A force-vibration zoning comprehensive rock burst monitoring and early warning method

Abstract

The application provides a force-vibration zoning comprehensive rock burst monitoring and early warning method, comprising the following steps: determining critical values and danger grades of static mechanics early warning indexes in a region 100 meters inside and outside a working face; performing weight distribution of the same static mechanics early warning indexes in the region 100 meters inside and outside the working face; determining vibration early warning indexes of an open-off cut and a solid coal roadway; dividing danger grades of the vibration early warning indexes; performing weight distribution of the vibration early warning indexes; evaluating a comprehensive danger grade of mine earthquake precursor indexes; determining a force-vibration zoning comprehensive danger coefficient according to the weight distribution of the static mechanics early warning indexes and the mine earthquake precursor indexes; and evaluating and preventing a countermeasure of the force-vibration zoning comprehensive danger grade. Through double-source disaster-causing mechanism modeling, zoning and grading dynamic early warning and a multi-source data fusion system, the application finally realizes accurate dynamic grading early warning of a rock burst danger grade.

Description

Technical Field

[0001] This invention relates to the technical field of coal mine rockburst monitoring and early warning, and in particular to a force-seismic zone integrated rockburst monitoring and early warning method. Background Technology

[0002] Rockbursts in coal mines are a common dynamic disaster during deep mining. Their occurrence mechanism is complex, and their hazards are extremely high, seriously threatening safe mine production. The formation of rockbursts is the result of the superposition of static stress (such as mining-induced stress and tectonic stress) and dynamic loads (such as mine tremors and fault slip). Traditional early warning methods often rely on single static or dynamic indicators, which are insufficient to comprehensively reflect the coupled dynamic-static load disaster-causing mechanism, leading to low accuracy and high false alarm rates. Furthermore, the surrounding rock mechanical properties and mine tremor responses differ significantly in different areas of the coal mine working face (such as accessible roadways and solid coal roadways). Existing early warning systems often use fixed thresholds and uniform weights, failing to achieve precise regional and hierarchical assessments, further limiting the effectiveness of early warning systems.

[0003] Existing technologies disclose an intelligent monitoring and early warning method and device for rockbursts based on multi-field, multi-source information fusion. By integrating stress, ground sound, support resistance, microseismic activity, and anchor bolt / anchor cable stress monitoring systems, and combining this with an early warning model constructed by a data processing center, accurate prediction and intelligent early warning of rockbursts are achieved, providing decision support for targeted prevention and control. Another method for rockburst early warning based on the charge induction characteristics of coal samples is also disclosed. This method determines the charge parameters (average charge and coefficient of variation) of the coal sample fracturing process in the laboratory, and establishes a charge critical coefficient model based on field measured data, achieving quantitative and accurate early warning of rockbursts in deep mines. This method features rapid determination of early warning thresholds and strong engineering applicability. Currently, rockburst early warning mainly faces the following problems:

[0004] 1. The synergistic effect of static and dynamic loads is not fully considered: Existing models are mostly based on a single factor of static or dynamic load, ignoring the dynamic superposition effect of the two, and are difficult to reflect the real disaster-causing process.

[0005] 2. Static thresholds and weights for indicators: The critical thresholds and weights of early warning indicators are usually fixed and are not dynamically adjusted according to the impact range of the action, resulting in insufficient adaptability of the early warning.

[0006] 3. Lack of regionally differentiated early warning: The surrounding rock mechanics and vibration response characteristics of tunnels near the ground and solid coal mine are different, but existing methods do not specifically distinguish the selection of indicators and weight allocation, which affects the accuracy of early warning.

[0007] 4. Difficulty in integrating multi-source indicators: The dimensions of static and dynamic indicators are not unified, and there is a lack of effective normalization processing and weight optimization methods, resulting in technical bottlenecks in the construction of comprehensive early warning models. Summary of the Invention

[0008] This invention aims to provide a force-seismic zone integrated rockburst monitoring and early warning method to address the problems of insufficient consideration of the dynamic and static load synergy mechanism, static index thresholds and weights, lack of regionally differentiated early warning, and difficulty in integrating multi-source indicators.

