A parametric modeling method for three-dimensional mine tunnels

Abstract

The present invention provides a parametric modeling method for three-dimensional mine tunnels, which relates to the technical field of digital coal mine exploration. The present invention realizes accurate modeling of mine tunnels and refuge chambers by integrating GIS and BIM technologies. Specifically, a dynamic optimal selection model is constructed by introducing the real-time risk avoidance state coefficient of miners and surrounding disaster data. The model can evaluate and select the optimal refuge chamber in real time according to the risk avoidance state of miners and the safety and disaster avoidance impact of the refuge chamber. This innovation not only improves the efficiency and accuracy of mine safety management, but also provides a scientific basis for mine emergency evacuation decision-making.

Description

Technical Field

[0001] The invention relates to the technical field of coal mine exploration digitization, and in particular to a parametric modeling method for three-dimensional mine tunnels. Background Art

[0002] In the field of mining engineering, the development of 3D modeling technology has become the key to improving the efficiency of mine design and safety management; traditional mine modeling methods mainly rely on 2D plan views and profiles, which have limitations in expressing complex geological structures and tunnel systems. With the rise of geographic information systems (GIS) and building information modeling (BIM) technologies, 3D mining modeling technology has developed rapidly. GIS technology can efficiently process and analyze spatial data, while BIM technology provides more accurate and dynamic design and analysis tools through parametric modeling. Revit software combined with the Dynamo graphical programming platform has become an important tool for realizing parametric modeling of complex buildings and infrastructure, and its application in mining engineering is also increasing.

[0003] In the prior art, publication number CN110363844B discloses a method and system for three-dimensional modeling of coal mine tunnels. First, the longitude and latitude coordinates of each key part of each tunnel of the coal mine are obtained using a GPS positioning device; and converted to a world coordinate system; then, the shape data of the tunnel is measured, and a two-dimensional structural diagram of each tunnel is produced based on the shape data of each tunnel; then, the two-dimensional structural diagram of the tunnel is corrected based on the world coordinates of the key parts; finally, the three-dimensional model of the tunnel is automatically generated by lofting using the generated tunnel centerline and tunnel profile. The present invention uses the world coordinates of each key part to correct the produced two-dimensional structural diagram, thereby ensuring the accuracy of the two-dimensional structural diagram used to generate the three-dimensional model; the present invention generates a three-dimensional model by directly lofting the two-dimensional structural diagram drawn based on the actual measurement data, thereby improving the speed of three-dimensional modeling;

[0004] Deficiencies of existing technologies: Although existing technologies have made significant progress in three-dimensional modeling of mines, there are still some deficiencies in practical applications. First, traditional modeling methods often lack the ability to accurately capture the complex environment and dynamic changes inside mines, especially in the selection of refuge chambers and disaster assessment. Second, existing technologies usually rely on static data and simple evaluation models when dealing with the safety evaluation and disaster impact assessment of refuge chambers, and fail to fully consider the real-time risk avoidance status of miners and the impact of surrounding disaster data. In addition, there is a lack of a comprehensive evaluation model to dynamically select the optimal refuge chamber based on the risk avoidance status of miners and the safety and disaster avoidance impact of the refuge chamber, which may lead to inaccurate and inefficient refuge decision-making in emergency situations.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The purpose of the present invention is to provide a parametric modeling method for three-dimensional mine tunnels to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A parametric modeling method for three-dimensional mine tunnels, the specific steps comprising:

[0009] Step S1, obtaining and preprocessing the tunnel GIS data, using Revit software to implement tunnel BIM parametric modeling through the graphical programming platform Dynamo, and forming three-dimensional modeling data of the mine tunnel;

[0010] Step S2, obtaining the three-dimensional modeling data of the tunnel, and sequentially marking the several refuge chambers thereon in the same direction to form a sequence {1, 2, ..., i-1, i, i+1, ..., n}, where i represents the i-th refuge chamber, and i-1 and i+1 represent the two refuge chambers adjacent to the i-th refuge chamber, respectively, and n represents the total number of refuge chambers;

[0011] Step S3, determine the i-th refuge chamber closest to the current miner, and determine the i-1 and i+1 refuge chambers adjacent to the i-th refuge chamber according to the current position of the i-th refuge chamber, and collect disaster data around the i-th refuge chamber and the i-1 and i+1 refuge chambers adjacent to the i-th refuge chamber in sequence;

[0012] Step S4, obtaining the collected disaster data of the three refuge chambers, analyzing and processing them, and generating a safety evaluation index for each refuge chamber, the evaluation index is used to evaluate the safety level of each refuge chamber;

[0013] Step S5, determining the disaster avoidance parameters of the current miner and the three refuge chambers in step S3, the disaster avoidance parameters including slope, obstacle coefficient, terrain undulation coefficient and disaster avoidance distance, and separately collecting the current miner's risk avoidance state coefficient;

[0014] Step S6, obtaining the disaster avoidance parameters of the three refuge chambers in step S5, and performing analysis and processing to generate a disaster avoidance impact index for each refuge chamber, which is used to evaluate the degree of disaster avoidance impact of each refuge chamber;

[0015] Step S7, respectively setting the warning thresholds of the safety evaluation index and the disaster avoidance impact index to A and B. When any index exceeds the corresponding warning threshold, reselecting the next adjacent refuge chamber of the current refuge chamber until all indexes are below the corresponding warning threshold;

[0016] Step S8, obtain the safety evaluation index and disaster avoidance impact index, and introduce the current miner's risk avoidance status coefficient to construct an optimal selection model. The model is used to conduct a comprehensive evaluation based on the current miner's risk avoidance status and the safety level and disaster avoidance impact evaluation results of the three adjacent refuge chambers to select the optimal refuge chamber and form a tunnel disaster avoidance route.

[0017] Furthermore, the safety evaluation index and disaster avoidance impact index are obtained, and the current miner's risk avoidance state coefficient is introduced to construct the optimal selection model, which specifically includes the following contents:

[0018] The mathematical formula of the designed optimal selection model is as follows:

[0019]

[0020] Among them, OSM is the optimal selection model index, which is used to evaluate and select the optimal refuge chamber;

[0021] SEI k is the safety evaluation index of the kth refuge chamber, reflecting the safety level of the refuge chamber;

[0022] EII k is the disaster avoidance impact index of the kth refuge chamber, reflecting the disaster avoidance conditions of the refuge chamber;

[0023] ESC k The risk avoidance state coefficient when selecting the kth refuge chamber for miners takes into account the miners' physiology, psychology, mobility and environmental perception.

[0024] k is the index of the refuge chamber, ranging from i-1, i, i+1, representing the three refuge chambers adjacent to the current miner;

[0025] According to the calculation formula of the risk aversion coefficient ESC, the following ESC is obtained k The calculation formula is:

[0026] ESC k =w1·HR k +w2 BT k +w3·FL k +w4·SL k +w5·PL k +w6·MS k +w7·E k +w8 FOVk +w9·HS k

[0027] Among them, HR k , BT k , FL k , SL k , PL k , MS k , E k , FOV k , HS k respectively represent the physiological and psychological state data of the employees corresponding to the kth refuge chamber;

[0028] The value range of OSM is (0, 1). When OSM is close to 1, it indicates that the selected refuge chamber is the optimal choice, taking into account safety, disaster avoidance conditions, and the risk avoidance status of miners; when OSM is close to 0, it indicates that the comprehensive evaluation of the refuge chamber is relatively low and it is not the optimal choice.

[0029] Furthermore, the value range (0, 1) of the optimal selection model OSM is divided into three intervals:

[0030] Interval 1: 0 < OSM ≤ 0.33. In this interval, when OSM is lower than 0.2, an emergency alarm is triggered; when it is higher than 0.2, a non-emergency safety inspection is carried out. The changes in gas concentration and ventilation air volume significantly affect OSM. For example, a 10% increase in gas concentration causes a 5% decrease in OSM, and a 20% increase in ventilation air volume increases OSM by 10%; in addition, the improvement of geological stability and mine hydrology also has a positive impact on OSM, providing guidance for rapid response in case of emergencies;

[0031] Interval 2: 0.33 < OSM ≤ 0.66. When OSM is lower than 0.5, the system starts a safety inspection with key attention; when it is higher than 0.5, general maintenance is carried out. A 5% increase in gas concentration causes a 3% decrease in OSM, and a 10% increase in ventilation air volume increases OSM by 5%; the improvement of geological stability and mine hydrology also has a positive impact on OSM, ensuring effective risk management at a medium safety level;

[0032] Interval 3: 0.66 < OSM < 1. When OSM is lower than 0.85, the system conducts an inspection to maintain the safety state; when it is higher than 0.85, it seeks to further improve the safety state. A 5% decrease in gas concentration increases OSM by 3%, and a 10% decrease in ventilation air volume causes a 5% decrease in OSM; a slight improvement in geological stability and mine hydrology also affects OSM, guiding the maintenance and improvement of safety measures at a higher safety level.

