Intelligent coal mine accident risk assessment method

Abstract

The invention relates to the technical field of coal mine safety, solves the technical problems that gas concentration and ventilation quantity are not comprehensively considered during risk assessment and accident potential levels cannot be effectively judged, and particularly relates to an intelligent coal mine accident risk assessment method which comprises the following steps: S1, acquiring gas concentration data and mine internal temperature in real time; s2, calculating a weighted average value of the gas concentration according to the gas concentration data; s3, judging whether accident potential exists or not according to the concentration potential threshold value; s4, whether a risk alarm is triggered or not is judged according to the warning threshold value; s5, calculating the gas emission rate according to the ventilation quantity data in combination with the weighted average value of the gas concentration; s6, constructing a risk assessment model according to the gas emission rate and the mine internal temperature, and generating a risk assessment coefficient; and S7, judging whether a risk alarm is triggered or not according to the risk assessment threshold. According to the method, more comprehensive risk assessment is provided, and a response is made in advance by hierarchically judging the risk by setting a plurality of threshold values.

Description

Technical Field

[0001] The present invention relates to the field of coal mine safety technology, and in particular to an intelligent coal mine accident risk assessment method. Background Art

[0002] Gas concentration monitoring and mine safety management are crucial safety components in underground coal mines and other underground operations. The gas content in a mine is directly related to safe operations. Excessive gas concentrations can cause serious safety incidents such as gas explosions. Therefore, real-time monitoring of gas concentrations and the timely implementation of emergency measures when potential hazards arise are crucial to ensuring safe mine operations.

[0003] In existing technologies, many monitoring systems rely solely on gas concentration to determine mine safety. This single indicator cannot accurately reflect the actual risk situation. Traditional risk assessment methods can only determine whether a mine is dangerous, but cannot further take corresponding measures based on different risk levels. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides an intelligent coal mine accident risk assessment method, which solves the technical problems of not comprehensively considering gas concentration and ventilation volume during risk assessment and being unable to effectively judge the level of accident hazards.

[0005] To solve the above technical problems, the present invention provides the following technical solution: an intelligent coal mine accident risk assessment method, the method comprising the following steps:

[0006] S1. Real-time acquisition of gas concentration data M within time period T ij and the temperature inside the mine

[0007] S2, according to the gas concentration data M ij Calculate the weighted average value M of gas concentration;

[0008] S3. Determine whether there is an accident hazard based on the concentration hazard threshold A;

[0009] If the weighted average value of gas concentration M is less than the concentration hidden danger threshold value A, the system is in a stable state, and the process returns to step S1 and re-evaluates the next time period T+1.

[0010] If the weighted average value of gas concentration M is greater than the concentration potential hazard threshold A, there is a potential accident hazard, and the process proceeds to step S4;

[0011] S4. Determine whether a risk alert is triggered based on the warning threshold B;

[0012] If the weighted average value of gas concentration M ≤ warning threshold B, proceed to step S5;

[0013] If the weighted average value of gas concentration M> warning threshold B, a risk alarm is triggered;

[0014] S5. Obtain ventilation volume data Q i , according to the ventilation data Q i Calculate the gas emission rate V based on the weighted average value M of gas concentration;

[0015] S6, according to the gas outburst rate V and the temperature inside the mine Construct a risk assessment model and generate a risk assessment coefficient P;

[0016] S7. Determine whether to trigger a risk alert based on the risk assessment threshold C;

[0017] If the risk assessment coefficient P ≤ risk assessment threshold C, an early warning signal is issued;

[0018] If the risk assessment coefficient P>risk assessment threshold C, a risk alarm is triggered.

[0019] By means of the above technical solution, the present invention provides an intelligent coal mine accident risk assessment method, which has at least the following beneficial effects:

[0020] 1. The present invention uses multi-location, high-frequency data collection, combined with ventilation volume data, to accurately calculate the gas outburst rate. It collects gas concentration data in real time at multiple key locations in the mine, and simultaneously obtains ventilation volume data. This multi-dimensional data collection method avoids the one-sidedness brought about by a single location or a single data type. The gas flow rate is estimated by multiplying the gas concentration and the ventilation volume, and then through time series analysis and smoothing, an accurate gas outburst rate is finally obtained. The accurate gas outburst rate provides a solid data foundation for risk assessment, can more accurately reflect the actual gas outburst conditions in the mine, greatly improves the accuracy of risk assessment results, and allows coal mine managers to have a clearer understanding of potential risks, so as to formulate more targeted preventive measures.

