A mine ventilation self-adaptive intelligent regulation and control method and system based on wireless networking

Abstract

This invention relates to the field of mine ventilation technology and discloses a wireless networking-based adaptive intelligent control method and system for mine ventilation. The method includes: acquiring data; triggering power adjustment of ventilation equipment when environmental parameters in the downstream working area are detected to deteriorate; comparing and analyzing the monitored operating parameters, the relationship between upstream wind pressure and downstream wind speed, with a response benchmark to determine the cause of the deterioration of environmental parameters in the downstream working area; if the cause of deterioration is increased airflow path obstruction, quantifying the degree of obstruction based on the actual relationship between operating parameters, upstream wind pressure, and downstream wind speed; and adjusting the operation strategy of the ventilation system according to the degree of obstruction. This invention, by introducing the concept of a response benchmark and combining real-time monitoring and comparative analysis, can effectively solve the problems of inaccurate diagnosis and untimely response of traditional mine ventilation systems in complex and variable environments.

Description

Technical Field

[0001] This invention relates to the field of mine ventilation technology, specifically to a mine ventilation adaptive intelligent control method and system based on wireless networking. Background Technology

[0002] In modern mine production, ventilation systems are crucial for ensuring the safety of underground workers and the health of the production environment. To overcome the problems of slow response, high energy consumption, and poor equipment coordination caused by traditional manual adjustment based on experience, a wireless networking-based adaptive intelligent control method and system for mine ventilation has been introduced. This system collects environmental data in real time by deploying sensors and actuators throughout the mine, and intelligently adjusts airflow and direction based on this data to achieve refined and efficient ventilation management. However, the complexity and unpredictability of the mine environment mean that even advanced intelligent systems can face unexpected challenges.

[0003] However, because existing systems cannot determine whether the root cause of the problem is a decline in the performance of the ventilation fan itself or a change in the ventilation network structure, the system may issue a series of false alarms, such as "local ventilation fan failure at the mining face" or "abnormal sensor readings at the mining face." This misleads underground maintenance and management personnel to focus their attention on checking the fans and sensors, while neglecting to investigate the ventilation roadway itself. This undoubtedly delays the best opportunity to address the real hazard. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention discloses a mine ventilation adaptive intelligent control method and system based on wireless networking. It aims to solve problems such as slow response, high energy consumption, and poor equipment coordination caused by manual experience-based adjustment in existing mine ventilation systems, as well as the challenges brought by the complexity and unpredictability of the mine environment.

[0005] The technical solution of the present invention is as follows:

[0006] An adaptive intelligent control method for mine ventilation based on wireless networking includes:

[0007] The system acquires the operating parameters of the ventilation equipment in the area to be diagnosed, the wind pressure parameters in the upstream area, the wind speed parameters in the downstream area, and the response benchmark. The response benchmark is the response relationship established based on the operating parameters of the ventilation equipment, the upstream wind pressure, and the downstream wind speed during normal operation of the ventilation system.

[0008] Real-time monitoring of environmental parameters in downstream work areas; when environmental parameters in downstream work areas are detected to deteriorate, the ventilation equipment is triggered to adjust its power.

[0009] During the power adjustment of the ventilation equipment, the changes in operating parameters, upstream wind pressure and downstream wind speed are monitored, and the relationship between the monitored operating parameters, upstream wind pressure and downstream wind speed is compared and analyzed with the response benchmark to determine the causes of the deterioration of environmental parameters in the downstream work area. The causes of deterioration include: increased obstruction of the airflow path or insufficient capacity of the ventilation equipment.

[0010] If the deterioration is caused by increased obstruction of the airflow path, the degree of obstruction can be quantified based on the actual relationship between operating parameters, upstream wind pressure, and downstream wind speed.

[0011] Adjust the operation strategy of the ventilation system according to the degree of obstruction.

[0012] Furthermore, it also includes:

[0013] When no deterioration of environmental parameters in the downstream operating area is detected, the operating parameters, wind pressure parameters in the upstream area, and wind speed parameters in the downstream area are periodically analyzed to identify system response drift caused by environmental factors and determine the magnitude and direction of the system response drift.

[0014] Based on the magnitude and direction of the system response drift, the response benchmark is incrementally adjusted so that it can continuously reflect the normal operating status of the ventilation system under the current environment.

[0015] Furthermore, the steps of performing trend analysis on operating parameters, upstream wind pressure parameters, and downstream wind speed parameters to identify system response drift caused by environmental factors and determine the magnitude and direction of the system response drift include:

[0016] Acquire various environmental parameters related to the operation of the ventilation system;

[0017] Obtain the change curves of the response relationship between each environmental parameter and operating parameter, wind pressure parameter in the upstream area, and wind speed parameter in the downstream area;

[0018] Determine whether system response drift exists based on the changing trend of the curve;

[0019] When system response drift is identified, the current changes of various environmental parameters are analyzed to determine the direction of system response drift.

[0020] Based on the change curves corresponding to each environmental parameter, calculate the contribution weight of each environmental parameter to the current system response drift;

[0021] Based on contribution weights, the influence of different environmental factors on system response drift is distinguished and quantified in order to determine the magnitude of system response drift.

[0022] Furthermore, the steps of monitoring changes in operating parameters, upstream wind pressure, and downstream wind speed, and comparing the monitored relationships between these parameters with a response baseline to determine the causes of environmental parameter deterioration in the downstream work area include:

[0023] The changes in operating parameters, upstream wind pressure, and downstream wind speed monitored during the power regulation of ventilation equipment are transformed into the membership degrees of fuzzy sets.

[0024] Based on the response benchmark, the membership degree of the fuzzy set is inferred to obtain the fuzzy output set;

[0025] The fuzzy output set is transformed into anomaly index through the defuzzification process;

[0026] Based on the anomaly index, the confidence level of increased airflow path obstruction and insufficient ventilation equipment capacity is quantified;

[0027] Based on confidence levels, determine the causes of the deterioration of environmental parameters in downstream operating areas.

[0028] Specifically, the steps for adjusting the operation strategy of the ventilation system according to the degree of obstruction include:

[0029] Obtain gas concentration and wind speed parameters in the upstream area;

[0030] By combining the gas concentration parameters of the upstream area, the air volume entering the area to be diagnosed, and the degree of obstruction, the gas diffusion and accumulation situation inside the area to be diagnosed is inferred, and the internal environmental conditions of the area to be diagnosed are obtained. The air volume entering the area to be diagnosed is calculated based on the wind speed parameters of the upstream area and the preset roadway cross-section size.

[0031] Based on the cause of the deterioration and the internal environment of the area to be diagnosed, a troubleshooting guide is generated to adjust the operation strategy of the ventilation system.