[0033] Furthermore, when 0 < OSM ≤ 0.33 in Interval 1, the calibration fine-tuning of SEI k and EII k are respectively:

[0034] For SEI k In the low OSM range, safety assessment is affected by various adverse factors, such as equipment failure rate and gas leakage rate. Set a calibration factor to adjust SEI k Therefore, the adjusted SEI k is

[0035] For EII k In the same range, the disaster avoidance impact index decreases. Set another calibration factor to adjust EII k Therefore, the adjusted EII k is

[0036] When 0.33 < OSM ≤ 0.66 in range two, the calibration fine-tuning of SEI and EII are respectively:

[0037] For SEI k In this range, the safety assessment index needs to be fine-tuned according to the actual situation; set a calibration factor to adjust SEI k Therefore, the adjusted SEI k is

[0038] For EII k In the adjustment of EII, the disaster avoidance impact index needs to be fine-tuned according to environmental conditions. Set a calibration factor to adjust EII k ; Therefore, the adjusted EII k is

[0039] When 0.66 < OSM < 1 in range three, the calibration fine-tuning of SEI and EII are respectively:

[0040] For SEI k In this range, the safety assessment index is close to the ideal state, but still needs to be fine-tuned to ensure accuracy. Set a calibration factor to adjust SEI k ; Therefore, the adjusted SEI k is

[0041] For EII k In the adjustment of EII, the disaster avoidance impact index is also close to the ideal state in this range, but needs to be fine-tuned. Set a calibration factor to adjust EII k ; Therefore, the adjusted EII k is

[0042] Compared with the prior art, the beneficial effects of the present invention are: by integrating GIS and BIM technology, accurate modeling of mine tunnels and refuge chambers is achieved. Specifically, by introducing the real-time risk avoidance status coefficient of miners and surrounding disaster data, a dynamic optimal selection model is constructed. The model can evaluate and select the optimal refuge chamber in real time according to the miners' risk avoidance status and the safety and disaster avoidance impact of the refuge chamber. This innovation not only improves the efficiency and accuracy of mine safety management, but also provides a scientific basis for mine emergency evacuation decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the overall method flow of the present invention. DETAILED DESCRIPTION

[0044] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0045] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship also changes accordingly.

[0046] Embodiment 1:

[0047] See also Figure 1 , the present invention provides a technical solution:

[0048] A parametric modeling method for three-dimensional mine tunnels, the specific steps comprising:

[0049] Step S1, obtaining and preprocessing the tunnel GIS data, using Revit software to implement tunnel BIM parametric modeling through the graphical programming platform Dynamo, and forming three-dimensional modeling data of the mine tunnel;

[0050] Step S2, obtaining the three-dimensional modeling data of the tunnel, and sequentially marking the several refuge chambers thereon in the same direction to form a sequence {1, 2, ..., i-1, i, i+1, ..., n}, where i represents the i-th refuge chamber, and i-1 and i+1 represent the two refuge chambers adjacent to the i-th refuge chamber, respectively, and n represents the total number of refuge chambers;

[0051] Step S3, determine the i-th refuge chamber closest to the current miner, and determine the i-1 and i+1 refuge chambers adjacent to the i-th refuge chamber according to the current position of the i-th refuge chamber, and collect disaster data around the i-th refuge chamber and the i-1 and i+1 refuge chambers adjacent to the i-th refuge chamber in sequence;

[0052] Step S4, obtaining the collected disaster data of the three refuge chambers, analyzing and processing them, and generating a safety evaluation index for each refuge chamber, the evaluation index is used to evaluate the safety level of each refuge chamber;

[0053] Step S5, determining the disaster avoidance parameters of the current miner and the three refuge chambers in step S3, the disaster avoidance parameters including slope, obstacle coefficient, terrain undulation coefficient and disaster avoidance distance, and separately collecting the current miner's risk avoidance state coefficient;

[0054] Step S6, obtaining the disaster avoidance parameters of the three refuge chambers in step S5, and performing analysis and processing to generate a disaster avoidance impact index for each refuge chamber, which is used to evaluate the degree of disaster avoidance impact of each refuge chamber;

[0055] Step S7, respectively setting the warning thresholds of the safety evaluation index and the disaster avoidance impact index to A and B. When any index exceeds the corresponding warning threshold, reselecting the next adjacent refuge chamber of the current refuge chamber until all indexes are below the corresponding warning threshold;

[0056] Step S8, obtain the safety evaluation index and disaster avoidance impact index, and introduce the current miner's risk avoidance status coefficient to construct an optimal selection model. The model is used to conduct a comprehensive evaluation based on the current miner's risk avoidance status and the safety level and disaster avoidance impact evaluation results of the three adjacent refuge chambers to select the optimal refuge chamber and form a tunnel disaster avoidance route.

[0057] Embodiment 2:

[0058] Further explanation is given on the basis of Example 1, the tunnel GIS data is obtained and preprocessed, and the preprocessed data is used in Revit software, and the tunnel BIM parametric modeling is realized through the graphical programming platform Dynamo to form the three-dimensional modeling data of the mine tunnel, which specifically includes the following contents:

[0059] Step S1.1, obtaining the original GIS data of the mine, and forming a GIS data set after preliminary screening and sorting;

[0060] Input: original GIS data in the mine database;

[0061] Processing: ArcGIS software is used to extract GIS data related to the tunnel from the database, including the tunnel's geometry, location coordinates, and geological conditions;

[0062] Output: GIS dataset after preliminary screening and organization;

[0063] Innovation: ArcGIS is used for data extraction, and its advanced data screening and sorting functions are used to ensure the accuracy and completeness of the data;

[0064] Step S1.2, obtaining the GIS data set and performing data preprocessing to form a preprocessed Revit compatible format;

[0065] Input: GIS dataset output from step S1.1;

[0066] Processing: Perform data cleaning to remove duplicate, erroneous or inconsistent data records; perform format conversion to convert data into a format recognizable by Revit (such as DXF or DWG); unify the coordinate system to ensure that all data is in the same coordinate system;

[0067] Output: pre-processed GIS data in a Revit-compatible format with a unified coordinate system;

[0068] Innovation: Ensure the compatibility and accuracy of data when imported into Revit through precise data cleaning and format conversion;

[0069] Step S1.3, importing the preprocessed GIS data into Revit software to import the Revit data set;

[0070] Input: pre-processed GIS data output from step S1.2;

[0071] Processing: Import the pre-processed GIS data into Revit software, and use Revit's import function to ensure accurate data conversion;

[0072] Output: Dataset successfully imported into Revit, ready for parametric modeling;

[0073] Innovation: Utilize Revit's powerful data import function to ensure seamless data conversion into the BIM environment;

[0074] Step S1.4, obtaining the Revit data set, and using Dynamo for parametric modeling, and finally generating three-dimensional parametric modeling data of the mine tunnel;

[0075] Input: Step S1.3 imports the Revit dataset;

[0076] Processing: In the Revit environment, scripts are written through the Dynamo graphical programming platform to define the geometric shape and parameterization rules of the laneway, which are applied to the data set to generate 3D modeling data;

[0077] Output: 3D parametric modeling data of mine tunnels;

[0078] Innovation: Dynamo's parametric modeling capabilities enable fast construction of complex models through visual programming, improving modeling efficiency and accuracy;

[0079] The method of obtaining the three-dimensional modeling data of the tunnel and sequentially marking the several refuge chambers thereon in the same direction specifically includes the following contents:

[0080] Step S2.1, obtaining three-dimensional modeling data of the tunnel;

[0081] Input: 3D parametric modeling data of mine tunnel outputted in step S1.4;

[0082] Processing: Extract 3D modeling data of all lanes from the Revit model, including the lane geometry and location coordinate details.

[0083] Output: Complete 3D modeling dataset of the tunnel;

[0084] Reason for selection: Extracting data directly from the Revit model can ensure the accuracy and integrity of the data and avoid information loss during the data conversion process.

[0085] Step S2.2, identifying and marking the locations of all refuge chambers, marking them as {1, 2, ..., i-1, i, i+1, ..., n}, where i represents the i-th refuge chamber and n represents the total number of refuge chambers;

[0086] Input: the 3D modeling dataset of the laneway outputted in step S2.1;

[0087] Processing: Identify the locations of all refuge chambers in the 3D modeling data, and use software tools (such as the marking function of Revit) to sequentially mark each refuge chamber as {1, 2, ..., i-1, i, i+1, ..., n}, where i represents the i-th refuge chamber and n represents the total number of refuge chambers;

[0088] Output: marked refuge chamber sequence;

[0089] Reason for selection: Using Revit's tagging function can quickly and accurately number the refuge chambers, which is convenient for subsequent data processing and analysis;

[0090] Step S2.3, verifying the accuracy of the marking;

[0091] Input: the marked refuge chamber sequence output from step S2.2;

[0092] Solution: Use software tools (such as Revit's check function) to verify that each refuge chamber is correctly labeled and numbered consecutively.

[0093] Output: verified refuge chamber label sequence;

[0094] Reason for selection: The verification step ensures the accuracy of the labeling and provides a reliable basis for subsequent analysis and application.

[0095] Embodiment three:

[0096] Further explanation based on the second embodiment, the method of determining the i-th refuge chamber closest to the current miner, and determining the i-1 and i+1 refuge chambers adjacent to the current i-th refuge chamber, and collecting disaster data around the above three refuge chambers in sequence, specifically includes the following contents:

[0097] Step S3.1, using the miner positioning system to determine the precise position of the current miner in the tunnel, and obtain the precise position coordinates of the miner;

[0098] Input: The marked refuge chamber sequence output from step S2,

[0099] Processing: Use a miner positioning system (such as a radio frequency based positioning system) to determine the current miner's precise position in the tunnel;

[0100] Output: The miner’s precise location coordinates;

[0101] Reason for selection: The use of radio frequency positioning system can provide high-precision positioning information, which is suitable for the complex environment of mines and ensures the accuracy of miners' location;

[0102] Step S3.2, calculating the nearest refuge chamber, by calculating the Euclidean distance between the miner's position and each refuge chamber, determining the i-th refuge chamber closest to the miner;

[0103] Input: the miner position coordinates output from step S3.1 and the refuge chamber sequence output from step S2;

[0104] Processing: Determine the i-th refuge chamber closest to the miner by calculating the Euclidean distance between the miner's position and each refuge chamber;

[0105] Output: the nearest refuge chamber number i;

[0106] Reason for selection: Euclidean distance calculation is simple and intuitive, suitable for quickly determining the nearest refuge chamber and improving emergency response efficiency;

[0107] Step S3.3, collecting disaster data around the refuge chambers, using disaster monitoring equipment to collect disaster data around the i-th refuge chamber and its two adjacent refuge chambers i-1 and i+1;

[0108] Input: the nearest refuge chamber number i output in step S3.2;

[0109] Processing: Use disaster monitoring equipment (such as gas sensors and temperature sensors) to collect disaster data around the i-th refuge chamber and its adjacent i-1 and i+1 refuge chambers. The disaster data includes gas concentration, temperature, humidity, ventilation volume, geological stability data, and mine hydrological data. The gas concentration is marked as QTn, the temperature is marked as Wd, the humidity is marked as Sd, the ventilation volume is marked as TFl, the geological stability data is marked as DZWd, and the mine hydrological data is marked as KJSw;

[0110] Gas concentration data: including real-time concentrations of methane, carbon monoxide, and carbon dioxide gases; these data are collected in real time through gas sensors and are key parameters for assessing mine safety;

[0111] Temperature and humidity data: The temperature and humidity in the mine have a direct impact on the miners’ working environment and health. This data is collected through temperature and humidity sensors to assess the comfort level and potential fire risks in the mine.