[0009] Therefore, the technical solution adopted by the present invention is: a method for monitoring and early warning of rockbursts by force-seismic zoning, comprising the following steps:

[0010] S1. Determine the critical values ​​and hazard levels of various static early warning indicators in the area 100 meters ahead of the working face;

[0011] S2. Perform weight allocation for similar static early warning indicators within and outside 100 meters ahead of the working face;

[0012] S3. Determine the vibration early warning indicators for open roadways and solid coal roadways;

[0013] S4. Classify the danger levels of each vibration early warning indicator;

[0014] S5. Perform weight allocation for each of the vibration early warning indicators;

[0015] S6. Establish a set of vibration early warning indicators for different zones, collectively referred to as mine earthquake precursor indicators, and evaluate the comprehensive hazard level of the mine earthquake precursor indicators.

[0016] S7. Determine the comprehensive hazard coefficient of the force-seismic zone based on the weight allocation of the static early warning index and the mine earthquake precursor index.

[0017] S8. Conduct a comprehensive assessment of the force-seismic zoning hazard level and develop prevention and control measures.

[0018] As a preferred embodiment of the above scheme, in step S1, the static early warning index includes stress value (σ) and stress growth rate (Δσ). The stress change law of the surrounding rock of the roadway in front of the working face is obtained in real time through the monitoring system. Due to the influence of the advance support pressure, the early warning value is different in different areas. The working face is divided into two areas with 100 meters ahead as the boundary, the critical value is determined and the hazard level is evaluated.

[0019] More preferably, the stress value has a weight of 0.7 within 100 meters ahead of the working surface and a weight of 0.3 beyond 100 meters ahead of the working surface; the stress increase has a weight of 0.7 within 100 meters ahead of the working surface and a weight of 0.3 beyond 100 meters ahead of the working surface.

[0020] More preferably, in step S3, due to the different complexity of the stress environment and the different damage mechanisms, the vibration early warning indicators of the open roadway include: b value, A(b) value, total fault area, seismic absence, algorithm complexity AC value, and mine seismic activity scale ΔF; the vibration early warning indicators of the solid coal roadway include: A(b) value, total fault area, algorithm complexity AC value, and mine seismic activity scale ΔF.

[0021] More preferably, in step S4, in order to quantitatively describe the abnormal level of each of the vibration early warning indicators, an exponential distribution function of reliability analysis theory is introduced, wherein the abnormality index W of each of the vibration early warning indicators is... ij The expression is:

[0022]

[0023] In the formula, e is the base of the natural logarithm. This represents the abnormal membership degree of each indicator within the statistical time window t, with a value range of 0 to 1;

[0024] By using the Gaussian membership function, the membership of each vibration warning indicator to different hazard levels can be further calculated. The hazard levels of the vibration warning indicators are divided according to the maximum membership probability. The hazard levels of the vibration warning indicators are: A. No hazard level, B. Slight hazard level, C. Medium hazard level, and D. Strong hazard level.

[0025] A further preferred embodiment involves calculating the probability that each vibration warning indicator belongs to a different hazard level using the Gaussian membership function, defining F... W F represents the probability that the vibration warning index belongs to the B-level (weak hazard) category. M F represents the probability of belonging to the medium risk level C. S The probability of belonging to the D strong hazard level is considered. The D strong hazard level warning is more important, followed by the C medium hazard level warning, and finally the B weak hazard level warning. Therefore, different weights need to be assigned to the three warning levels. The final comprehensive value F of the vibration warning index i is obtained through calculation. icom The formula is as follows:

[0026]

[0027] The weighting formula for the vibration early warning index i is as follows:

[0028]

[0029] In the formula, a i F represents the weight of the vibration early warning index i. icom This is the comprehensive value of the vibration early warning index i.