[0032] Based on this, and according to the causes of deterioration and the internal environmental conditions of the area to be diagnosed, a troubleshooting guide is generated to guide the steps for adjusting the ventilation system operation strategy, including:

[0033] To obtain the confidence level of the cause of deterioration and the reliability of assessing the internal environmental conditions of the area to be diagnosed;

[0034] When the confidence or reliability is lower than a preset threshold, a guideline is generated that includes on-site verification or multi-source cross-verification steps. On-site verification or multi-source cross-verification steps include requiring on-site personnel to use portable detection equipment to conduct supplementary measurements of specific areas, or to confirm changes in roadway structure through manual inspection.

[0035] Based on confidence level or reliability, the risk level and safe operating procedures are determined from a pre-set guidance library, and the corresponding risk level and safe operating procedures are marked in the guidance. The guidance library includes multiple sets of risk levels and safe operating procedures that match different confidence or reliability ranges. The safe operating procedures include requiring personnel to wear a higher level of respirator before entering the area to be diagnosed, or to conduct the investigation in the presence of a safety officer.

[0036] Furthermore, the steps to assess the reliability of the internal environmental conditions of the area to be diagnosed include:

[0037] It continuously receives data from multiple different types of sensors within the mine's ventilation system, as well as data from historical operation records and manual inspection reports;

[0038] By integrating data from different types of sensors, as well as data from historical operation records and manual inspection reports, the reliability of the internal environmental conditions of the area to be diagnosed is calculated.

[0039] Based on the above, the steps for calculating the reliability of the internal environmental conditions of the area to be diagnosed, by integrating data from different types of sensors, as well as data from historical operation records and manual inspection reports, include:

[0040] The sensor data is preliminarily processed to identify and filter out abnormal fluctuations caused by transient interference, thereby obtaining local environmental state information;

[0041] Analyze historical operation records and manual inspection reports to extract long-term trend characteristics.

[0042] Local environmental state information is used as the main input, and time alignment is performed based on the timestamp of the local environmental state information and long-term trend feature information.

[0043] The influence weight of long-term trend feature information is dynamically adjusted based on the instantaneous change of local environmental state information. Specifically, when the local environmental state information changes drastically, the influence weight of long-term trend feature information is reduced; when the local environmental state information changes steadily, the influence weight of long-term trend feature information is increased.

[0044] Based on the fusion of local environmental state information and long-term trend characteristic information by influencing weights, comprehensive environmental state information is obtained;

[0045] Based on comprehensive environmental status information, the reliability of the internal environmental conditions of the area to be diagnosed is calculated.

[0046] More specifically, the steps for calculating the reliability of the internal environmental conditions of the area to be diagnosed based on comprehensive environmental status information include:

[0047] A quality assessment of comprehensive environmental status information is conducted to obtain multiple assessment indicators, including information consistency, stability of information changes, and reliability of data sources.

[0048] Based on preset evaluation rules, multiple evaluation indicators are weighted and fused to obtain a quantitative value of the reliability of the internal environment of the area to be diagnosed.

[0049] A wireless networking-based adaptive intelligent control system for mine ventilation is provided to implement the aforementioned wireless networking-based adaptive intelligent control method for mine ventilation. The system includes:

[0050] The data acquisition module is used to acquire the operating parameters of the ventilation equipment in the area to be diagnosed, the wind pressure parameters in the upstream area, the wind speed parameters in the downstream area, and the response benchmark. The response benchmark is the response relationship established based on the operating parameters of the ventilation equipment, the upstream wind pressure, and the downstream wind speed during the normal operation of the ventilation system.

[0051] The trigger adjustment module is used to monitor the environmental parameters of the downstream work area in real time. When the environmental parameters of the downstream work area are detected to deteriorate, the ventilation equipment is triggered to adjust its power.

[0052] The cause determination module is used to monitor changes in operating parameters, upstream wind pressure, and downstream wind speed during power adjustment of ventilation equipment. It compares and analyzes the relationship between the monitored operating parameters, upstream wind pressure, and downstream wind speed with the response benchmark to determine the cause of the deterioration of environmental parameters in the downstream work area. The causes of deterioration include: increased obstruction of the airflow path or insufficient capacity of the ventilation equipment.

[0053] If the cause of the deterioration is increased obstruction of the airflow path, the obstruction level is quantified based on the actual relationship between operating parameters, upstream wind pressure, and downstream wind speed to obtain the degree of obstruction.

[0054] The strategy adjustment module is used to adjust the operating strategy of the ventilation system according to the degree of obstruction.

[0055] Through the above technical solution, the present invention can provide a system carrier for implementing the above method. Through modular design, the integrity and scalability of system functions are ensured, thereby effectively improving the intelligent management level of mine ventilation.

[0056] The beneficial effects of this invention are:

[0057] This invention discloses a wireless networking-based adaptive intelligent control method and system for mine ventilation. The method acquires the operating parameters of ventilation equipment in the area to be diagnosed, the wind pressure parameters of the upstream area, the wind speed parameters of the downstream area, and a response benchmark, while simultaneously monitoring environmental parameters in the downstream work area in real time. When environmental parameters deteriorate, the ventilation equipment is triggered to adjust its power. During adjustment, changes in operating parameters, upstream wind pressure, and downstream wind speed are monitored and compared with the response benchmark to determine the specific cause of the environmental parameter deterioration. If the deterioration is due to increased airflow path obstruction, the degree of obstruction is further quantified, and the ventilation system's operating strategy is adjusted accordingly. By establishing a dynamic response benchmark, this method achieves precise perception and anomaly diagnosis of the ventilation system's operating status, avoiding excessive reliance on human experience in traditional methods. Simultaneously, through real-time monitoring and adaptive adjustment, it rapidly responds to environmental changes, promptly identifies and quantifies issues such as airflow path obstruction, and thus accurately adjusts the ventilation strategy, effectively improving the safety, efficiency, and energy utilization of mine ventilation, overcoming the challenges posed by the complexity and unpredictability of the mine environment. Attached Figure Description

[0058] Figure 1 A flowchart illustrating an adaptive intelligent control method for mine ventilation based on wireless networking, provided in an embodiment of the present invention;

[0059] Figure 2 This is a structural block diagram of a mine ventilation adaptive intelligent control system based on wireless networking, provided as an embodiment of the present invention.