[0021] 2. The present invention utilizes real-time data collection and a dynamic calculation mechanism, resulting in a high degree of timeliness: gas concentration and ventilation volume data are collected in real time at fixed intervals, and each data update is rapidly reflected in the calculation of the gas emission rate. This enables the risk assessment system to promptly detect subtle changes in gas emission conditions within the mine. If the gas emission rate fluctuates abnormally, the system detects it within a very short timeframe and issues a timely warning signal. Compared to traditional assessment methods, this significantly shortens the time lag for risk discovery, provides valuable emergency response time for coal mine safety, and effectively reduces the likelihood of accidents.

[0022] 3. The present invention comprehensively considers multiple factors to determine the weights of location points and realizes a comprehensive and integrated assessment: when calculating the comprehensive gas outburst rate, the weights are determined based on multiple factors such as the degree of fluctuation of the historical data of gas outbursts at the location point and the frequency of mining activities in the area through scientific means such as the hierarchical analysis method. This method fully considers the actual conditions of different areas in the mine, and the contribution of different location points to the overall gas risk is reasonably quantified. Comprehensive and integrated consideration of various factors in the mine makes risk assessment no longer limited to single data or local conditions, but starts from the overall level to conduct a more comprehensive and in-depth assessment of coal mine accident risks, which helps coal mine managers to formulate more complete and more global risk management strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0024] Figure 1 This is a flow chart of an intelligent coal mine accident risk assessment method of the present invention. DETAILED DESCRIPTION

[0025] To make the above-mentioned objectives, features, and advantages of the present invention more clearly understood, the present invention is further described below in detail with reference to the accompanying drawings and specific embodiments. This will enable a full understanding of how this application uses technical means to solve technical problems and achieve technical effects, and to implement the invention accordingly.

[0026] This embodiment proposes an intelligent coal mine accident risk assessment method, which judges whether the mine is in a stable state or has accident hazards by comparing the weighted average value of gas concentration with the hidden danger threshold, so as to take timely measures to avoid accidents. By setting a warning threshold, the weighted average value of gas concentration is judged. When the gas concentration reaches a certain dangerous level, a risk alarm is triggered in time to remind relevant personnel to pay attention. A risk assessment model is constructed based on the gas outburst rate and the temperature inside the mine, and a risk assessment coefficient is generated. The risk status of the mine is further quantitatively assessed. The risk assessment coefficient is judged based on the risk assessment threshold, and the warning signal and risk alarm are distinguished, making the warning and alarm mechanism more accurate and effective. It can not only give timely warnings when potential risks occur, but also issue alarms when the risks are high, so as to arrange response measures more reasonably and ensure safe production in mines. Figure 1 As shown, the method includes the following steps:

[0027] S1. Real-time acquisition of gas concentration data M within time period T ij and the temperature inside the mine As a further implementation of the method in this embodiment, the specific process is as follows:

[0028] S11. Arrange sensors at key locations in the mine, including the mining face, return air lane, and electromechanical chamber;

[0029] S12, collect gas concentration data M at key location i at every time t i1 、M i2 ,...,M in , calculate the average gas concentration M at each key location i i , the calculation formula is:

[0030]

[0031] Where M ij is the gas concentration data collected at the key location point i; n is the number of collection times;

[0032] S13, converting the temperature signal into an electrical signal and transmitting it to the data acquisition system. After the data acquisition system processes and converts the signal, the acquisition system collects temperature data T1, T2, ..., T at intervals of time t. n , the calculation formula is:

[0033]

[0034] Where, is the internal temperature of the mine; n is the number of acquisitions; T i It is to collect temperature data.