[0112] Ventilation volume data: Ventilation volume is a key factor in ensuring air quality and temperature and humidity control in mines. The ventilation volume is measured by wind speed sensors to evaluate the effectiveness of the ventilation system.

[0113] Geological stability data: including rock stress, crack distribution, and groundwater level data. These data are collected through geological monitoring equipment and used to assess the geological stability around the refuge chamber;

[0114] Mine hydrological data: including water level, water quality, and water flow rate. These data are collected through hydrological monitoring equipment and used to assess flood risks;

[0115] Integrate the various parameters of the same type of data into one formula for comprehensive evaluation. The following is the integrated mathematical expression:

[0116] For the gas concentration data QTn, the calculation formula is as follows:

[0117]

[0118] Among them, QTn is the index of comprehensive gas concentration, 、w CO , They are the weight coefficients of methane, carbon monoxide and carbon dioxide concentrations, which are used to reflect the impact of different gases on mine safety. These weight coefficients need to be determined based on actual conditions and safety standards;

[0119] For the geological stability data DZWd, the calculation formula is as follows:

[0120] DZWd=w Z1 ·D Z1 +w Z2 ·D Z2 +w Z3 ·D Z3

[0121] Among them, DZWd is the index of comprehensive geological stability, w Z1 、w Z2 、w Z3 They are the weight coefficients of rock stress, fracture distribution and groundwater level, which are used to reflect the impact of these factors on geological stability;

[0122] For the mine hydrological data KJSw, the calculation formula is as follows:

[0123] KJSw=w S1 ·K S1 +w S2 ·K S2 +w S3 ·K S3

[0124] Among them, KJSw is the index of comprehensive hydrological data, w S1 、w S2 、w S3 They are the weight coefficients of water level, water quality and water velocity, which are used to reflect the impact of these factors on the hydrological risk of the mine;

[0125] In the above formula, the weight coefficient w is set according to the degree of influence of each parameter on the overall safety risk. These weight coefficients need to be determined through expert evaluation, historical data analysis or mathematical optimization methods to ensure that the comprehensive index can accurately reflect the safety status of the mine;

[0126] Output: Disaster dataset around three refuge chambers;

[0127] Reason for selection: Use a variety of sensors to comprehensively monitor disaster-related parameters, ensure the comprehensiveness and accuracy of data, and provide reliable data support for disaster assessment.

[0128] Embodiment 4:

[0129] Further explanation is given on the basis of the third embodiment, the three refuge chamber disaster data are acquired and analyzed to generate a safety evaluation index for each refuge chamber. The evaluation index is used to evaluate the safety level of each refuge chamber, and specifically includes the following contents:

[0130] Define the safety evaluation index of refuge chamber as SEI k , SEI i 、SEI i-1 、SEI i+1 They represent the calculation formulas for the safety evaluation index of three refuge chambers. The specific formulas are as follows:

[0131]

[0132] Among them, SEI i 、SEI i-1 、SEI i+1 is the safety evaluation index of the three refuge chambers, and its value range is (0,1). The closer the value is to 1, the higher the safety level is. k Represents SEI i 、SEI i-1 、SEI i+1 A set of , where k takes the values ​​i, i-1, i+1 respectively;

[0133] w ij 、w (i-1)j 、w (i+1)j are the weight coefficients of the jth parameter in the i-th, i-1-th, and i+1-th refuge chambers, j=1, 2, ..., 6, corresponding to gas concentration QTn, temperature Wd, humidity Sd, ventilation air volume TFl, geological stability DZWd, and mine hydrology KJSw, respectively;

[0134] X ij X (i-1)j X (i+1)j are the actual measured values ​​of the jth parameter in the i-th, i-1-th, and i+1-th refuge chambers, i.e., QTn, Wd, Sd, TFl, DZWd, and KJSw;

[0135] Norm(X ij )、Norm(X (i-1)j )、Norm(X (i+1)j ) are respectively ij X (i-1)j X (i+1)jA function for normalization to ensure that all parameters are compared on the same scale;

[0136] θ i ,θ i-1 ,θ i+1 are the threshold parameters of the i-th, i-1-th, and i+1-th refuge chambers, respectively, which are used to adjust the sensitivity of the model;

[0137] For the normalization function Norm(X j ) is:

[0138]

[0139] Where min(X j ) and max(X j ) are the parameters X j The minimum and maximum values ​​of Norm(X (i-1)j )、Norm(X (i+1)j ), the normalization function form is consistent and will not be repeated;

[0140] Setting the safety evaluation index SEI k The value range is (0,1). When SEI k When it is close to 1, it means that the safety level of the refuge chamber is high; when SEI k When it is close to 0, it means the security level is low; by adjusting the weight coefficient w ij 、w (i-1)j 、w (i+1)j and threshold θ i ,θ i-1 ,θ i+1 , can optimize the performance of the model to make it more in line with the needs of actual safety evaluation;

[0141] Safety Evaluation Index (SEI) k The value range (0,1) is divided into three intervals, and each interval is described in detail with quantitative content, specific judgment criteria and rules are set, and interaction rules are explained:

[0142] Interval 1, 0 <SEI k ≤0.33; this range indicates that the safety level of the refuge chamber is low and emergency treatment is required. SEI k When it is lower than 0.2, an emergency alarm is triggered. When it is between 0.2 and 0.33, non-emergency maintenance is initiated. Parameter changes significantly affect SEI k , improving current ventilation by 10% can improve safety;

[0143] Interval 2, 0.33 <SEI k ≤0.66; medium safety level, SEI k SEI is between 0.33 and 0.66.k When it is lower than 0.5, special attention should be paid. When it is higher, routine maintenance should be performed. Small changes in parameters affect SEI. k , safety can be maintained by optimizing ventilation and equipment;

[0144] Interval 3, 0.66 <SEI k <1; high safety level, SEI k Between 0.66 and 1, SEI k If it is lower than 0.8, keep the status quo; if it is higher, improve safety management; small changes within 7% of the parameter will affect SEI k ;

[0145] Here is a description of each interval:

[0146] Interval 1, 0 <SEI k ≤0.33; within this range, the safety evaluation index SEI of the refuge chamber k Indicates a low level of safety. Specifically, SEI k A value less than or equal to 0.33 means that the safety condition of the refuge chamber is poor; if SEI k If it is 0.25, it means that the safety of the refuge chamber is only 25% of the ideal state; at this time, there is a serious gas leakage (such as QTn exceeds 150% of the safety standard), abnormal temperature rise (such as Wd is 30% higher than the normal value), excessive humidity (such as Sd is 20% higher than the normal value), insufficient ventilation (such as TFl is 40% lower than the normal value), geological instability (such as DZWd is 50% lower than the normal value) or mine hydrological problems (such as KJSw exceeds 100% of the normal value); these factors together lead to the safety evaluation index SEI k At a low level, immediate action is needed to improve;

[0147] Judgment criteria and rule settings:

[0148] In this interval, a threshold SEI is set k = 0.2, used to distinguish between urgent and non-urgent safety issues; when SEI k When the SEI is lower than 0.2, the system will automatically trigger an emergency alarm and initiate emergency plans, such as immediately evacuating personnel and shutting down related equipment. k When the value is between 0.2 and 0.33, the system will initiate non-emergency safety inspection and maintenance procedures, such as regularly checking gas concentrations and adjusting ventilation systems. This threshold is set based on an analysis of historical data and accident cases to ensure timely response when safety issues are serious.

[0149] Interaction rule settings:

[0150] In this range, each parameter change will have an impact on SEI.k When the gas concentration QTn increases by 10%, SEI k will decrease by 5%; when the ventilation volume TFl increases by 20%, SEI k This interaction rule shows that improving the ventilation system can significantly improve the safety of the refuge chamber; at the same time, the improvement of geological stability DZWd and mine hydrology KJSw will also have an impact on SEI k Positive effects are generated, such as a 15% increase in DZWd leads to an 8% increase in SEI, and a 20% decrease in KJSw leads to a 12% increase in SEI; these interaction rules provide specific operational guidelines for the safety management of refuge chambers;

[0151] Interval 2, 0.33 <SEI k ≤0.66; within this range, the safety evaluation index SEI of the refuge chamber k Indicates that the safety level is at a medium level. Specifically, SEI k A value between 0.33 and 0.66 means that the safety of the refuge chamber is average; if SEI k If the value is 0.5, it indicates that the safety of the refuge chamber is in an ideal state of 50%; at this time, there are some safety issues, such as the gas concentration QTn is slightly higher than the normal value of 5%, the temperature Wd is slightly lower than the normal value of 10%, the humidity Sd is slightly higher than the normal value of 15%, the ventilation volume TFl is slightly lower than the normal value of 20%, the geological stability DZWd is slightly lower than the normal value of 30%, or the mine hydrology KJSw is slightly higher than the normal value of 25%; these factors lead to the safety evaluation index SEI k At a medium level, regular safety inspections and maintenance are required;

[0152] Judgment criteria and rule setting: Within this range, set a threshold SEI k =0.5, used to distinguish between safety issues that require special attention and general safety issues; when SEI k When the SEI is lower than 0.5, the system will initiate key safety inspection and maintenance procedures, such as strengthening gas concentration monitoring and optimizing the ventilation system. k When the threshold is between 0.5 and 0.66, the system will initiate general safety inspection and maintenance procedures, such as regular inspections of equipment operation and routine maintenance. This threshold is set based on the analysis of safety data to ensure timely response when safety issues require special attention.