[0060] Labeling Explanation: 210, Data Acquisition Module; 220, Trigger Adjustment Module; 230, Cause Judgment Module; 240, Obstacle Quantification Module; 250, Strategy Adjustment Module. Detailed Implementation

[0061] The technical solutions of this invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some, not all, of the embodiments of this invention. The components of this invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0062] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0063] In modern mine production, ventilation systems are crucial for ensuring the safety of underground workers and the health of the production environment. To overcome the problems of slow response, high energy consumption, and poor equipment coordination caused by traditional manual adjustment, a wireless networking-based adaptive intelligent control method and system for mine ventilation has been introduced. This system collects environmental data in real time by deploying sensors and actuators throughout the mine, and intelligently adjusts airflow and direction based on this data to achieve refined and efficient ventilation management. However, the complexity and unpredictability of the mine environment mean that even advanced intelligent systems can face unexpected challenges.

[0064] Please see Figure 1 This invention proposes an adaptive intelligent control method for mine ventilation based on wireless networking, the method comprising:

[0065] S1. Obtain the operating parameters of the ventilation equipment in the area to be diagnosed, the wind pressure parameters in the upstream area, the wind speed parameters in the downstream area, and the response benchmark. The response benchmark is the response relationship established based on the operating parameters of the ventilation equipment, the upstream wind pressure, and the downstream wind speed during normal operation of the ventilation system.

[0066] S2. Monitor the environmental parameters of the downstream work area. When the environmental parameters of the downstream work area are detected to deteriorate, trigger the ventilation equipment to adjust its power.

[0067] S3. During the power adjustment of the ventilation equipment, monitor the changes in operating parameters, upstream wind pressure and downstream wind speed, and compare the relationship between the monitored operating parameters, upstream wind pressure and downstream wind speed with the response benchmark to determine the cause of the deterioration of environmental parameters in the downstream work area. The cause of deterioration includes: increased obstruction of the airflow path or insufficient capacity of the ventilation equipment.

[0068] S4. If the deterioration is caused by increased obstruction of the airflow path, then the degree of obstruction of the airflow path is quantified based on the actual relationship between the operating parameters, upstream wind pressure and downstream wind speed, and the degree of obstruction is obtained.

[0069] S5. Adjust the operation strategy of the ventilation system according to the degree of obstruction.

[0070] The method proposed in this invention first requires acquiring the operating parameters of the ventilation equipment in the area to be diagnosed, the wind pressure parameters in the upstream area, the wind speed parameters in the downstream area, and the response benchmark. In one embodiment, this data is collected in real time by deploying a sensor network at various key locations in the mine. For example, current and voltage sensors are installed near the ventilation equipment to acquire operating parameters; pressure sensors are installed in the upstream area to acquire wind pressure parameters; and wind speed sensors are installed in the downstream area to acquire wind speed parameters. The establishment of the response benchmark can be achieved through long-term data acquisition and statistical analysis during normal operation of the ventilation system, using methods such as regression analysis and machine learning to establish a mathematical model or mapping relationship between the ventilation equipment operating parameters, upstream wind pressure, and downstream wind speed. For example, a polynomial model can be established, using fan power and upstream wind pressure as inputs to predict downstream wind speed, and the deviation between the actual observed value and the predicted value can be used as the response feature of normal operation.

[0071] Next, the system will monitor environmental parameters in the downstream work area in real time. When environmental parameters in the downstream work area deteriorate, such as excessive methane concentration or excessively low oxygen concentration, the system will trigger the ventilation equipment to adjust its power. Monitoring of environmental parameters can be achieved by deploying methane sensors, oxygen sensors, and temperature sensors in the downstream work area. When any environmental parameter exceeds a preset safety threshold, it is considered a deterioration of the environmental parameters. The ventilation equipment is triggered to adjust its power by sending a command to its controller, causing it to automatically increase the airflow output, for example, by increasing the fan speed from a preset normal operating value to a higher emergency operating value, thereby improving environmental conditions by increasing ventilation volume.

[0072] During power adjustment of the ventilation equipment, the system continuously monitors changes in operating parameters, upstream air pressure, and downstream air velocity. Simultaneously, the actual relationship between the monitored operating parameters, upstream air pressure, and downstream air velocity is compared with a pre-established response baseline to determine the causes of environmental parameter deterioration in the downstream work area. The main causes of deterioration include increased obstruction of the airflow path or insufficient capacity of the ventilation equipment. For example, during power adjustment, if the operating parameters of the ventilation equipment increase significantly, but the changes in upstream air pressure and downstream air velocity are not obvious, or the increase in air velocity is much lower than expected, this may indicate obstruction in the airflow path, leading to increased wind resistance. Conversely, if the ventilation equipment has reached its maximum power, but the air pressure and air velocity still fail to reach the expected levels, it may indicate that the ventilation equipment itself is insufficient to meet the current environmental demands. This comparative analysis can be achieved by calculating indicators such as the deviation and trend difference between the actual relationship and the response baseline.

[0073] If the analysis determines that the deterioration is caused by increased obstruction of the airflow path, then the degree of obstruction needs to be quantified based on the actual relationship between operating parameters, upstream wind pressure, and downstream wind speed. For example, the equivalent drag coefficient of the current airflow path can be calculated using the fan characteristic curve, drag formula, and actual measured wind pressure and speed data. This equivalent drag coefficient can then be compared with the drag coefficient during normal operation to quantify the degree of obstruction. The quantified value of the obstruction degree can be a percentage, representing how much the wind resistance has increased, or a specific difference in drag coefficient.

[0074] Finally, based on the quantified level of obstruction, the system adjusts the ventilation system's operating strategy. For example, if the obstruction level is high, the system generates instructions suggesting that on-site personnel inspect specific areas to find and remove obstacles in the airflow path, such as landslides or equipment accumulation. Alternatively, the system intelligently adjusts the operating modes of other ventilation equipment based on the level of obstruction, such as increasing the power of nearby fans or changing the opening of local dampers, to compensate for insufficient ventilation caused by obstruction and ensure effective ventilation in the area under diagnosis.

[0075] This invention effectively solves the problems of inaccurate diagnosis and untimely response of traditional mine ventilation systems in complex and variable environments by introducing the concept of response benchmark and combining real-time monitoring and comparative analysis.

[0076] The core innovation of this invention lies in establishing a "response baseline" during the normal operation of the ventilation system and dynamically comparing actual operating data with this baseline. When environmental parameters deteriorate, the system not only triggers power adjustment, but more importantly, it monitors changes in key parameters during the adjustment process and compares them with the response baseline. This dynamic comparison mechanism enables the system to accurately identify the causes of deterioration. For example, when airflow path obstruction increases, even if the ventilation equipment power is increased, the response of air pressure and air velocity will deviate from the normal baseline, exhibiting a "laborious but ineffective" characteristic; while when the ventilation equipment capacity is insufficient, it may manifest as power reaching its limit, but air pressure and air velocity still failing to meet the demand. This refined diagnostic capability is difficult to achieve with existing technologies.