[0035] S2. Calculate the weighted average value of gas concentration based on the gas concentration data. As a further implementation of the method in this embodiment, the specific process is as follows:

[0036] S21. Calculate the importance of key location i in mine safety production based on the number of personnel working at each key location i on a daily basis and the number of key equipment at key location i in the entire mine production process. i1 , the calculation formula is:

[0037] s i1 =ξ1*P i +ξ2*B i

[0038] Where, P i is the number of personnel performing daily operations at key location i; B iis the number of key equipment at key location i in the entire mine production process; ξ1 and ξ2 are the importance weight coefficients of the number of personnel and the number of equipment respectively; if the two factors are equally important to safe production, then ξ1 = ξ2 = 1 can be set;

[0039] S22. Based on the geological exploration report, obtain the gas content data of each key location and the geological structure of the location. According to the geological structure of the location, obtain the coal seam inclination angle θ. Normalize the coal seam inclination angle and gas content data, and perform weighted average calculation to comprehensively evaluate the possibility of gas outburst. i2 , the specific calculation formula is:

[0040]

[0041] Where τ is the weight of gas content data, (1-τ) is the weight of coal seam inclination, and h min is the minimum value of gas content data, h max is the maximum value of gas content data, h i is the gas content data, θ i is the coal seam inclination, θ min is the minimum value of coal seam inclination, θ max It is the maximum inclination of the coal seam.

[0042] S23. Obtain ventilation conditions at each key location, and obtain gas emission frequency and intensity based on gas emission history records, and determine the danger of gas emission based on ventilation conditions at each key location. i3 ;

[0043] Obtain the gas emission frequency and gas emission amount according to the gas emission history record, calculate the average value of gas emission frequency and gas emission amount, obtain the maximum and minimum values ​​of gas emission frequency and gas emission amount, and determine the danger of gas emission. i3 The specific calculation formula is:

[0044]

[0045] Where, is the average frequency of gas outburst, f min is the minimum value of gas outburst frequency, f max is the maximum value of gas emission frequency, γ1 is the gas emission frequency weight, γ2 is the gas emission amount weight, is the average gas emission volume, I min is the minimum value of gas emission, I max It is the maximum value of gas emission.

[0046] S24. According to the importance of each key location point in mine safety production i1, the possibility of gas outburst i2 and the danger of gas outbursts i3 , determine the weight w of each key position point i i , and w i >0;

[0047] According to the importance of each key location point in mine safety production i1 , the possibility of gas outburst i2 and the danger of gas outbursts i3 , determine the weight w of each key position point i i , the calculation formula is:

[0048]

[0049] Where s i1 is the importance of key location point i in mine safety production; a is the weight factor of the importance of key location point i in mine safety production; s i2 is the possibility of gas outburst at key location i; b is the weight factor of the possibility of gas outburst at key location i; s i3 is the hazard of gas outburst at key location i; c is the hazard weight factor of gas outburst at key location i; m is the number of key location i; w i is the weight of each key position point i.

[0050] S25, according to the average gas concentration M at the key position i i Combined with the weight w of key position point i i Calculate the weighted average value M of gas concentration using the following formula:

[0051]

[0052] Where M is the weighted average of gas concentration; m is the number of key location points i.

[0053] It should be noted that gas concentrations may vary significantly at different locations in a mine. By collecting data at multiple key locations, calculating the average, and then performing a weighted average, we can comprehensively consider the gas conditions at each location, avoiding the one-sidedness of data from a single location, thereby more accurately reflecting the overall gas concentration level of the mine and providing a more reliable basis for risk assessment. Assigning corresponding weights to different key locations can reflect the importance of each location in the mine gas risk. For example, areas with large gas outbursts or frequent human activities, such as mining working faces, are given higher weights, and their gas concentrations have a greater impact on the overall weighted average. This helps to highlight the potential risks of these key locations in risk assessments and make the assessment results more targeted.