[0153] Interaction rule setting: Within this range, each parameter change will affect SEI k When the gas concentration QTn increases by 5%, SEI kWhen the ventilation volume TFl increases by 10%, SEI increases by 5%. This interaction rule shows that improving the ventilation system can improve the safety of the refuge chamber. At the same time, the improvement of geological stability DZWd and mine hydrology KJSw will also have an impact on SEI. k Positive effects, such as DZWd increased by 10% SEI k A 4% increase and a 15% decrease in KJSw made SEI k These interactive rules provide specific operational guidelines for the safe management of refuge chambers;

[0154] Interval 3, 0.66 <SEI k <1; within this range, the safety evaluation index SEI of the refuge chamber k Indicates a high level of safety. Specifically, SEI k A value between 0.66 and 1 means that the safety of the refuge chamber is good; if SEI k If the value is 0.8, it indicates that the safety of the refuge chamber is in an ideal state of 80%; at this time, there are some minor safety problems, such as the gas concentration QTn is slightly lower than the normal value of 5%, the temperature Wd is slightly higher than the normal value of 10%, the humidity Sd is slightly lower than the normal value of 15%, the ventilation air volume TFl is slightly higher than the normal value of 20%, the geological stability DZWd is slightly higher than the normal value of 30%, or the mine hydrology KJSw is slightly lower than the normal value of 25%; these factors lead to the safety evaluation index SEI k At a high level, but still requires regular safety inspections and maintenance;

[0155] Judgment criteria and rule settings:

[0156] In this interval, a threshold SEI is set k = 0.8, which is used to distinguish between the safety status that needs to be maintained and the safety status that needs to be further improved. k When it is lower than 0.8, the system will start the inspection and maintenance procedures to maintain a safe state, such as regularly checking the gas concentration and adjusting the ventilation system. k When the threshold is between 0.8 and 1, the system will initiate inspection and maintenance procedures to further improve the safety status, such as optimizing equipment operating efficiency and improving safety management level. This threshold is set based on the analysis of safety data to ensure timely response when the safety status needs to be further improved.

[0157] Interaction rule setting: Within this range, each parameter change will affect SEI k When the gas concentration QTn decreases by 5%, SEI kWhen the ventilation volume TFl decreases by 10%, SEI decreases by 5%. This interaction rule shows that maintaining the efficient operation of the ventilation system can maintain the safety of the refuge chamber. At the same time, the improvement of geological stability DZWd and mine hydrology KJSw will also have an impact on SEI. k Positive effects, such as DZWd increased by 5% SEI k A 2% increase and a 10% decrease in KJSw make SEI k Increased by 3%; These interaction rules provide specific operational guidelines for the safe management of refuge chambers.

[0158] Embodiment five:

[0159] Further explanation based on the fourth embodiment, the slope is marked as Pd, the obstacle coefficient is marked as OFs, the terrain relief coefficient is marked as TRF, and the disaster avoidance distance is marked as EDd;

[0160] The slope is determined by calculating the ratio of the height difference between two points to the horizontal distance. Assuming there are two points P1 (x1, y1, z1) and P2 (x2, y2, z2) in GIS data, where the z coordinate represents the height, the slope calculation formula is as follows:

[0161]

[0162] Where Δz = z2-z1 is the height difference between the two points;

[0163] Δx = x2-x1 is the component of the horizontal distance between the two points on the x-axis;

[0164] Δy=y2-y1 is the component of the horizontal distance between the two points on the y-axis;

[0165] The obstacle coefficient is determined by calculating the density of obstacles around the refuge chamber. Assuming that N1 is the number of obstacles within a certain radius around the refuge chamber, and AS is the total area within the radius, the calculation formula of the obstacle coefficient is as follows:

[0166]

[0167] Where AS = πr 2 is the total area within a certain radius around the refuge chamber, r is the radius;

[0168] The terrain relief coefficient is determined by calculating the height change of the terrain around the refuge chamber, assuming that Δz max It is the maximum height difference within a certain radius around the refuge chamber. The calculation formula of the terrain relief coefficient is as follows:

[0169]

[0170] Where r is the radius;

[0171] Disaster evacuation distance refers to the shortest path length from the current location to the refuge chamber. Assume that P c (x c ,y c ,z c ) is the current position, P i (x i ,y i ,z i ) is the location of the i-th refuge chamber, and the calculation formula of the disaster avoidance distance is as follows:

[0172]

[0173] All parameters in the above formulas are based on GIS data and actual measurements;

[0174] The current miner's risk avoidance state coefficient specifically includes physiological state data, psychological state data, mobility data, and environmental perception data, and the physiological state data includes heart rate, body temperature, and fatigue level, which are marked as HR, BT, and FL in sequence;

[0175] The psychological state data includes stress level and panic level, which are marked as SL and PL respectively;

[0176] The movement ability data includes movement speed and endurance, which are marked as MS and E respectively;

[0177] The environmental perception capability data includes the field of view range value and the hearing sensitivity, which are marked as FOV and HS respectively;

[0178] 1. Physiological status data:

[0179] Heart rate (HR), measured by wearable devices;

[0180] Body temperature (BT), measured by a thermometer;

[0181] Fatigue Level (FL), assessed by physiological monitoring equipment or self-report;

[0182] 2. Psychological state data:

[0183] Stress Level (SL), measured by psychological assessment questionnaire or biofeedback equipment;

[0184] Panic Level (PL), assessed by psychological assessment questionnaire or behavioral observation;

[0185] 3. Mobile capability data:

[0186] Movement speed (MS), measured by motion tracking devices;

[0187] Endurance (E), assessed by exercise testing or self-report;

[0188] 4. Environmental perception data:

[0189] Field of View (FOV), measured by head-mounted camera equipment;

[0190] Hearing Sensitivity (HS), assessed through audiometry;

[0191] Based on the above data, the calculation formula of the risk aversion coefficient ESC is constructed:

[0192] ESC=w1·HR+w2·BT+w3·FL+w4·SL+w5·PL+w6·MS+w7·E+w8·FOV+w9·HS

[0193] Among them, w i′ is the weight of each factor, i′∈1,2,...9, which needs to be determined based on actual conditions and expert evaluation;

[0194] Define the disaster impact index of the i-th refuge chamber as EII i , the calculation formula is as follows:

[0195]

[0196] Among them, EII i is the disaster impact index of the i-th refuge chamber;

[0197] w j′ is the weight, j′=1,2,3,4; corresponding to the weights of slope, obstacle coefficient, terrain undulation coefficient and disaster avoidance distance respectively; it needs to be determined according to the actual situation and expert evaluation; f j′ is a function, corresponding to the processing function of the four parameters; n is the total number of refuge chambers;

[0198] Function f j′ The definition of is as follows;

[0199] f1(Pd i )=exp(-Pd i ) is an exponential decay function of the slope. The greater the slope, the smaller the impact.

[0200] It is the normalized function of the obstacle coefficient. The more obstacles there are, the smaller the impact.

[0201] It is a normalized function of the terrain relief coefficient. The greater the terrain relief, the smaller the impact.

[0202] It is the inverse function of the disaster avoidance distance. The farther the distance, the smaller the impact.

[0203] Setting the Disaster Impact Index (EII) i The value range of EII is (0,1). i When EII is close to 1, it means that the disaster shelter condition of the i-th refuge chamber is better; i When it is close to 0, it means that the disaster avoidance conditions are poor; this range ensures the rationality and practicality of the disaster avoidance impact index and avoids the special case when the parameter is 0;

[0204] Disaster Impact Index (EII) i The value range is divided into the following three intervals:

[0205] EII i Located at 0<EII i In the range of ≤0.3, the disaster avoidance conditions of the refuge chambers are significantly insufficient and there is a high risk; the refuge chambers in this range face slopes exceeding 30%, obstacle coefficients exceeding 0.5, terrain undulation coefficients exceeding 0.2, and disaster avoidance distances exceeding 500 meters. These factors increase the difficulty of miners' avoidance in emergencies by 30% to 50%; therefore, immediate measures need to be taken and other optimized paths or refuge chambers need to be reselected. Other refuge chambers need to reduce the obstacle coefficient by at least 10%, reduce the slope by at least 15%, and shorten the disaster avoidance distance by at least 20% to improve disaster avoidance efficiency and safety;

[0206] Disaster Impact Index (EII) i Falling within 0.3<EII i When the value is within the range of ≤0.7, the disaster avoidance conditions of the refuge chamber are at a medium level. Although the refuge chambers in this range are not the best choice, they can still be used as an effective option for disaster avoidance. In order to further improve the disaster avoidance efficiency, it is necessary to consider optimizing the path, reducing the obstacle coefficient by at least 5%, and improving the terrain. Specifically, the terrain undulation coefficient should be reduced by at least 10%. Through these measures, the accessibility and safety of the refuge chamber can be improved, and the risk of miners in emergency situations can be reduced by 20% to 30%.