[0077] Traditional adaptive intelligent control methods for mine ventilation rely primarily on pre-established response benchmarks for comparative analysis when determining the causes of environmental parameter deterioration in downstream work areas. However, the mine environment is complex and variable, with environmental factors (such as temperature, humidity, and atmospheric pressure) changing slowly over time. These changes can cause subtle drifts in the normal operating state of the ventilation system, gradually decoupling the original response benchmark from the actual situation. If this problem is not addressed, the system cannot detect these response drifts caused by environmental factors when environmental parameters are not deteriorating. This can lead to inaccurate diagnosis and adjustment based on outdated response benchmarks when environmental parameters worsen in the future, or even misjudgments, affecting the timeliness and effectiveness of control. To address this, this invention proposes a method that uses periodic trend analysis and incremental adjustment of the response benchmark when environmental parameter deterioration is not detected, ensuring that the response benchmark continuously reflects the normal operating state of the ventilation system under the current environment.

[0078] In some of the embodiments of the present invention described above, the invention further includes:

[0079] When no deterioration of environmental parameters in the downstream operating area is detected, the operating parameters, wind pressure parameters in the upstream area, and wind speed parameters in the downstream area are periodically analyzed to identify system response drift caused by environmental factors and determine the magnitude and direction of the system response drift.

[0080] Based on the magnitude and direction of the system response drift, the response benchmark is incrementally adjusted so that it can continuously reflect the normal operating status of the ventilation system under the current environment.

[0081] The present invention effectively solves the aforementioned problems by introducing a periodic trend analysis and an incremental adjustment mechanism for the response benchmark. Specifically, when the system does not detect a deterioration in environmental parameters in the downstream working area, it does not simply maintain the existing state, but actively and periodically monitors and analyzes the operating parameters of the ventilation equipment, the wind pressure parameters in the upstream area, and the wind speed parameters in the downstream area. In this way, the system can promptly capture slowly occurring system response drifts caused by environmental factors. Once such a drift is identified, the system further quantifies its magnitude and direction, thereby accurately understanding the degree and trend of deviation between the current ventilation system and the initial response benchmark under normal operating conditions. Based on this information, the system incrementally adjusts the response benchmark, enabling it to dynamically adapt to long-term changes in the mine environment. Thus, even without sudden environmental deterioration, the response benchmark maintains its accuracy and timeliness, ensuring that the benchmark used for future fault diagnosis and strategy adjustments is highly matched to the current actual operating environment.

[0082] In some embodiments of the present invention described above, when no deterioration of environmental parameters in the downstream operating area is detected, it is necessary to periodically perform trend analysis on the operating parameters, wind pressure parameters in the upstream area, and wind speed parameters in the downstream area to identify system response drift caused by environmental factors and determine the magnitude and direction of the system response drift. Specifically, the steps of performing trend analysis on the operating parameters, wind pressure parameters in the upstream area, and wind speed parameters in the downstream area to identify system response drift caused by environmental factors and determine the magnitude and direction of the system response drift include:

[0083] Acquire various environmental parameters related to the operation of the ventilation system;

[0084] Obtain the change curves of the response relationship between each environmental parameter and operating parameter, wind pressure parameter in the upstream area, and wind speed parameter in the downstream area;

[0085] Determine whether system response drift exists based on the changing trend of the curve;

[0086] When system response drift is identified, the current changes of various environmental parameters are analyzed to determine the direction of system response drift.

[0087] Based on the change curves corresponding to each environmental parameter, calculate the contribution weight of each environmental parameter to the current system response drift;

[0088] Based on contribution weights, the influence of different environmental factors on system response drift is distinguished and quantified in order to determine the magnitude of system response drift.

[0089] This invention acquires and analyzes various environmental parameters related to the operation of a ventilation system, establishing change curves showing the response relationships between these environmental parameters and the system's operating parameters, upstream wind pressure, and downstream wind speed. This allows for a refined capture of the potential impact of environmental factors on the ventilation system's performance. When the system response drifts, the current changes in each environmental parameter are analyzed to accurately determine the direction of the drift and identify which environmental factors are causing the deviation in system performance. Furthermore, by calculating the contribution weight of each environmental parameter to the system response drift and using these weights to differentiate and quantify the influence of different environmental factors, the magnitude of the system response drift can be accurately determined. This detailed analysis mechanism enables the system to deeply understand how environmental changes affect the normal operation of the ventilation system, providing a scientific and quantitative basis for subsequent incremental adjustments to the response benchmark, ensuring the accuracy and adaptability of the benchmark.

[0090] In some embodiments of the present invention, during power adjustment of the ventilation equipment, changes in operating parameters, upstream wind pressure, and downstream wind speed are monitored and compared with a response benchmark to determine the cause of environmental parameter deterioration in the downstream working area. However, in actual mine environments, the operating status of ventilation systems is affected by various factors, and parameter changes are often fuzzy and uncertain. Simple threshold judgments or linear comparison analyses may be insufficient to accurately capture complex system behaviors, resulting in insufficient accuracy and robustness in determining the cause of deterioration, and even potential misjudgments. Failure to address these issues may delay troubleshooting and strategy adjustments, impacting mine operation safety and efficiency. Therefore, the present invention further proposes a method for determining the cause of deterioration based on fuzzy logic to improve the accuracy and adaptability of the judgment.

[0091] This invention further proposes a step to monitor changes in the aforementioned operating parameters, upstream wind pressure, and downstream wind speed, and to compare and analyze the relationship between the monitored operating parameters, upstream wind pressure, and downstream wind speed with a response benchmark to determine the causes of deterioration in environmental parameters in the downstream operating area. This includes:

[0092] The changes in operating parameters, upstream wind pressure, and downstream wind speed monitored during the power regulation of ventilation equipment are transformed into the membership degrees of fuzzy sets.

[0093] Based on the response benchmark, the membership degree of the fuzzy set is inferred to obtain the fuzzy output set;

[0094] The fuzzy output set is transformed into anomaly index through the defuzzification process;

[0095] Based on the anomaly index, the confidence level of increased airflow path obstruction and insufficient ventilation equipment capacity is quantified;

[0096] Based on the confidence level, determine the causes of the deterioration of environmental parameters in the downstream operating area.