[0030] More preferably, the precursory index for mine tremors is W, for roadways near open ground, ,in Each represents the b-value, A(b)-value, total fault area A(t), seismic absence, algorithm complexity AC-value, and mine seismic activity scale ΔF; for solid coal roadways, ,in Each represents the value of A(b), the total fault area A(t), the algorithm complexity AC, and the seismic activity scale ΔF.

[0031] More preferably, in step S8, the danger level of rockburst is divided into 4 danger levels, and different prevention and control measures are required for rockbursts of different danger levels.

[0032] The beneficial effects of this invention are:

[0033] 1. Modeling of dual-source disaster-causing mechanism: Constructing a static early warning model (stress value, stress growth rate) and a vibration early warning index model (differentiated mine earthquake precursor index) respectively. By dynamically adjusting the threshold and weight, the risk quantification assessment under the combined action of dynamic and static loads is realized.

[0034] 2. Differentiated and tiered dynamic early warning system, based on the impact range of advanced mining and roadway type (near-hole / solid coal), with differentiated design of critical values ​​and weights for indicators.

[0035] 3. Multi-source data fusion system: Using normalization processing and multi-index fusion technology, a comprehensive early warning system for force-seismic zones is established to solve the problem of inconsistent dimensions and ultimately achieve accurate dynamic classification and early warning of rockburst hazard levels. Attached Figure Description

[0036] Figure 1 This is a system diagram of the force-seismic zoning comprehensive early warning index in this invention.

[0037] Figure 2 This is a flowchart of the early warning process for force-seismic zoned integrated rockburst in this invention. Detailed Implementation

[0038] The present invention will now be further described with reference to the accompanying drawings and embodiments.

[0039] like Figure 1-2 As shown, a method for monitoring and early warning of rockbursts by force-seismic zoning includes the following steps:

[0040] S1. Determine the critical values ​​and hazard levels of various static early warning indicators in the area 100 meters ahead of the working face.

[0041] In step S1, the static early warning indicators include stress value (σ) and stress increase rate (Δσ). The stress change pattern of the surrounding rock in the roadway ahead of the working face is obtained in real time through the monitoring system. Due to the influence of the advance support pressure, the early warning value is different in different areas. The working face is divided into two areas with 100 meters ahead as the boundary, and the critical value is determined for each area, and the hazard level is evaluated. As shown in Table 1, the principle for determining the critical value is as follows: real-time adjustment is made based on the data of the corresponding samples in the actual monitoring of the two areas. In Table 1, α1, b1, c1, and d1 are the average values ​​of the samples in the corresponding areas, α2, b2, c2, and d2 are the average value + 1 standard deviation, and α3, b3, c3, and d3 are the average value + 2 standard deviations.

[0042] Table 1 Evaluation Table of Static Early Warning Indicators for Rockburst

[0043]

[0044] S2. Assign weights to similar static early warning indicators within and outside the working face up to 100 meters ahead.

[0045] The stress value has a weight of 0.7 within 100 meters ahead of the working face and a weight of 0.3 beyond 100 meters ahead of the working face. The stress increase has a weight of 0.7 within 100 meters ahead of the working face and a weight of 0.3 beyond 100 meters ahead of the working face.

[0046] S3. Determine the vibration early warning indicators for both open roadways and solid coal roadways.

[0047] In step S3, due to the different complexity of the stress environment and the different damage mechanisms, the vibration early warning indicators for the open roadway include: b value, A(b) value, total fault area, seismic absence, algorithm complexity AC value, and mine seismic activity scale △F; the vibration early warning indicators for the solid coal roadway include: A(b) value, total fault area, algorithm complexity AC value, and mine seismic activity scale △F.

[0048] The b-value reflects the intensity of the vibration. A larger b-value indicates a higher proportion of low-energy earthquakes in the seismic event, and a lower probability of high-energy micro-seismic events. The calculation formula is as follows:

[0049] Equation (1)

[0050] In the formula, m is the total number of energy level divisions, and lgE i For the i-th energy level, N i This represents the actual number of microseismic events at the i-th energy level.