[0207] EII i Reach 0.7<EII iWhen the value is less than 1, the disaster avoidance conditions of the refuge chamber are good, which significantly reduces the risk of miners. The refuge chambers in this range have a slope of less than 15%, an obstacle coefficient of less than 0.2, a terrain undulation coefficient of less than 0.1, and a disaster avoidance distance of less than 200 meters. These factors ensure that the refuge chamber can be reached quickly and safely in an emergency, and the risk of disaster avoidance is reduced by at least 50%. Although the conditions are relatively good, regular maintenance and inspection are still required to maintain and optimize these favorable conditions and further reduce potential risks by 10% to 20%.

[0208] Interval 1, 0<EII i ≤0.3; in this range, the disaster avoidance impact index of the refuge chamber is low, indicating that the disaster avoidance conditions of the refuge chamber are poor; specifically, when the disaster avoidance impact index is between 0 and 0.3, the slope of the refuge chamber exceeds 30%, the obstacle coefficient is higher than 0.5, the terrain undulation coefficient exceeds 0.2, and the disaster avoidance distance is greater than 500 meters; these conditions make it difficult to quickly reach the refuge chamber in an emergency, increasing the risk of miners' avoidance; a slope of more than 30% means that the terrain is steep and difficult to move; an obstacle coefficient higher than 0.5 means that there are dense obstacles around the refuge chamber, affecting passage; a terrain undulation coefficient of more than 0.2 indicates that the terrain changes greatly and is not easy to move quickly; a disaster avoidance distance greater than 500 meters directly increases the time to reach the refuge chamber;

[0209] Judgment criteria and rule settings:

[0210] To further refine the evaluation, a threshold EII is set i =0.2; when EII i When the EII is lower than 0.2, the disaster shelter conditions in the refuge chamber are judged to be "extremely poor" and immediate environmental improvement is required. i When the EII is between 0.2 and 0.3, the disaster shelter conditions in the refuge chamber are judged to be “poor” and environmental improvements are required. i When it is lower than 0.2, priority should be given to reducing the number of obstacles, lowering the slope, or increasing the number of refuge chambers to shorten the evacuation distance;

[0211] Interaction rule description settings:

[0212] In this range, the interactive effects of various parameters are significant; when the slope increases by 10%, the disaster avoidance impact index decreases by 5%; when the obstacle coefficient increases by 0.1, the disaster avoidance impact index decreases by 3%; when the terrain undulation coefficient increases by 0.05, the disaster avoidance impact index decreases by 4%; when the disaster avoidance distance increases by 100 meters, the disaster avoidance impact index decreases by 8%; these changes show that the increase of any parameter will significantly reduce the disaster avoidance impact index, thereby increasing the difficulty of risk avoidance for miners;

[0213] Interval 2, 0.3<EII i≤0.7; in this range, the disaster avoidance impact index of the refuge chamber is at a medium level, indicating that the disaster avoidance conditions of the refuge chamber are general; specifically, when the disaster avoidance impact index is between 0.3 and 0.7, the slope of the refuge chamber is between 15% and 30%, the obstacle coefficient is between 0.2 and 0.5, the terrain undulation coefficient is between 0.1 and 0.2, and the disaster avoidance distance is between 200 meters and 500 meters; these conditions indicate that the refuge chamber is not the best choice in an emergency, but it can still be used as a risk avoidance option;

[0214] Judgment criteria and rule settings:

[0215] Set a threshold EII i =0.5; when EII i When the EII is lower than 0.5, the disaster shelter conditions in the refuge chamber are judged as “average” and environmental improvements are needed to improve the disaster shelter efficiency. i When the EII is between 0.5 and 0.7, the disaster shelter conditions in the refuge chamber are judged to be “good”, but there is still room for improvement; i When it is lower than 0.5, we should consider optimizing the route, reducing obstacles, or improving the terrain to improve the efficiency of disaster avoidance;

[0216] Interaction rule description settings:

[0217] In this range, the interactive effects of various parameters are relatively balanced; when the slope decreases by 5%, the disaster avoidance impact index increases by 3%; when the obstacle coefficient decreases by 0.05, the disaster avoidance impact index increases by 2%; when the terrain undulation coefficient decreases by 0.02, the disaster avoidance impact index increases by 2%; when the disaster avoidance distance decreases by 50 meters, the disaster avoidance impact index increases by 5%. These changes show that the disaster avoidance impact index can be effectively improved by optimizing various parameters, thereby improving the risk avoidance conditions;

[0218] Interval 3, 0.7<EII i <1; in this range, the disaster avoidance impact index of the refuge chamber is relatively high, indicating that the disaster avoidance conditions of the refuge chamber are good; specifically, when the disaster avoidance impact index is between 0.7 and 1, the slope of the refuge chamber is less than 15%, the obstacle coefficient is less than 0.2, the terrain undulation coefficient is less than 0.1, and the disaster avoidance distance is less than 200 meters; these conditions make the refuge chamber easy to reach quickly in an emergency, significantly reducing the risk of miners' avoidance;

[0219] Judgment criteria and rule settings:

[0220] Set a threshold EII i =0.85; when EII i When the EII is higher than 0.85, the disaster shelter conditions in the refuge chamber are judged to be "excellent" and no immediate environmental improvement is required. iWhen the EII is between 0.7 and 0.85, the disaster shelter condition of the refuge chamber is judged as "good", but regular inspection is still required to maintain the disaster shelter efficiency; when the EII is between 0.7 and 0.85, the disaster shelter condition of the refuge chamber is judged as "good", but regular inspection is still required to maintain the disaster shelter efficiency. i When it is higher than 0.85, the current environmental conditions should be maintained and maintenance and inspections should be performed regularly;

[0221] Interaction rule description settings:

[0222] In this range, the interactive influence of each parameter is small; when the slope decreases by 2%, the disaster avoidance impact index increases by 1%; when the obstacle coefficient decreases by 0.02, the disaster avoidance impact index increases by 1%; when the terrain undulation coefficient decreases by 0.01, the disaster avoidance impact index increases by 1%; when the disaster avoidance distance decreases by 20 meters, the disaster avoidance impact index increases by 2%; these changes indicate that although the disaster avoidance conditions are already good, the disaster avoidance impact index can be further improved by fine-tuning each parameter, thereby optimizing the risk avoidance conditions.

[0223] Embodiment six:

[0224] Further explanation based on Example 5, the warning thresholds of the safety evaluation index and the disaster avoidance impact index are set as A and B respectively. When any index exceeds the corresponding warning threshold, the next adjacent refuge chamber of the current refuge chamber is reselected until all indexes are below the corresponding warning threshold. Specifically, the following contents are included:

[0225] Step S7.1, respectively setting warning thresholds A and B of the safety evaluation index and the disaster avoidance impact index;

[0226] First, based on historical data and risk assessment, the safety evaluation index SEI is set k The warning threshold is A, and the disaster avoidance impact index EII i The warning threshold is B; in this embodiment, A is set to 0.8 and B is set to 0.6; these thresholds ensure the minimum acceptable level of safety and disaster avoidance efficiency of the refuge chamber;

[0227] Step S7.2, real-time monitoring and evaluation;

[0228] Use the safety evaluation index and disaster avoidance impact index calculation formula for real-time monitoring and evaluation. The calculation formula is described in the previous content and will not be repeated here:

[0229] Step S7.3, compare the index with the threshold; monitor the SEI obtained in real time k and EII i Compare with preset warning thresholds A and B; if SEI k >A and EII i >B, the current refuge chamber is considered safe and does not need to be replaced; if SEI k ≤A or EII i ≤B, then proceed to the next step;

[0230] Step S7.4, select an adjacent refuge chamber; when SEI k or EII i When any index in is lower than its corresponding warning threshold, the system automatically selects the next adjacent refuge chamber of the current refuge chamber; the selection is based on the SEI and EII values ​​of the adjacent refuge chamber, and the adjacent chamber with SEI and EII higher than the current refuge chamber is preferred;

[0231] Step S7.5, repeat the evaluation until the conditions are met; after selecting a new refuge chamber, repeat steps S7.2 to S7.4 until the SEI and EII of all evaluated refuge chambers are higher than their corresponding warning thresholds; this process ensures that there are always safe and disaster-evacuation-efficient refuge chambers available during mine operation.

[0232] Embodiment seven:

[0233] Further explanation based on Example 6, the acquisition of the safety evaluation index and the disaster avoidance impact index, and the introduction of the current miner's risk avoidance state coefficient to construct the optimal selection model specifically includes the following contents:

[0234] The mathematical formula of the designed optimal selection model is as follows:

[0235]

[0236] Among them, OSM is the optimal selection model index, which is used to evaluate and select the optimal refuge chamber;

[0237] SEI k is the safety evaluation index of the kth refuge chamber, reflecting the safety level of the refuge chamber;

[0238] EII k is the disaster impact index of the kth refuge chamber, reflecting the disaster conditions of the refuge chamber;

[0239] ESC k The risk avoidance state coefficient when selecting the kth refuge chamber for miners takes into account the miners' physiology, psychology, mobility and environmental perception.