[0097] This invention effectively addresses the limitations of traditional comparative analysis methods in handling the complexity and uncertainty of mine ventilation systems by introducing fuzzy logic. Specifically, it transforms monitored operating parameters, upstream air pressure, and downstream wind speed changes into membership degrees of fuzzy sets, enabling the system to tolerate data inaccuracies and fuzziness, and avoiding potential misjudgments due to preset thresholds. Subsequently, fuzzy inference based on response benchmarks simulates expert experience, comprehensively judging from multi-dimensional fuzzy inputs to more accurately capture potential deterioration patterns. A defuzzification process transforms fuzzy outputs into anomaly indices, achieving a shift from qualitative judgment to quantitative assessment, providing a solid foundation for subsequent confidence quantification. Finally, based on quantified confidence levels, the causes of deterioration are determined, making the judgment not only clear but also credible, significantly improving the accuracy and robustness of deterioration cause diagnosis.

[0098] In some embodiments of the present invention, an operational strategy for adjusting the ventilation system based on the degree of obstruction of the airflow path is proposed. However, in its implementation, adjusting the strategy solely based on the degree of obstruction may not fully reflect the actual environmental risks within the area to be diagnosed, such as gas diffusion and accumulation, resulting in insufficient targeting of the adjustment strategy or potential safety hazards. To address this, the present invention further proposes a more refined strategy adjustment method. By comprehensively considering multiple environmental parameters, it infers the internal environmental conditions of the area and generates specific troubleshooting guidelines to achieve safer and more effective adjustment of the ventilation system's operational strategy.

[0099] The steps described above for adjusting the ventilation system operation strategy according to the degree of obstruction include:

[0100] Obtain gas concentration and wind speed parameters in the upstream area;

[0101] By combining the gas concentration parameters of the upstream area, the air volume entering the area to be diagnosed, and the degree of obstruction, the gas diffusion and accumulation situation inside the area to be diagnosed is inferred, and the internal environmental conditions of the area to be diagnosed are obtained. The air volume entering the area to be diagnosed is calculated based on the wind speed parameters of the upstream area and the preset roadway cross-section size.

[0102] Based on the cause of the deterioration and the internal environment of the area to be diagnosed, a troubleshooting guide is generated to adjust the operation strategy of the ventilation system.

[0103] Specifically, when adjusting the ventilation system's operating strategy, it's necessary to obtain gas concentration and wind speed parameters from the upstream area. These parameters are crucial data for assessing the internal environmental conditions of the area to be diagnosed. Gas concentration parameters can include the concentration of harmful gases such as methane and carbon monoxide, while wind speed reflects the intensity of airflow. The obtained upstream gas concentration parameters, the airflow entering the area to be diagnosed, and the quantified level of obstruction are comprehensively analyzed. The airflow entering the area to be diagnosed is calculated based on the upstream wind speed parameters and the pre-set tunnel cross-sectional size. This method infers the gas diffusion and accumulation within the area to be diagnosed, thus obtaining a more accurate understanding of the internal environmental conditions. For example, when the level of obstruction is high and the upstream gas concentration is high, it is inferred that there may be a risk of harmful gas accumulation within the area to be diagnosed. Based on this, and according to the identified causes of deterioration and the inferred internal environmental conditions of the area to be diagnosed, specific troubleshooting guidelines are generated. These guidelines aim to provide on-site personnel with clear operating procedures and suggestions for adjusting the ventilation system's operating strategy. The guidelines can include specific measures such as adjusting local ventilation facilities, removing obstructions, and strengthening gas monitoring.

[0104] This invention, by introducing gas concentration and wind speed parameters from the upstream area and combining them with quantified obstruction levels, enables a more comprehensive assessment of the actual environmental conditions within the area to be diagnosed, particularly gas diffusion and accumulation. This in-depth inference of the internal environmental conditions makes the subsequent troubleshooting guidelines more targeted and effective. By combining the causes of deterioration with specific internal environmental conditions, this solution elevates the assessment from a single obstruction level to providing early warnings of potential hazards (such as excessive levels of harmful gases) and specific countermeasures, thereby ensuring that the adjusted ventilation system operation strategy effectively solves the problem and guarantees mine operation safety.

[0105] In some embodiments of the present invention described above, troubleshooting guidelines can be generated based on the cause of deterioration and the internal environmental conditions of the area to be diagnosed, in order to adjust the operation strategy of the ventilation system. However, in practical applications, if the confidence level of the judgment on the cause of deterioration is low, or if the reliability of the inferred internal environmental conditions of the area to be diagnosed is questionable, guidelines generated directly based on this information may be misleading or lack sufficient safety, thereby affecting the accuracy of troubleshooting and the safety of personnel operations. Failure to address these issues may lead to low troubleshooting efficiency or even safety accidents.

[0106] To address this, the present invention further proposes the steps of generating troubleshooting guidelines based on the causes of deterioration and the internal environmental conditions of the area to be diagnosed, in order to adjust the ventilation system operation strategy, including:

[0107] To obtain the confidence level of the cause of deterioration and the reliability of assessing the internal environmental conditions of the area to be diagnosed;

[0108] When the confidence or reliability is lower than a preset threshold, a guideline is generated that includes on-site verification or multi-source cross-verification steps. On-site verification or multi-source cross-verification steps include requiring on-site personnel to use portable detection equipment to conduct supplementary measurements of specific areas, or to confirm changes in roadway structure through manual inspection.

[0109] Based on confidence level or reliability, the risk level and safe operating procedures are determined from a pre-set guidance library, and the corresponding risk level and safe operating procedures are marked in the guidance. The guidance library includes multiple sets of risk levels and safe operating procedures that match different confidence or reliability ranges. The safe operating procedures include requiring personnel to wear a higher level of respirator before entering the area to be diagnosed, or to conduct the investigation in the presence of a safety officer.

[0110] This invention effectively addresses the potential for misleading or unsafe guidelines by introducing assessments of the confidence level of the cause of deterioration and the reliability of the internal environmental conditions of the area to be diagnosed. Specifically, when the system's judgment of the cause of deterioration or its assessment of the internal environmental conditions is uncertain—that is, when the confidence level or reliability is below a preset threshold—the system no longer blindly generates conventional guidelines. Instead, it intelligently generates guidelines that include on-site verification or multi-source cross-verification steps. This proactively guides on-site personnel to conduct supplementary verification when information is insufficient or uncertain, thereby improving the accuracy and reliability of troubleshooting. Simultaneously, by determining and labeling risk levels and safe operating procedures from a preset guide library based on confidence level or reliability, this invention ensures appropriate safety guarantees for operators under different risk levels, avoiding potential safety risks caused by information uncertainty, thereby enhancing the safety and practicality of the entire ventilation system control method.

[0111] Specifically, in the above-described implementation of generating troubleshooting guidelines to adjust ventilation system operation strategies, the step of assessing the reliability of the internal environmental conditions of the area to be diagnosed may include the following:

[0112] It continuously receives data from multiple different types of sensors within the mine's ventilation system, as well as data from historical operation records and manual inspection reports;

[0113] By integrating data from different types of sensors, as well as data from historical operation records and manual inspection reports, the reliability of the internal environmental conditions of the area to be diagnosed is calculated.