[0054] S3. Determine whether an accident hazard exists based on a concentration hazard threshold. As a further implementation of this method in this embodiment, the specific process is as follows: Gas concentration data is collected at key locations i and a weighted average gas concentration value M is calculated to reflect the current comprehensive gas concentration level within the mine. The weighted average gas concentration value is then compared with the concentration hazard threshold value. The concentration hazard threshold value A is set to 1%.

[0055] If the weighted average gas concentration M is less than or equal to 1%, it indicates that the current gas concentration is within a relatively safe range and the mine is in a stable state. At this point, the system automatically returns to step S1 and collects and processes gas concentration data for the next time period T+1, continuously monitoring changes in gas concentration.

[0056] If the weighted average value M of the gas concentration is greater than 1%, it means that the gas concentration has exceeded the normal safety range and there is a potential accident hazard, and the process proceeds to step S4 for the next step of judgment.

[0057] It's important to note that the concentration hazard threshold is a safety limit established through scientific research and practical experience. When gas concentrations approach or exceed the threshold, an alarm is triggered, prompting personnel to take appropriate measures to prevent accidents. In underground coal mines, when gas concentrations reach 1%, the alarm system is triggered, prompting workers to prepare for ventilation and evacuation in advance to prevent serious accidents like gas explosions. Using specific concentration values ​​as a basis for judgment makes the assessment of accident hazards more objective and accurate. Compared to subjective judgments or vague standards, the concentration hazard threshold provides a clear, quantitative indicator, reducing the influence of human factors.

[0058] S4. Determine whether a risk alarm has been triggered based on the warning threshold. As a further implementation of this method in this embodiment, the specific process is as follows: Compare and analyze the weighted average gas concentration with the warning threshold: Set the warning threshold B to 5%. If the weighted average gas concentration M is ≤ 5%, it indicates that the gas concentration, while exceeding the hidden danger threshold A, has not yet reached an abnormal severity level. At this point, the mine has a certain degree of gas hazard, and further inspection and assessment of the ventilation system and environmental conditions must be carried out in step S5. If the weighted average gas concentration M is greater than 5%, it indicates that the gas concentration has reached an abnormal level and may cause a serious accident at any time. The risk alarm must be triggered immediately, and all mine operations must be stopped.

[0059] It's important to note that the system can quickly issue an alarm signal when gas concentrations and other related indicators approach dangerous levels. The 5% threshold strikes a balance between ensuring safe production and maintaining normal production activities. Within this range, gas concentrations generally won't immediately trigger serious accidents like explosions. For managers, this clear threshold also facilitates the development of unified management strategies and emergency response measures. When gas concentrations reach this threshold, they can follow established procedures, improving management efficiency and emergency response capabilities.

[0060] S5. Obtain ventilation volume data Q i The gas emission rate V is calculated based on the ventilation volume data combined with the weighted average of the gas concentration. As a further implementation of this method in this embodiment, the specific process is as follows: The gas emission rate is an indicator that measures the speed at which gas is released from the coal seam or rock stratum into the mine space. By calculating the gas emission rate, the amount of gas emitted per unit time can be understood. In order to further construct a risk assessment model and generate a risk assessment coefficient P, thereby further processing the coal mine accident risk and determining whether to trigger a risk alarm, this embodiment includes the following steps:

[0061] S51, within a time period T, obtain ventilation volume data Q1, Q2, ..., Q at intervals t using a flow meter installed in the ventilation duct. n , according to the ventilation volume data Q1, Q2..., Q n Calculate the weighted average ventilation volume Q using the following formula:

[0062]

[0063] Where Q i is the ventilation volume data obtained at every time t; n is the number of ventilation volume data obtained.

[0064] S52. Obtain theoretical ventilation volume Q l And the ventilation equipment performance correction coefficient η, combined with the weighted average ventilation volume Q to calculate the ventilation efficiency factor E, the formula is:

[0065]

[0066] Where E is the ventilation efficiency factor; η is the ventilation equipment performance correction factor;

[0067] S53. Calculate the standard deviation O of the gas concentration based on the weighted average value M of the gas concentration. Calculate the gas concentration fluctuation coefficient C based on the weighted average value M of the gas concentration and the standard deviation O of the gas concentration. The formula is:

[0068]

[0069] Where C is the gas concentration fluctuation coefficient, M is the weighted average of gas concentration, and O is the standard deviation of gas concentration;

[0070] S54. Calculate the gas outflow rate V based on the gas concentration fluctuation coefficient C, ventilation efficiency factor E, weighted average gas concentration M, and time period T. The formula is:

[0071]

[0072] Where Q is the weighted average ventilation volume; M is the weighted average gas concentration; T is the time period; δ is the dynamic balance factor of air pressure. is the temperature dynamic equilibrium factor.