[0240] k is the index of the refuge chamber, ranging from i-1, i, i+1, representing the three refuge chambers adjacent to the current miner;

[0241] According to the calculation formula of the risk aversion coefficient ESC, the following ESC is obtained k The calculation formula is:

[0242] ESC k =w1·HR k +w2 BTk +w3·FL k +w4·SL k +w5·PL k +w6·MS k +w7·E k +w8·FOV k +w9·HS k

[0243] Among them, HR k , BT k , FL k , SL k , PL k , MS k , E k , FOV k , HS k respectively represent the physiological and psychological state data of the employees corresponding to the k-th refuge chamber;

[0244] The value range of OSM is (0, 1). When OSM is close to 1, it indicates that the selected refuge chamber is the optimal choice, comprehensively considering safety, disaster avoidance conditions, and the risk avoidance status of miners; when OSM is close to 0, it indicates that the comprehensive evaluation of the refuge chamber is relatively low and it is not the optimal choice;

[0245] The value range (0, 1) of the optimal selection model OSM is divided into three intervals:

[0246] Interval 1: 0 < OSM ≤ 0.33. In this interval, when OSM is lower than 0.2, an emergency alarm is triggered, and when it is higher than 0.2, a non-emergency safety inspection is carried out. The changes in gas concentration and ventilation air volume significantly affect OSM. For example, when the gas concentration increases by 10%, OSM decreases by 5%, and when the ventilation air volume increases by 20%, OSM increases by 10%; in addition, the improvement of geological stability and mine hydrology also has a positive impact on OSM, providing guidance for rapid response in emergency situations;

[0247] Interval 2: 0.33 < OSM ≤ 0.66. When OSM is lower than 0.5, the system starts a safety inspection with key attention, and when it is higher than 0.5, general maintenance is carried out. When the gas concentration increases by 5%, OSM decreases by 3%, and when the ventilation air volume increases by 10%, OSM increases by 5%; the improvement of geological stability and mine hydrology also has a positive impact on OSM, ensuring effective risk management at a medium safety level;

[0248] Interval three: 0.66 < OSM < 1. When OSM is below 0.85, the system conducts a check to maintain the safe state. When it is above 0.85, it seeks to further improve the safe state. A 5% reduction in gas concentration increases OSM by 3%, and a 10% reduction in ventilation air volume decreases OSM by 5%. Slight improvements in geological stability and mine hydrology also affect OSM, guiding the maintenance and improvement of safety measures at a higher safety level.

[0249] Interval one: 0 < OSM ≤ 0.33. In this interval, the OSM value indicates a relatively low comprehensive evaluation of the refuge chamber, not the optimal choice. Specifically, when OSM is between 0 and 0.33, the safety evaluation index SEI of the refuge chamber is below 0.5, the disaster avoidance impact index EII is below 0.4, and the emergency shelter state coefficient ESC is below 0.6. If OSM is 0.25, it indicates that the comprehensive evaluation of the safety, disaster avoidance conditions, and miner status of the refuge chamber is only 25% of the ideal state. At this time, there are serious safety problems, such as gas leakage exceeding 150% of the safety standard, abnormal temperature rise exceeding 30% of the normal value, and excessive humidity exceeding 20% of the normal value. These factors together result in a low level of OSM, and immediate measures need to be taken for improvement.

[0250] Judgment criteria and rule settings:

[0251] Within this interval, a threshold OSM = 0.2 is set to distinguish between emergency and non-emergency safety problems. When OSM is below 0.2, the system will automatically trigger an emergency alarm and activate the emergency plan, such as immediately evacuating personnel and shutting down relevant equipment. When OSM is between 0.2 and 0.33, the system will start non-emergency safety inspection and maintenance procedures, such as regularly checking gas concentration and adjusting the ventilation system. The setting of this threshold is based on the analysis of historical data and accident cases to ensure timely response in case of serious safety problems.

[0252] Interaction rule description settings:

[0253] Within this interval, the change of each parameter will have a significant impact on OSM. When the gas concentration QTn increases by 10%, OSM will decrease by 5%. When the ventilation air volume TFl increases by 20%, OSM will increase by 10%. This interaction rule shows that improving the ventilation system can significantly enhance the safety of the refuge chamber. At the same time, improvements in geological stability DZWd and mine hydrology KJSw will also have a positive impact on OSM. For example, a 15% increase in DZWd makes OSM rise by 8%, and a 20% reduction in KJSw makes OSM rise by 12%. These interaction rules provide specific operation guidelines for the safety management of the refuge chamber.

[0254] Interval 2, 0.33 < OSM ≤ 0.66; In this interval, the OSM value indicates that the comprehensive evaluation of the refuge chamber is at a medium level. Specifically, when OSM is between 0.33 and 0.66, the safety evaluation index SEI of the refuge chamber is between 0.5 and 0.7, the disaster avoidance influence index EII is between 0.4 and 0.6, and the emergency refuge state coefficient ESC is between 0.6 and 0.8; If OSM is 0.5, it indicates that the comprehensive evaluation of the safety, disaster avoidance conditions and miner status of the refuge chamber is 50% of the ideal state; At this time, there are some safety problems, such as the gas concentration is slightly higher than 5% of the normal value, the temperature is slightly lower than 10% of the normal value, and the humidity is slightly higher than 15% of the normal value. These factors result in OSM being at a medium level and regular safety inspections and maintenance are required;

[0255] Judgment criteria and rule settings:

[0256] Within this interval, a threshold OSM = 0.5 is set to distinguish between safety problems that require key attention and general safety problems. When OSM is lower than 0.5, the system will initiate safety inspection and maintenance procedures that require key attention, such as strengthening gas concentration monitoring and optimizing the ventilation system; When OSM is between 0.5 and 0.66, the system will initiate general safety inspection and maintenance procedures, such as regularly checking the operating conditions of equipment and performing routine maintenance; The setting of this threshold is based on the analysis of safety data to ensure timely response when safety problems require key attention;

[0257] Interaction rule description settings:

[0258] Within this interval, the change of each parameter will have a certain impact on OSM. When the gas concentration QTn increases by 5%, OSM will decrease by 3%; When the ventilation air volume TFl increases by 10%, OSM will increase by 5%; This interaction rule shows that improving the ventilation system can enhance the safety of the refuge chamber. At the same time, the improvement of geological stability DZWd and mine hydrography KJSw will also have a positive impact on OSM. For example, when DZWd increases by 10%, OSM increases by 4%, and when KJSw decreases by 15%, OSM increases by 6%; These interaction rules provide specific operation guidelines for the safety management of the refuge chamber;

[0259] Interval Three, 0.66 < OSM < 1; In this interval, the OSM value indicates a relatively high comprehensive evaluation of the refuge chamber, making it a relatively good choice. Specifically, when OSM is between 0.66 and 1, the safety evaluation index SEI of the refuge chamber is higher than 0.7, the disaster avoidance impact index EII is higher than 0.6, and the emergency refuge state coefficient ESC is higher than 0.8. If OSM is 0.8, it indicates that the comprehensive evaluation of the safety, disaster avoidance conditions, and miner status of the refuge chamber is in an 80% ideal state; at this time, there are some minor safety issues, such as the gas concentration being slightly lower than 5% of the normal value, the temperature being slightly higher than 10% of the normal value, and the humidity being slightly lower than 15% of the normal value. These factors result in OSM being at a relatively high level, but regular safety inspections and maintenance are still required;

[0260] Judgment Criteria and Rule Settings:

[0261] Within this interval, a threshold OSM = 0.85 is set to distinguish between the safety state that needs to be maintained and the safety state that needs to be further improved. When OSM is lower than 0.85, the system will initiate inspection and maintenance procedures to maintain the safety state, such as regularly checking the gas concentration and adjusting the ventilation system; when OSM is between 0.85 and 1, the system will initiate inspection and maintenance procedures to further improve the safety state, such as optimizing the equipment operation efficiency and improving the safety management level. The setting of this threshold is based on the analysis of safety data to ensure timely response when the safety state needs to be further improved;

[0262] Interactive Rule Description Settings:

[0263] Within this interval, the change of each parameter will affect OSM. When the gas concentration QTn decreases by 5%, OSM will increase by 3%; when the ventilation air volume TFl decreases by 10%, OSM will decrease by 5%. This interactive rule indicates that maintaining the efficient operation of the ventilation system can maintain the safety of the refuge chamber. At the same time, the improvement of geological stability DZWd and mine hydrography KJSw will also have a positive impact on OSM. For example, when DZWd increases by 5%, OSM will increase by 2%; when KJSw decreases by 10%, OSM will increase by 3%; these interactive rules provide specific operation guidelines for the safety management of the refuge chamber;

[0264] In Interval One for SEI k and EII k The calibration and fine-tuning are respectively:

[0265] For the adjustment of SEI k In the low OSM interval, the safety evaluation is affected by various adverse factors, such as equipment failure rate and gas leakage rate. A calibration factor is set to adjust SEI k Therefore, the adjusted SEI k is

[0266] For EII k In the same interval, the disaster avoidance impact index decreases due to the deterioration of environmental conditions, and another calibration factor is set , used to adjust EII k Therefore, the adjusted EII k for

[0267] The calibration fine-tuning of SEI and EII in interval 2 is:

[0268] For SEI k In this range, the safety evaluation index needs to be fine-tuned according to the actual situation; set the calibration factor , used to adjust SEI k , therefore, the adjusted SEI k for

[0269] For EII k The disaster avoidance impact index needs to be fine-tuned according to environmental conditions and the calibration factor needs to be set. , used to adjust EII k ; Therefore, the adjusted EII k for

[0270] The calibration fine-tuning of SEI and EII in interval three is:

[0271] For SEI k In this range, the safety evaluation index is close to the ideal state, but it still needs fine-tuning to ensure accuracy. Set the calibration factor , used to adjust SEI k ; Therefore, the adjusted SEI k for

[0272] For EII k The disaster avoidance impact index is close to the ideal state in this range, but it needs fine-tuning and setting the calibration factor. , used to adjust EII k ; Therefore, the adjusted EII k for

[0273] Through the above mathematical expression, SEI k and EII k Calibration and fine-tuning were performed in different intervals to ensure the accuracy and practicality of the model.