[0114] The system continuously receives data from multiple different types of sensors within the mine's ventilation system, as well as data from historical operation records and manual inspection reports, aiming to build a comprehensive and real-time information input system. Specifically, sensor data can include, but is not limited to, real-time physical quantities collected by wind speed sensors, wind pressure sensors, gas concentration sensors (e.g., methane, carbon monoxide), and temperature sensors. These sensors are deployed at key nodes and areas to be diagnosed in the mine's ventilation system to provide accurate instantaneous environmental parameters. Historical operation records can be obtained from the mine's central monitoring system or a dedicated database, containing information on parameter changes during the long-term operation of the ventilation system, equipment maintenance records, and past failure cases, revealing the system's operational patterns and potential trends. Furthermore, manual inspection reports provide on-site personnel with direct observations of the environmental conditions in specific areas, preliminary judgments of abnormalities, and unstructured textual descriptions, serving as an important supplement to automated data acquisition. By continuously receiving this multi-source heterogeneous data, a sufficient information foundation can be ensured for assessing the mine's environmental conditions.

[0115] This invention constructs a multi-dimensional, multi-layered data input system by continuously receiving data from multiple different types of sensors, historical operation records, and manual inspection reports. These data sources each provide different perspectives and information regarding the operational status of the mine ventilation system and the internal environment of the area to be diagnosed. For example, sensor data provides real-time, quantified physical parameters, historical operation records reveal the long-term operational patterns and trends of the system, while manual inspection reports supplement unstructured information and provide preliminary judgments of anomalies. By fusing these heterogeneous data, they can mutually verify, supplement, and correct each other, thereby overcoming the limitations, errors, or information gaps that may exist with a single data source. This allows for a more comprehensive and accurate reflection of the true internal environment of the area to be diagnosed, providing a solid data foundation for subsequent reliability calculations.

[0116] In some embodiments of the present invention, a method is proposed to fuse data from different types of sensors, historical operation records, and manual inspection reports to calculate the reliability of the internal environmental conditions of the area to be diagnosed. However, in its implementation, simple data fusion methods may not effectively handle instantaneous fluctuations in sensor data, time differences between historical and real-time data, and changes in the reliability of different data sources under different circumstances, which may lead to insufficient accuracy and real-time performance in the environmental reliability assessment. If these problems are not addressed, inaccurate reliability assessments may be provided at critical moments, affecting the effectiveness of fault diagnosis guidance and even jeopardizing mine operation safety. Therefore, the present invention further proposes a more refined data fusion method, which performs preprocessing, trend analysis, time alignment, and dynamic weight adjustment on multi-source data to more accurately calculate the reliability of the internal environmental conditions of the area to be diagnosed.

[0117] To address this, the present invention further proposes a step for calculating the reliability of the internal environmental conditions of the area to be diagnosed by fusing data from different types of sensors, as well as data from historical operation records and manual inspection reports, including:

[0118] The sensor data is preliminarily processed to identify and filter out abnormal fluctuations caused by transient interference, thereby obtaining local environmental state information;

[0119] Analyze historical operation records and manual inspection reports to extract long-term trend characteristics.

[0120] Local environmental state information is used as the main input, and time alignment is performed based on the timestamp of the local environmental state information and long-term trend feature information.

[0121] The influence weight of long-term trend feature information is dynamically adjusted based on the instantaneous change of local environmental state information. Specifically, when the local environmental state information changes drastically, the influence weight of long-term trend feature information is reduced; when the local environmental state information changes steadily, the influence weight of long-term trend feature information is increased.

[0122] Based on the fusion of local environmental state information and long-term trend characteristic information by influencing weights, comprehensive environmental state information is obtained;

[0123] Based on comprehensive environmental status information, the reliability of the internal environmental conditions of the area to be diagnosed is calculated.

[0124] This invention effectively addresses the shortcomings in accuracy and real-time performance that traditional simple data fusion methods may lack when assessing the reliability of the mine's internal environment by introducing refined processing of multi-source data and a dynamic weight adjustment mechanism. Specifically, firstly, preliminary processing of sensor data effectively filters out transient interference, ensuring the purity and accuracy of real-time local environmental state information and avoiding misjudgments caused by noise or abnormal fluctuations. Secondly, analysis of historical operation records and manual inspection reports extracts long-term trend characteristic information, providing a macro-level background and stability reference for reliability assessment. More importantly, time alignment between local environmental state information and long-term trend characteristic information ensures effective fusion of data at different time scales. Based on this, the influence weight of long-term trend characteristic information is dynamically adjusted according to the degree of instantaneous change in local environmental state information. This allows the system to respond quickly and prioritize real-time data when facing sudden and drastic changes, avoiding the lagging influence of historical trends. Conversely, when the environment is stable, it can fully utilize historical experience to provide more robust judgments. This dynamic and adaptive fusion mechanism enables the final comprehensive environmental state information to more accurately and timely reflect the true environmental conditions of the area to be diagnosed, thus providing a solid foundation for reliability calculations.

[0125] In some embodiments of the present invention described above, a scheme for calculating the reliability of the internal environmental conditions of the area to be diagnosed based on comprehensive environmental state information is proposed. Specifically, the steps for calculating the reliability of the internal environmental conditions of the area to be diagnosed based on comprehensive environmental state information include:

[0126] A quality assessment of comprehensive environmental status information is conducted to obtain multiple assessment indicators, including information consistency, stability of information changes, and reliability of data sources.

[0127] Based on preset evaluation rules, multiple evaluation indicators are weighted and fused to obtain a quantitative value of the reliability of the internal environment of the area to be diagnosed.

[0128] This invention conducts a multi-dimensional quality assessment of comprehensive environmental state information and performs weighted fusion based on preset rules. This allows for a systematic consideration of the intrinsic quality of information, its dynamic change characteristics, and the reliability of the original data. Specifically, information consistency ensures logical coordination between different data points or data sources, avoiding misjudgments caused by data conflicts; information change stability reflects the inherent stability of the environmental state, helping to distinguish between abnormal fluctuations and normal changes; and data source credibility guarantees information quality from the source, ensuring the reliability of the input data. By weighted fusion of these indicators, their impact on the final reliability quantification value can be flexibly adjusted according to the actual application scenario and the degree of importance attached to different indicators, thus making the reliability assessment results more comprehensive, objective, and accurate.