[0073] It should be noted that a high gas outflow rate, even if the current weighted average gas concentration has not reached the explosion limit, may indicate rapid gas accumulation within a short period of time, thereby increasing the risk of a gas explosion. Conversely, a low gas outflow rate indicates a slow accumulation of gas and a relatively low risk.

[0074] S6. Constructing a risk assessment model based on the gas emission rate and the internal temperature of the mine to generate a risk assessment coefficient. As a further implementation of the method in this embodiment, the specific process is as follows:

[0075] S61. Since the gas emission rate and temperature have different dimensions, they need to be normalized to make them have the same influence in the model. For the gas emission rate V, the normalization formula is:

[0076]

[0077] Where V norm is the normalized gas outburst rate; V max is the maximum value of the gas outburst rate; V min It is the maximum value of the gas outburst rate;

[0078] The temperature inside the mine The normalization formula is:

[0079]

[0080] Where, is the normalized gas emission rate; It is the maximum value of the gas outburst rate; It is the maximum value of the gas outburst rate;

[0081] S62. Use the analytic hierarchy process (AHP) to determine the weights of gas emission rate and internal mine temperature in risk assessment;

[0082] S621. Evaluate the relative importance of gas emission rate and internal temperature of the mine based on historical risk accidents, and give a judgment value of relative importance. ij , the process is as follows:

[0083] Obtain gas emission rate and internal mine temperature within a certain historical time range, as well as historical risk accident records;

[0084] Obtain the severity of historical risk accidents based on historical risk accident records, which is used as an indicator to measure the severity of accidents;

[0085] Perform data cleaning and standardization on gas emission rate and internal temperature of mine within a certain historical time range;

[0086] Calculate the Pearson correlation coefficient r between gas emission rate and internal mine temperature and the severity of historical risk accidents v and r T ; The formula is:

[0087]

[0088] Where x V is the gas emission rate within the historical time range, x T is the internal temperature of the mine within the historical time range, y is the severity of historical risk accidents, and n is the number of measurements within the historical time range;

[0089] Obtain the Pearson correlation coefficient r between the gas emission rate and the internal temperature of the mine and the severity of historical risk accidents respectively v and r T The absolute value of r v |、|r T |, calculate the judgment value a of the relative importance of gas outburst rate and internal mine temperature to the severity of historical risk accidents based on absolute values ij and a ji , the calculation formula is:

[0090]

[0091] S622. The judgment value a of the relative importance of the severity of historical risk accidents based on the gas emission rate and the internal temperature of the mine. ij and a ji , construct the judgment matrix A as:

[0092]

[0093] S623, by calculating the eigenvalues ​​and eigenvectors of the judgment matrix A, the maximum eigenvalue λ of the judgment matrix A is obtained. max and its corresponding eigenvector x;

[0094] S624. Normalize the eigenvector x by dividing each element in the eigenvector by the sum of the elements in the eigenvector to obtain weight values ​​x1 and x2; where x1 is the weight value of the gas emission rate, and x2 is the weight value of the internal temperature of the mine;

[0095] S63, based on the gas emission rate and the internal temperature of the mine, a risk assessment model is constructed in combination with the gas emission rate weight value and the internal temperature weight value to generate a risk assessment coefficient.

[0096] By constructing a risk assessment model, the gas outburst rate and the temperature inside the mine are taken as input, combined with the gas outburst rate weight value and the mine internal temperature weight value. After a series of complex calculations and analyses, the risk assessment coefficient P is obtained. This coefficient comprehensively reflects the overall situation of the gas risk in the current mine. The model can update the risk assessment coefficient in real time according to the changes in the gas outburst rate and mine temperature, thereby realizing dynamic monitoring of the risk of gas explosion in mines.