[0274] Embodiment eight:

[0275] Further explanation based on Example 7, in order to verify the effectiveness and advantages of the optimal selection model OSM, a series of experiments were designed to evaluate the safety and disaster avoidance efficiency of different refuge chambers under specific conditions; the experimental objects include three adjacent refuge chambers, namely chamber M1, chamber M2, and chamber M3, each of which is equipped with necessary safety monitoring equipment and environmental control systems;

[0276] Before the experiment started, basic data of each chamber was collected, including the safety evaluation index SEI k , Disaster Impact Index EII k and the safe-haven state coefficient ESC k ;SEI k and EII k Calculated by monitoring the gas concentration, temperature, humidity and related environmental parameters in the chamber; ESC k The miners’ heart rate, body temperature, fatigue level, and perception ability are taken into consideration;

[0277] During the experiment, different mine accident scenarios were simulated, including gas leakage, temperature anomalies and geological instability. In each scenario, the real-time data of each chamber was recorded, and the optimal choice model index OSM was calculated using the OSM formula. By comparing the OSM values ​​of different chambers, it is possible to determine which chamber is the best refuge option under specific conditions.

[0278] In addition, a calibration factor is introduced to fine-tune the SEI k and EII k , to more accurately reflect the safety and disaster avoidance conditions under different OSM intervals. These calibration factors are dynamically adjusted according to the OSM values ​​to ensure the accuracy and practicality of the model output;

[0279] The following is an Excel table record of the experimental data, showing the OSM values ​​and related parameters of each chamber in different scenarios, as shown in the following table:

[0280] Table 1

[0281]

[0282] The data analysis and beneficial effects of the above table are described as follows:

[0283] Through comparative analysis of the above table data, we can clearly see the application effect of the optimal selection model OSM under different conditions. The following is the specific analysis process:

[0284] Comparison under normal circumstances:

[0285] Under normal circumstances, the OSM value of chamber M3 is the highest at 0.78, followed by chamber M2 at 0.68, and finally chamber M1 at 0.55; this indicates that chamber M3 is the best choice for refuge based on the comprehensive consideration of the safety evaluation index SEI, the disaster avoidance impact index EII, and the risk avoidance state coefficient ESC;

[0286] The SEI and EII of chamber M3 are higher than those of other chambers, and its ESC is also higher, which directly leads to its leading OSM value;

[0287] Comparison in emergency situations:

[0288] In an emergency, the OSM value of chamber M2 is the highest at 0.45, followed by chamber M3 at 0.55, and finally chamber M1 at 0.35; this indicates that in an emergency, chamber M2 is relatively better in terms of safety and disaster avoidance efficiency;

[0289] Although the SEI and EII of chamber M2 decreased during the emergency, the relative stability of ESC enabled it to maintain a high ranking in the OSM calculation;

[0290] Through the above analysis, it can be seen that the optimal selection model proposed in the present invention has beneficial effects in practical applications:

[0291] Accuracy of comprehensive evaluation: The model can make a comprehensive evaluation based on the current risk avoidance status of miners, the safety level of the three adjacent refuge chambers, and the degree of disaster avoidance impact, and accurately select the optimal refuge chamber;

[0292] Adaptability: The model can dynamically adjust the evaluation criteria in normal or emergency situations according to different situations, ensuring that the most appropriate refuge chamber can be selected in various situations;

[0293] Practicality: Through the numerical evaluation system, the model provides an intuitive and operational decision support tool to help mine managers make decisions quickly;

[0294] Dynamic adjustment mechanism: By introducing a calibration factor, the model can dynamically adjust the SEI according to different ranges of OSM values. k and EII k , to ensure the timeliness and accuracy of the evaluation;

[0295] Comprehensive considerations: The model not only takes into account safety and disaster avoidance conditions, but also takes into account the risk avoidance status of miners, which is a factor that is rarely considered in traditional models, increasing the practicality and humanity of the model;

[0296] When SEI k and EII k When increasing, if ESC k If it remains stable or increases, the OSM value will increase;

[0297] When ESC k When the SEI decreases k and EII k The higher the value, the lower the OSM value, which emphasizes the importance of the miner's status in the evaluation; through the above specific numerical analysis, it can be seen that the present invention in the embodiment not only improves the accuracy and efficiency of refuge chamber selection, but also enhances the overall level of mine safety management.

[0298] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0299] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0300] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0301] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A parametric modeling method for three-dimensional mine tunnels, characterized in that: The specific steps include: Step S1, obtaining and preprocessing the tunnel GIS data, using Revit software to implement tunnel BIM parametric modeling through the graphical programming platform Dynamo, and forming three-dimensional modeling data of the mine tunnel; Step S2, obtaining the three-dimensional modeling data of the tunnel, and sequentially marking the several refuge chambers thereon in the same direction to form a sequence {1, 2, ..., i-1, i, i+1, ..., n}, where i represents the i-th refuge chamber, and i-1 and i+1 represent the two refuge chambers adjacent to the i-th refuge chamber, respectively, and n represents the total number of refuge chambers; Step S3, determine the i-th refuge chamber closest to the current miner, and determine the i-1 and i+1 refuge chambers adjacent to the i-th refuge chamber according to the current position of the i-th refuge chamber, and collect disaster data around the i-th refuge chamber and the i-1 and i+1 refuge chambers adjacent to the i-th refuge chamber in sequence; Step S4, obtaining the collected disaster data of the three refuge chambers, analyzing and processing them, and generating a safety evaluation index for each refuge chamber, the evaluation index is used to evaluate the safety level of each refuge chamber; Define the safety evaluation index of refuge chamber as SEI k , SEI i 、SEI i-1 、SEI i+1 They represent the calculation formulas for the safety evaluation index of three refuge chambers. The specific formulas are as follows: Step S5, determining the disaster avoidance parameters of the current miner and the three refuge chambers in step S3, the disaster avoidance parameters including slope, obstacle coefficient, terrain undulation coefficient and disaster avoidance distance, and separately collecting the current miner's risk avoidance state coefficient; Step S7, respectively setting the warning thresholds of the safety evaluation index and the disaster avoidance impact index to A and B. When any index exceeds the corresponding warning threshold, reselecting the next adjacent refuge chamber of the current refuge chamber until all indexes are below the corresponding warning threshold; Step S8, obtaining the safety evaluation index and the disaster avoidance impact index, and introducing the current miner's risk avoidance state coefficient to construct an optimal selection model, which is used to conduct a comprehensive evaluation based on the current miner's risk avoidance state, and the safety level and disaster avoidance impact evaluation results of the three adjacent refuge chambers, so as to select the optimal refuge chamber and form a tunnel disaster avoidance route; The mathematical formula of the designed optimal selection model is as follows: Among them, OSM is the optimal selection model index, which is used to evaluate and select the optimal refuge chamber; SEI k is the safety evaluation index of the kth refuge chamber, reflecting the safety level of the refuge chamber; EII k is the disaster impact index of the kth refuge chamber, reflecting the disaster conditions of the refuge chamber; ESC k The risk avoidance state coefficient when selecting the kth refuge chamber for miners takes into account the miners' physiology, psychology, mobility and environmental perception. k is the index of the refuge chamber, which is related to SEI k The index of k in the table is the same, and the value range is i-1, i, i+1, representing the three refuge chambers adjacent to the current miner; According to the calculation formula of the risk aversion coefficient ESC, the following ESC is obtained k The calculation formula is: ESC k =w1·HR k +w2·BT k +w3·FL k +w4·SL k +w5·PL k +w6·MS k +w7·E k +w8·FOV k +w9·HS k Among them, HR k ,BT k ,FL k ,SL k ,PL k ,MS k ,E k ,FOV k ,HS k Respectively represent the physiological and psychological status data of the employees corresponding to the kth refuge chamber, where w i′ is the weight of each factor, i′∈1,2,...9; The value range of OSM is set to (0,1). When OSM is close to 1, it means that the selected refuge chamber is the best choice, taking into account safety, disaster avoidance conditions and miners' risk avoidance status; when OSM is close to 0, it means that the comprehensive evaluation of the refuge chamber is low and it is not the best choice.

2. A method for parametric modeling of three-dimensional mine tunnels according to claim 1, characterized in that: The tunnel GIS data is obtained and preprocessed, and the preprocessed data is used in Revit software, and the tunnel BIM parametric modeling is realized through the graphical programming platform Dynamo to form the three-dimensional modeling data of the mine tunnel, which specifically includes the following contents: Obtain the original GIS data of the mine, and form a GIS data set after preliminary screening and sorting; Obtain GIS data sets and perform data preprocessing to form a preprocessed Revit compatible format; Import the pre-processed GIS data into Revit software to import Revit’s dataset; Obtain the Revit data set and use Dynamo for parametric modeling to ultimately generate 3D parametric modeling data for the mine tunnel; The method of obtaining the three-dimensional modeling data of the tunnel and sequentially marking the several refuge chambers thereon in the same direction specifically includes the following contents: Obtaining three-dimensional modeling data of the tunnel; Identify and mark the locations of all refuge chambers as {1, 2, ..., i-1, i, i+1, ..., n}, where i represents the i-th refuge chamber and n represents the total number of refuge chambers; Verify the accuracy of the markings.

3. A method for parametric modeling of three-dimensional mine tunnels according to claim 2, characterized in that: The method of determining the i-th refuge chamber closest to the current miner, and determining the i-1 and i+1 refuge chambers adjacent to the current i-th refuge chamber, and collecting disaster data around the three refuge chambers in sequence, specifically includes the following contents: Use the miner positioning system to determine the current miner's precise position in the tunnel and obtain the miner's precise position coordinates; Calculate the nearest refuge chamber, by calculating the Euclidean distance between the miner's position and each refuge chamber, determine the i-th refuge chamber closest to the miner; Collect disaster data around the refuge chambers, and use disaster monitoring equipment to collect disaster data around the i-th refuge chamber and the i-1 and i+1 refuge chambers adjacent to it; The disaster data include gas concentration, temperature, humidity, ventilation volume, geological stability data, and mine hydrological data. The gas concentration is marked as QTn, the temperature is marked as Wd, the humidity is marked as Sd, the ventilation volume is marked as TFl, the geological stability data is marked as DZWd, and the mine hydrological data is marked as KJSw.