[0129] In modern mine production, ventilation systems are crucial for ensuring the safety of underground workers and the health of the production environment. To overcome the problems of slow response, high energy consumption, and poor equipment coordination caused by traditional manual adjustment, a wireless networking-based adaptive intelligent control method and system for mine ventilation has been introduced. This system collects environmental data in real time by deploying sensors and actuators throughout the mine, and intelligently adjusts airflow and direction based on this data to achieve refined and efficient ventilation management. However, the complexity and unpredictability of the mine environment mean that even advanced intelligent systems can face unexpected challenges.

[0130] See Figure 2 This invention proposes a wireless networking-based adaptive intelligent control system for mine ventilation, used to implement the aforementioned wireless networking-based adaptive intelligent control method for mine ventilation, comprising:

[0131] The data acquisition module 210 is used to acquire the operating parameters of the ventilation equipment in the area to be diagnosed, the wind pressure parameters in the upstream area, the wind speed parameters in the downstream area, and the response benchmark. The response benchmark is the response relationship established based on the operating parameters of the ventilation equipment, the upstream wind pressure, and the downstream wind speed during the normal operation of the ventilation system.

[0132] The trigger adjustment module 220 is used to monitor the environmental parameters of the downstream work area in real time. When the environmental parameters of the downstream work area are detected to deteriorate, the ventilation equipment is triggered to adjust its power.

[0133] The cause determination module 230 is used to monitor changes in operating parameters, upstream wind pressure, and downstream wind speed during the power adjustment of ventilation equipment. It compares and analyzes the relationship between the monitored operating parameters, upstream wind pressure, and downstream wind speed with the response benchmark to determine the cause of the deterioration of environmental parameters in the downstream working area. The causes of deterioration include: increased obstruction of the airflow path or insufficient capacity of the ventilation equipment.

[0134] The obstruction quantification module 240, if the cause of the deterioration is the increase in obstruction of the airflow path, quantifies the degree of obstruction of the airflow path based on the actual relationship between the operating parameters, upstream wind pressure and downstream wind speed, and obtains the degree of obstruction.

[0135] Strategy adjustment module 250 is used to adjust the operating strategy of the ventilation system according to the degree of obstruction.

[0136] The wireless networking-based adaptive intelligent control system for mine ventilation proposed in this invention demonstrates significant progress in addressing the challenges faced by mine ventilation systems compared to traditional or existing technologies. Traditional systems often rely on human experience or simple threshold alarms, making it difficult to respond accurately and promptly to complex changes in the mine environment, and even more difficult to effectively distinguish the root causes of ventilation anomalies, resulting in low troubleshooting efficiency and potentially delaying optimal handling. The core innovation of this invention lies in its modular system design, which achieves comprehensive perception, intelligent diagnosis, and adaptive adjustment of the mine ventilation status. The data acquisition module 210 ensures the real-time nature and accuracy of the data; the trigger adjustment module 220 ensures the timeliness of emergency response; and, most importantly, the cause judgment module 230, by introducing a response benchmark and performing dynamic comparative analysis, can accurately identify the specific causes of environmental deterioration, whether it is increased obstruction of the airflow path or insufficient ventilation equipment capacity. This refined diagnostic capability is difficult to achieve with existing technologies. Furthermore, the obstruction quantification module 240 provides a quantified obstruction level, providing a scientific basis for the strategy adjustment module 250 to generate more targeted and efficient operating strategies. The strategy adjustment module 250 can intelligently adjust the fan power and damper opening according to actual conditions, and even generate specific troubleshooting guidelines, thus avoiding the traditional "one-size-fits-all" adjustment method. Through the above system design, the system of this invention can significantly improve the intelligence and safety of the mine ventilation system, reduce energy consumption, and provide more reliable safety protection for underground workers. This integrated and intelligent control system overcomes the shortcomings of existing technologies in terms of diagnostic accuracy, response timeliness, and strategy optimization, providing strong technical support for safe mine production.

[0137] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A wireless networking-based mine ventilation self-adaptive intelligent regulation method, characterized in that, include: The system acquires the operating parameters of the ventilation equipment in the area to be diagnosed, the wind pressure parameters in the upstream area, the wind speed parameters in the downstream area, and the response benchmark. The response benchmark is the response relationship established based on the operating parameters of the ventilation equipment, the upstream wind pressure, and the downstream wind speed during normal operation of the ventilation system. Real-time monitoring of environmental parameters in downstream work areas; when environmental parameters in downstream work areas are detected to deteriorate, the ventilation equipment is triggered to adjust its power. During the power adjustment of the ventilation equipment, the changes in operating parameters, upstream wind pressure and downstream wind speed are monitored, and the relationship between the monitored operating parameters, upstream wind pressure and downstream wind speed is compared and analyzed with the response benchmark to determine the causes of the deterioration of environmental parameters in the downstream work area. The causes of deterioration include: increased obstruction of the airflow path or insufficient capacity of the ventilation equipment. If the deterioration is caused by increased obstruction of the airflow path, the degree of obstruction can be quantified based on the actual relationship between operating parameters, upstream wind pressure, and downstream wind speed. Adjust the operation strategy of the ventilation system according to the degree of obstruction; Also includes: When no deterioration of environmental parameters in the downstream operating area is detected, periodic trend analysis is performed on operating parameters, wind pressure parameters in the upstream area, and wind speed parameters in the downstream area to identify system response drift caused by environmental factors and determine the magnitude and direction of the system response drift. Specifically, this includes: Acquire various environmental parameters related to the operation of the ventilation system; Obtain the change curves of the response relationship between each environmental parameter and operating parameter, wind pressure parameter in the upstream area, and wind speed parameter in the downstream area; Determine whether system response drift exists based on the changing trend of the curve; When system response drift is identified, the current changes of various environmental parameters are analyzed to determine the direction of system response drift. Based on the change curves corresponding to each environmental parameter, calculate the contribution weight of each environmental parameter to the current system response drift; Based on contribution weights, the influence of different environmental factors on system response drift is distinguished and quantified in order to determine the magnitude of system response drift; Based on the magnitude and direction of the system response drift, the response benchmark is incrementally adjusted so that it can continuously reflect the normal operating status of the ventilation system under the current environment.

2. The mine ventilation self-adaptive intelligent regulation and control method based on wireless networking according to claim 1, characterized in that, The steps for monitoring changes in operating parameters, upstream wind pressure, and downstream wind speed, and comparing the monitored relationships between these parameters with a response baseline to determine the causes of environmental parameter deterioration in the downstream work area include: The changes in operating parameters, upstream wind pressure, and downstream wind speed monitored during the power regulation of ventilation equipment are transformed into the membership degrees of fuzzy sets. Based on the response benchmark, the membership degree of the fuzzy set is inferred to obtain the fuzzy output set; The fuzzy output set is transformed into anomaly index through the defuzzification process; Based on the anomaly index, the confidence level of increased airflow path obstruction and insufficient ventilation equipment capacity is quantified; Based on confidence levels, determine the causes of the deterioration of environmental parameters in downstream operating areas.