[0097] The calculation formula of risk assessment coefficient P is:

[0098]

[0099] Where x1 is the weight value of gas emission rate; x2 is the weight value of mine internal temperature; V norm is the normalized gas emission rate; is the normalized gas emission rate.

[0100] It's important to note that both the gas emission rate and internal mine temperature are key factors influencing the risk of gas explosions. The gas emission rate is directly related to the rate of gas accumulation within the mine, while mine temperature not only affects the physical and chemical properties of gas but can also be associated with heat sources, increasing the potential risk of gas explosions. By building a risk assessment model that combines these two factors, a more comprehensive and accurate assessment of the overall risk of mine gas explosions can be achieved, avoiding the bias caused by considering only a single factor. The resulting risk assessment coefficient presents the gas explosion risk in a specific numerical form, quantifying the risk. This allows coal mine safety managers to more intuitively understand the current risk level within the mine, facilitating risk comparison and ranking. For example, a risk assessment coefficient of 0.8 indicates a high risk, allowing managers to take appropriate management measures based on the risk coefficient.

[0101] S7. Determine whether to trigger a risk alert based on the risk assessment threshold. As a further implementation of the method in this embodiment, the specific process is as follows:

[0102] If the risk assessment coefficient P ≤ the risk assessment threshold C, it means that although there is a certain gas risk in the mine, it is still within the controllable range. At this time, the system will issue an early warning signal to remind relevant personnel to pay close attention to the gas situation. For example, safety management personnel need to increase the frequency of inspections in key areas, and technical personnel need to conduct detailed inspections and maintenance of ventilation systems and gas monitoring equipment to ensure the normal operation of the system and prevent further expansion of risks.

[0103] If the risk assessment coefficient P exceeds the risk assessment threshold C, this indicates that the risk assessment coefficient has exceeded the safe and controllable threshold, and the mine faces a high gas risk, which could cause a serious accident at any time. At this time, the system immediately triggers a risk alarm, notifying all personnel in the mine through prominent sound and light signals. Once the alarm is triggered, they must strictly follow the emergency plan. For example, ongoing high-risk operations will be stopped, and personnel will be organized to evacuate to a safe area in an orderly manner. At the same time, a professional rescue team will be deployed to quickly investigate the source of the risk and implement emergency measures such as increasing ventilation and implementing gas extraction to reduce the gas risk until the risk assessment coefficient falls back to a safe range.

[0104] Those skilled in the art will appreciate that all or part of the steps in the above-mentioned embodiment methods can be accomplished by instructing the relevant hardware through a program. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0105] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to in detail. For the above embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For relevant parts, please refer to the partial description of the method embodiments.

[0106] The above embodiments provide a detailed introduction to the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. An intelligent coal mine accident risk assessment method, characterized in that: The method comprises the following steps: S1. Real-time acquisition of gas concentration data M within time period T ij and the temperature inside the mine S2, according to the gas concentration data M ij Calculate the weighted average value M of gas concentration; S3. Determine whether there is an accident hazard based on the concentration hazard threshold A; If the weighted average value of gas concentration M is less than the concentration hidden danger threshold value A, the system is in a stable state and returns to step S1 to re-judge the next time period T+1; If the weighted average value of gas concentration M is greater than the concentration potential hazard threshold A, there is a potential accident hazard, and the process proceeds to step S4; S4. Determine whether a risk alert is triggered based on the warning threshold B; If the weighted average value of gas concentration M ≤ warning threshold B, proceed to step S5; If the weighted average value of gas concentration M> warning threshold B, a risk alarm is triggered; S5. Obtain ventilation volume data Q i , according to the ventilation data Q i Calculate the gas emission rate V based on the weighted average value M of gas concentration; S6, according to the gas outburst rate V and the temperature inside the mine Construct a risk assessment model and generate a risk assessment coefficient P; S7. Determine whether to trigger a risk alert based on the risk assessment threshold C; If the risk assessment coefficient P ≤ risk assessment threshold C, an early warning signal is issued; If the risk assessment coefficient P>risk assessment threshold C, a risk alarm is triggered.