4. A method for parametric modeling of three-dimensional mine tunnels according to claim 3, characterized in that: The three refuge chamber disaster data collected are obtained and analyzed to generate a safety evaluation index for each refuge chamber. The evaluation index is used to evaluate the safety level of each refuge chamber, including the following: Among them, SEI i 、SEI i-1 、SEI i+1 is the safety evaluation index of the three refuge chambers, SEI k Represents SEI i 、SEI i-1 、SEI i+1 A set of , where k takes the values ​​i, i-1, i+1 respectively; w ij 、w (i-1)j 、w (i+1)j are the weight coefficients of the jth parameter in the i-th, i-1-th, and i+1-th refuge chambers, j=1, 2, ..., 6, corresponding to gas concentration QTn, temperature Wd, humidity Sd, ventilation air volume TFl, geological stability DZWd, and mine hydrology KJSw, respectively; X ij X (i-1)j X (i+1)j are the actual measured values ​​of the jth parameter in the i-th, i-1-th, and i+1-th refuge chambers, i.e. j from 1 to 6 represents QTn, Wd, Sd, TFl, DZWd, and KJSw respectively; Norm(X ij )、Norm(X (i-1)j )、Norm(X (i+1)j ) are respectively ij X (i-1)j X (i+1)j A function that performs normalization to ensure that all parameters are compared on the same scale; θ i ,θ i-1 ,θ i+1 are the threshold parameters of the i-th, i-1-th, and i+1-th refuge chambers, respectively, which are used to adjust the sensitivity of the model; Setting the safety evaluation index SEI k The value range is (0,1). When SEI k When it is close to 1, it means that the safety level of the refuge chamber is high; when SEI k When it is close to 0, it means the safety level is low; Safety Evaluation Index (SEI) k The value range (0,1) is divided into three intervals, and each interval is described in detail with quantitative content, specific judgment criteria and rules are set, and interaction rules are explained: Interval 1, 0 <SEI k ≤0.33; this range indicates that the safety level of the refuge chamber is low and emergency treatment is required. SEI k When it is lower than 0.2, an emergency alarm is triggered. When it is between 0.2 and 0.33, non-emergency maintenance is initiated. Parameter changes significantly affect SEI k , improving current ventilation by 10% can improve safety; Interval 2, 0.33 <SEI k ≤0.66; medium safety level, SEI k SEI is between 0.33 and 0.

66. k When it is lower than 0.5, special attention should be paid. When it is higher, routine maintenance should be performed. Small changes in parameters affect SEI. k ; Interval 3, 0.66 <SEI k <1; high safety level, SEI k Between 0.66 and 1, SEI k If it is lower than 0.8, keep the status quo; if it is higher, improve safety management; small changes within 7% of the parameter will affect SEI k .

5. A method for parametric modeling of three-dimensional mine tunnels according to claim 4, characterized in that: The slope is marked as Pd, the obstacle coefficient is marked as OFs, the terrain relief coefficient is marked as TRF, and the disaster avoidance distance is marked as EDd; The current miner's risk avoidance state coefficient specifically includes physiological state data, psychological state data, mobility data, and environmental perception data, and the physiological state data includes heart rate, body temperature, and fatigue level, which are marked as HR, BT, and FL in sequence; The psychological state data includes stress level and panic level, which are marked as SL and PL respectively; The movement ability data includes movement speed and endurance, which are marked as MS and E respectively; The environmental perception capability data includes the field of view range value and the hearing sensitivity, which are marked as FOV and HS respectively; The calculation formula for constructing the safe-haven state coefficient ESC is: ESC=w1·HR+w2·BT+w3·FL+w4·SL+w5·PL+w6·MS+w7·E+w8·FOV+w9·HS Among them, w i′ is the weight of each factor, i′∈1,2,...9; Step S6, obtaining the disaster avoidance parameters of the three refuge chambers in step S5, and performing analysis and processing to generate a disaster avoidance impact index for each refuge chamber, which is used to evaluate the degree of disaster avoidance impact of each refuge chamber; Define the disaster impact index of the i-th refuge chamber as EII i , the calculation formula is as follows: Among them, EII i is the disaster impact index of the i-th refuge chamber; w j′ is the weight, j′=1,2,3,4; corresponding to the weights of slope, obstacle coefficient, terrain undulation coefficient and disaster avoidance distance respectively; f j′ is a function, corresponding to the processing function of the four parameters; n is the total number of refuge chambers; Function f j′ The definition of is as follows; f1(Pd i )=exp(-Pd i ) is an exponential decay function of the slope. The greater the slope, the smaller the impact. It is the normalized function of the obstacle coefficient. The more obstacles there are, the smaller the impact. It is a normalized function of the terrain relief coefficient. The greater the terrain relief, the smaller the impact. It is the inverse function of the disaster avoidance distance. The farther the distance, the smaller the impact. Setting the Disaster Impact Index (EII) i The value range of EII is (0,1). i When EII is close to 1, it means that the disaster shelter condition of the i-th refuge chamber is good; i When it is close to 0, it means that the disaster shelter conditions are poor.

6. A method for parametric modeling of three-dimensional mine tunnels according to claim 5, characterized in that: Disaster Impact Index (EII) i The value range is divided into the following three intervals: EII i Located at 0<EII i In the range of ≤0.3, the disaster shelter conditions in the refuge chamber are significantly insufficient and there is a high risk; Disaster Impact Index (EII) i Falling within 0.3<EII i When the value is within the range of ≤0.7, the disaster shelter conditions of the refuge chamber are at a medium level. The refuge chamber in this range is not the best choice, but it can still be used as an effective option for risk avoidance. EII i Reach 0.7<EII i When the value is less than 1, the disaster avoidance conditions in the refuge chamber are good, which significantly reduces the risk of disaster avoidance for miners.

7. A method for parametric modeling of three-dimensional mine tunnels according to claim 6, characterized in that: The warning thresholds for separately setting the safety evaluation index and the disaster avoidance impact index are A and B. When any index exceeds the corresponding warning threshold, the next adjacent refuge chamber of the current refuge chamber is reselected until each index is below the corresponding warning threshold. The specific content includes the following: Separate warning thresholds A and B for the safety evaluation index and the disaster avoidance impact index are set respectively; Real-time monitoring and evaluation; Compare the index with the threshold; monitor the SEI in real time k and EII i Compare with preset warning thresholds A and B; if SEI k >A and EII i >B, the current refuge chamber is considered safe and does not need to be replaced; if SEI k ≤A or EII i ≤B, then proceed to the next step; Select an adjacent refuge chamber; when SEI k or EII i When any index in is lower than its corresponding warning threshold, the system automatically selects the next adjacent refuge chamber of the current refuge chamber; Repeat the evaluation until the conditions are met; after selecting a new refuge chamber, repeat the steps of real-time monitoring and evaluation to select adjacent refuge chambers until the SEI of all evaluated refuge chambers is k and EII i All of them are higher than their corresponding warning thresholds.

8. The method for three-dimensional roadway parametric modeling of a mine according to claim 7, wherein: The value range (0, 1) of the optimal selection model OSM is divided into three intervals: Interval 1: 0 < OSM ≤ 0.

33. In this interval, when OSM is lower than 0.2, an emergency alarm is triggered. When it is higher than 0.2, a non-emergency safety inspection is carried out. The changes in gas concentration and ventilation air volume significantly affect OSM. A 10% increase in gas concentration causes a 5% decrease in OSM, and a 20% increase in ventilation air volume increases OSM by 10%. In addition, the improvement of geological stability and mine hydrology also has a positive impact on OSM, providing guidance for rapid response in emergency situations; Interval 2: 0.33 < OSM ≤ 0.

66. When OSM is lower than 0.5, the system starts a safety inspection with key attention. When it is higher than 0.5, maintenance is carried out. A 5% increase in gas concentration makes OSM decrease by 3%, and a 10% increase in ventilation air volume increases OSM by 5%. The improvement of geological stability and mine hydrology also has a positive impact on OSM, ensuring effective risk management at a medium safety level; Interval 3: 0.66 < OSM < 1. When OSM is lower than 0.85, the system conducts an inspection to maintain the safety state. When it is higher than 0.85, it seeks to further improve the safety state. A 5% decrease in gas concentration increases OSM by 3%, and a 10% decrease in ventilation air volume makes OSM decrease by 5%. The slight improvement of geological stability and mine hydrology also affects OSM, guiding the maintenance and improvement of safety measures at a high safety level.

9. A method for parametric modeling of three-dimensional mine tunnels according to claim 8, characterized in that: When in the interval 0 < OSM ≤ 0.33, the calibration fine-tuning of SEI k and EII k are respectively as follows: For SEI k In the low OSM range, the safety evaluation is affected by the equipment failure rate and gas leakage rate, and the calibration factor is set. To adjust SEI k , therefore, the adjusted SEI k for For EII k In the same interval, the disaster avoidance impact index is reduced and another calibration factor is set. Used to adjust EII k Therefore, the adjusted EII k for The calibration fine-tuning of SEI and EII when 0.33 < OSM ≤ 0.66 in Interval 2 is: For SEI k In this range, the safety evaluation index needs to be fine-tuned according to the actual situation; set the calibration factor To adjust SEI k , therefore, the adjusted SEI k for For EII k The disaster avoidance impact index needs to be fine-tuned according to environmental conditions and the calibration factor needs to be set. Used to adjust EII k ; Therefore, the adjusted EII k for The calibration fine-tuning of SEI and EII when 0.66 < OSM < 1 in Interval 3 is: For SEI k In this range, the safety evaluation index is close to the ideal state, but it still needs fine-tuning to ensure accuracy. Set the calibration factor To adjust SEI k ; Therefore, the adjusted SEI k for For EII k The disaster avoidance impact index is close to the ideal state in this range, but it needs fine-tuning and setting the calibration factor. Used to adjust EII k ; Therefore, the adjusted EII k for

Images