3. The mine ventilation self-adaptive intelligent regulation and control method based on wireless networking according to claim 1, characterized in that, The steps for adjusting the operation strategy of the ventilation system according to the degree of obstruction include: Obtain gas concentration and wind speed parameters in the upstream area; By combining the gas concentration parameters of the upstream area, the air volume entering the area to be diagnosed, and the degree of obstruction, the gas diffusion and accumulation situation inside the area to be diagnosed is inferred, and the internal environmental conditions of the area to be diagnosed are obtained. The air volume entering the area to be diagnosed is calculated based on the wind speed parameters of the upstream area and the preset roadway cross-section size. Based on the cause of the deterioration and the internal environment of the area to be diagnosed, a troubleshooting guide is generated to adjust the operation strategy of the ventilation system.

4. The mine ventilation self-adaptive intelligent regulation and control method based on wireless networking according to claim 3, characterized in that, Based on the cause of the deterioration and the internal environmental conditions of the area to be diagnosed, a troubleshooting guide is generated to guide the steps for adjusting the ventilation system's operating strategy, including: To obtain the confidence level of the cause of deterioration and the reliability of assessing the internal environmental conditions of the area to be diagnosed; When the confidence or reliability is lower than a preset threshold, a guideline is generated that includes on-site verification or multi-source cross-verification steps. On-site verification or multi-source cross-verification steps include requiring on-site personnel to use portable detection equipment to conduct supplementary measurements of specific areas, or to confirm changes in roadway structure through manual inspection. Based on confidence level or reliability, the risk level and safe operating procedures are determined from a pre-set guidance library, and the corresponding risk level and safe operating procedures are marked in the guidance. The guidance library includes multiple sets of risk levels and safe operating procedures that match different confidence or reliability ranges. The safe operating procedures include requiring personnel to wear a higher level of respirator before entering the area to be diagnosed, or to conduct the investigation in the presence of a safety officer.

5. The mine ventilation self-adaptive intelligent regulation and control method based on wireless networking according to claim 4, characterized in that, The steps for assessing the reliability of the internal environmental conditions of the area to be diagnosed include: It continuously receives data from multiple different types of sensors within the mine's ventilation system, as well as data from historical operation records and manual inspection reports; By integrating data from different types of sensors, as well as data from historical operation records and manual inspection reports, the reliability of the internal environmental conditions of the area to be diagnosed is calculated.

6. The mine ventilation self-adaptive intelligent regulation and control method based on wireless networking according to claim 5, characterized in that, The steps for calculating the reliability of the internal environmental conditions of the area to be diagnosed, by integrating data from different types of sensors, as well as data from historical operation records and manual inspection reports, include: The sensor data is preliminarily processed to identify and filter out abnormal fluctuations caused by transient interference, thereby obtaining local environmental state information; Analyze historical operation records and manual inspection reports to extract long-term trend characteristics. Local environmental state information is used as the main input, and time alignment is performed based on the timestamp of the local environmental state information and long-term trend feature information. The influence weight of long-term trend feature information is dynamically adjusted based on the instantaneous change of local environmental state information. Specifically, when the local environmental state information changes drastically, the influence weight of long-term trend feature information is reduced; when the local environmental state information changes steadily, the influence weight of long-term trend feature information is increased. Based on the fusion of local environmental state information and long-term trend characteristic information by influencing weights, comprehensive environmental state information is obtained; Based on comprehensive environmental status information, the reliability of the internal environmental conditions of the area to be diagnosed is calculated.

7. The mine ventilation self-adaptive intelligent regulation and control method based on wireless networking according to claim 6, characterized in that, The steps for calculating the reliability of the internal environmental conditions of the area to be diagnosed based on comprehensive environmental status information include: A quality assessment of comprehensive environmental status information is conducted to obtain multiple assessment indicators, including information consistency, stability of information changes, and reliability of data sources. Based on preset evaluation rules, multiple evaluation indicators are weighted and fused to obtain a quantitative value of the reliability of the internal environment of the area to be diagnosed.

8. A wireless networking-based adaptive intelligent control system for mine ventilation, which is used to realize the wireless networking-based adaptive intelligent control method for mine ventilation in claim 1, characterized in that, The system includes: The data acquisition module is used to acquire the operating parameters of the ventilation equipment in the area to be diagnosed, the wind pressure parameters in the upstream area, the wind speed parameters in the downstream area, and the response benchmark. The response benchmark is the response relationship established based on the operating parameters of the ventilation equipment, the upstream wind pressure, and the downstream wind speed during the normal operation of the ventilation system. The trigger adjustment module is used to monitor the environmental parameters of the downstream work area in real time. When the environmental parameters of the downstream work area are detected to deteriorate, the ventilation equipment is triggered to adjust its power. The cause determination module is used to monitor changes in operating parameters, upstream wind pressure, and downstream wind speed during power adjustment of ventilation equipment. It compares and analyzes the relationship between the monitored operating parameters, upstream wind pressure, and downstream wind speed with the response benchmark to determine the cause of the deterioration of environmental parameters in the downstream work area. The causes of deterioration include: increased obstruction of the airflow path or insufficient capacity of the ventilation equipment. If the cause of the deterioration is increased obstruction of the airflow path, the obstruction level is quantified based on the actual relationship between operating parameters, upstream wind pressure, and downstream wind speed to obtain the degree of obstruction. The strategy adjustment module is used to adjust the operating strategy of the ventilation system according to the degree of obstruction. Also includes: When no deterioration of environmental parameters in the downstream operating area is detected, periodic trend analysis is performed on operating parameters, wind pressure parameters in the upstream area, and wind speed parameters in the downstream area to identify system response drift caused by environmental factors and determine the magnitude and direction of the system response drift. Specifically, this includes: Acquire various environmental parameters related to the operation of the ventilation system; Obtain the change curves of the response relationship between each environmental parameter and operating parameter, wind pressure parameter in the upstream area, and wind speed parameter in the downstream area; Determine whether system response drift exists based on the changing trend of the curve; When system response drift is identified, the current changes of various environmental parameters are analyzed to determine the direction of system response drift. Based on the change curves corresponding to each environmental parameter, calculate the contribution weight of each environmental parameter to the current system response drift; Based on contribution weights, the influence of different environmental factors on system response drift is distinguished and quantified in order to determine the magnitude of system response drift; Based on the magnitude and direction of the system response drift, the response benchmark is incrementally adjusted so that it can continuously reflect the normal operating status of the ventilation system under the current environment.

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