2. An intelligent coal mine accident risk assessment method according to claim 1, characterized in that: In step S1, the specific process includes the following steps: S11. Arrange sensors at key locations in the mine, including the mining face, return air lane, and electromechanical chamber; S12, collect gas concentration data M at key location i at every time t i1 、M i2 ,...,M in , calculate the average gas concentration M at each key location i i , the calculation formula is: Where M ij is the gas concentration data collected at the key location point i; n is the number of collection times; S13, converting the temperature signal into an electrical signal and transmitting it to the data acquisition system. After the data acquisition system processes and converts the signal, the acquisition system collects temperature data T1, T2, ..., T at intervals of time t. n , the calculation formula is: Where, is the internal temperature of the mine; n is the number of acquisitions; T i It is to collect temperature data.

3. An intelligent coal mine accident risk assessment method according to claim 2, characterized in that: In step S2, the specific process includes the following steps: S21. Calculate the importance of each key location point in mine safety production based on the number of people working at each key location point i on a daily basis and the number of key equipment at that location point in the entire mine production process. i1 ; S22. Based on the geological exploration report, obtain the gas content data of each key location and the geological structure of the location, and evaluate the possibility of gas outburst. i2 ; S23. Obtain ventilation conditions at each key location, and obtain gas emission frequency and intensity based on gas emission history records, and determine the danger of gas emission based on ventilation conditions at each key location. i3 ; S24. According to the importance of each key location point in mine safety production i1 , the possibility of gas outburst i2 and the danger of gas outbursts i3 , determine the weight w of each key position point i i , and w i >0; S25, according to the average gas concentration M at the key position i i Combined with the weight w of key position point i i Calculate the weighted average value M of gas concentration using the following formula: Where M is the weighted average of gas concentration; m is the number of key location points i.

4. The intelligent coal mine accident risk assessment method according to claim 3, characterized in that: In step S21, the importance s i1 The calculation formula is: s i1 =ξ1*P i +ξ2*B i Where, P i is the number of personnel performing daily operations at key location i; B i is the number of key equipment at key location point i in the entire mine production process; ξ1 and ξ2 are the importance weight coefficients of the number of personnel and the number of equipment, respectively; if the two factors are equally important to safe production, then ξ1 = ξ2 = 1 can be set.

5. The intelligent coal mine accident risk assessment method according to claim 3, characterized in that: In step S22, the probability of gas outburst s i2 The specific calculation formula is: Where τ is the weight of gas content data, (1-τ) is the weight of coal seam inclination, and h min is the minimum value of gas content data, h max is the maximum value of gas content data, h i is the gas content data, θ i is the coal seam inclination, θ min is the minimum value of coal seam inclination, θ max It is the maximum inclination of the coal seam.

6. The intelligent coal mine accident risk assessment method according to claim 3, characterized in that: In step S23, the risk of gas outburst is i3 The calculation formula is: Where, is the average frequency of gas outburst, f min is the minimum value of gas outburst frequency, f max is the maximum value of gas emission frequency, γ1 is the gas emission frequency weight, γ2 is the gas emission amount weight, is the average gas emission volume, I min is the minimum value of gas emission, I max It is the maximum value of gas emission.

7. The intelligent coal mine accident risk assessment method according to claim 4, characterized in that: In step S24, the weight w i The calculation formula is: Where s i1 is the importance of key location point i in mine safety production; a is the weight factor of the importance of key location point i in mine safety production; s i2 is the possibility of gas outburst at key location i; b is the weight factor of the possibility of gas outburst at key location i; s i3 is the hazard of gas outburst at key location i; c is the hazard weight factor of gas outburst at key location i; m is the number of key location i; w i is the weight of each key position point i.

