes: If the mine environment data does not meet the first condition, then the target adjustment direction for the ventilation equipment operating parameters in the parameter adjustment sequence is determined to be the positive direction; If the mine environment data meets the first condition, then the target adjustment direction is determined to be negative or unchanged; The positive direction includes increasing the number of operating fans, increasing the frequency of fans, and increasing the opening degree of fans; the first condition is that the mine gas data does not exceed the gas safety threshold and the mine temperature and humidity do not exceed the temperature and humidity safety threshold. The negative direction includes reducing the number of operating fans, reducing the fan frequency, and reducing the fan opening degree. The unchanged direction means not adjusting the number of operating fans, fan frequency, and fan opening degree.

7. The mine ventilation control method as described in claim 5, characterized in that, The parameter adjustment sequence includes the number of operating fans, the fan frequency, and the fan opening degree; The process of determining the target adjustment value based on the target ventilation control mode, the target adjustment direction, and the parameter adjustment sequence includes: The target adjustment step size is determined based on the target ventilation control mode; the target adjustment step size includes the fan frequency adjustment step size and the fan opening adjustment step size; The adjustment value for the number of operating fans is determined based on the target adjustment direction, the number of operating fans, and the total number of fans; the adjustment value for the fan frequency is determined based on the target adjustment direction, the fan frequency, and the fan frequency adjustment step size; and the adjustment value for the fan opening is determined based on the target adjustment direction, the fan opening degree, and the fan opening adjustment step size.

8. A mine ventilation control system, characterized in that, include: The control mode division module is used to determine the first risk value based on the number of working faces and mining depth, and to determine the second risk value based on the coal seam thickness and coal seam temperature and humidity. If the mining stage type is tunneling, then the target weight coefficient matrix is ​​determined to be the first weight coefficient matrix; If the mining stage type is longwall mining, then the target weight coefficient matrix is ​​determined as the second weight coefficient matrix; based on the target weight coefficient matrix, the first risk value and the second risk value are weighted and summed to obtain the safety risk coefficient; The target ventilation control mode is determined based on the aforementioned safety risk coefficient; In the first weighting coefficient matrix, the weighting coefficient of the first risk value is greater than the weighting coefficient of the second risk value; In the second weighting coefficient matrix, the weighting coefficient of the first risk value is no greater than the weighting coefficient of the second risk value; The control strategy determination module is used to acquire mine environmental data based on the target ventilation control mode; and to determine a target adjustment strategy based on the mine environmental data, the target ventilation control mode, and ventilation equipment operating parameters; the ventilation equipment operating parameters include the number of fans operating, fan frequency, and fan opening degree. The control module is used to control the operating parameters of the ventilation equipment based on the target adjustment strategy.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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