8. The intelligent coal mine accident risk assessment method according to claim 5, characterized in that: In step S5, the specific process includes the following steps: S51, within a time period T, obtain ventilation volume data Q1, Q2, ..., Q at intervals t using a flow meter installed in the ventilation duct. n , according to the ventilation volume data Q1, Q2..., Q n Calculate the weighted average ventilation volume Q using the following formula: Where Q i is the ventilation volume data obtained at every time t; n is the number of ventilation volume data obtained; S52. Obtain theoretical ventilation volume Q l And the ventilation equipment performance correction coefficient η, combined with the weighted average ventilation volume Q to calculate the ventilation efficiency factor E, the formula is: Where E is the ventilation efficiency factor; η is the ventilation equipment performance correction factor; S53. Calculate the standard deviation O of the gas concentration based on the weighted average value M of the gas concentration. Calculate the gas concentration fluctuation coefficient C based on the weighted average value M of the gas concentration and the standard deviation O of the gas concentration. The formula is: Where C is the gas concentration fluctuation coefficient, M is the weighted average of gas concentration, and O is the standard deviation of gas concentration; S54. Calculate the gas outflow rate V based on the gas concentration fluctuation coefficient C, ventilation efficiency factor E, weighted average gas concentration M, and time period T. The formula is: Where Q is the weighted average ventilation volume; M is the weighted average gas concentration; T is the time period; δ is the dynamic balance factor of air pressure. is the temperature dynamic equilibrium factor.

9. The intelligent coal mine accident risk assessment method according to claim 6, characterized in that: In step S6, the specific process includes the following steps: S61, gas outburst rate V and mine internal temperature Perform normalization processing, where: For the gas outburst rate V, the normalized formula is: Where V norm is the normalized gas outburst rate; V max is the maximum value of the gas outburst rate; V min It is the maximum value of the gas outburst rate; The temperature inside the mine The normalization formula is: Where, is the normalized gas emission rate; It is the maximum value of the gas outburst rate; It is the maximum value of the gas outburst rate; S62. Determine the gas emission rate V and the internal temperature of the mine Weight values ​​x1, x2 in risk assessment; S63, according to the gas outburst rate V and the internal temperature of the mine The risk assessment model is constructed by combining the gas emission rate weight value x1 and the mine internal temperature weight value x2 to generate the risk assessment coefficient P, which is expressed as: Where x1 is the weight value of gas emission rate; x2 is the weight value of mine internal temperature; V norm is the normalized gas emission rate; is the normalized gas emission rate.

10. An intelligent coal mine accident risk assessment method according to claim 7, characterized in that: In step S62, the specific process includes the following steps: S621. Evaluate the gas emission rate V and the internal temperature of the mine based on historical risk accidents. The relative importance of gas emission rate and internal temperature of the mine to the severity of historical risk accidents is given. ij and a ji , the process is as follows: Obtain gas emission rate and internal mine temperature within a certain historical time range, as well as historical risk accident records; Obtain the severity of historical risk accidents based on historical risk accident records; Perform data cleaning and standardization on gas emission rate and internal temperature of mine within a certain historical time range; Calculate the Pearson correlation coefficient r between gas emission rate and internal mine temperature and the severity of historical risk accidents v and r T ; The formula is: Where x V is the gas emission rate within the historical time range, x T is the internal temperature of the mine within the historical time range, y is the severity of historical risk accidents, and n is the number of measurements within the historical time range; Obtain the Pearson correlation coefficient r between the gas emission rate and the internal temperature of the mine and the severity of historical risk accidents respectively v and r T The absolute value of r v |、|r T |, calculate the judgment value a of the relative importance of gas outburst rate and internal mine temperature to the severity of historical risk accidents based on absolute values ij and a ji , the calculation formula is: S622. The judgment value a of the relative importance of the severity of historical risk accidents based on the gas emission rate and the internal temperature of the mine. ij and a ji , construct the judgment matrix A as: S623, calculate the eigenvalues ​​and eigenvectors of the judgment matrix A, and obtain the maximum eigenvalue λ of the judgment matrix A max and its corresponding eigenvector x; S624. Divide each element in the eigenvector x by the sum of the elements of the eigenvector to obtain the gas emission rate weight value x1 and the mine internal temperature weight value x2.

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