[0051] The A(b) value is a quantitative evaluation of seismic activity using two indicators: seismic energy and frequency. A higher A(b) value indicates a greater likelihood of a strong seismic event. The calculation formula is as follows:

[0052] Equation (2)

[0053] In the formula, b is the value of b in the statistical region, and M i Let N be the energy level of the i-th seismic event, and N be the total number of seismic events within the statistical time period and fixed area.

[0054] Total fault area: During coal mining, the number of low-energy seismic events is usually far greater than that of high-energy seismic events. The frequency of seismic events is determined by the frequency of low-energy events, but the total energy is determined by the intensity of high-energy events. The total fault area A(t) considers both the influence of low-energy events on the frequency and the influence of high-energy events on the total energy, thus resolving this contradiction. Theoretically, before a strong energy release, A(t) shows a high anomaly, indicating that microseismic activity is enhanced before the strong energy release. The calculation formula is as follows:

[0055] Equation (3)

[0056] In the formula, N(k) is the number of microseisms with energy level k within the time interval from time t to t+Δt, k0 is the lower limit of the counted microseisms, and k is the energy level of each microseismic event.

[0057] Seismic absence reflects a trend of missing energy levels in a certain area. Low-value anomalies generally appear before high-energy microseismic events. The calculation formula is as follows:

[0058] Equation (4)

[0059] In the formula, The average energy level over the statistical period. This is the initial energy level.

[0060] The AC value of algorithm complexity can be used to determine whether the evolution of a mine seismic event is a natural random fluctuation process or a chaotic process that satisfies certain characteristics. It can quantitatively characterize the instability of mine seismic events in time series changes. As shown in the following formula:

[0061] Equation (5)

[0062] In the formula, n represents the number of energy level changes within a certain time window, and M represents the total number of energy level classifications for the seismic event within a certain time window, and is M max -M min +1, M max M represents the maximum energy level of a mine seismic event within a certain time window. min This represents the minimum energy level of a mine seismic event within the same time window.

[0063] The seismic activity scale ΔF: By relating earthquake magnitude with the length L, width W, and displacement D of the rupture section, the correlation between the total stress on the earthquake rupture section and the earthquake magnitude is obtained, thus yielding the seismic activity scale ΔF, calculated as follows:

[0064] Equation (6)

[0065] In the formula, T represents the number of days, and M represents the seismic energy level.

[0066] S4. Classify the danger levels of each vibration early warning indicator.

[0067] In step S4, to quantitatively describe the abnormality level of each vibration early warning indicator, the exponential distribution function of reliability analysis theory is introduced, and the abnormality index W of each vibration early warning indicator is expressed. ij The expression is:

[0068] Equation (7)

[0069] In the formula, e is the base of the natural logarithm. This represents the abnormal membership degree of each indicator within the statistical time window t, with a value range of 0 to 1. Specifically... The calculations use a standardized method:

[0070] The positive anomaly indices A(b), A(t), seismic absence, algorithm complexity AC value, and mine seismic activity scale ΔF are expressed as follows:

[0071] Equation (8)

[0072] The negative anomaly indicator b value is represented as:

[0073] Equation (9)

[0074] In the formula, For indicator sequence values, The maximum value of the indicator sequence. It is the minimum value of the indicator sequence.

[0075] By using the Gaussian membership function, the membership of each vibration warning indicator to different hazard levels can be further calculated. The hazard levels of the vibration warning indicators are divided according to the maximum membership probability. The hazard levels of the vibration warning indicators are: A. No hazard level, B. Slight hazard level, C. Medium hazard level, and D. Strong hazard level.

[0076] A. No danger:

[0077] Equation (10)

[0078] B. Weak risk:

[0079] Equation (11)

[0080] C. Moderate risk:

[0081] Equation (12)

[0082] High Danger (D):

[0083] Equation (13)

[0084] In the formula, G(W) ij W is the membership probability of the comprehensive anomaly index. ij These are the abnormal indices of various vibration early warning indicators.

[0085] S5. Assign weights to each vibration early warning indicator.

[0086] The probability of each vibration warning indicator belonging to different hazard levels is calculated using the Gaussian membership function, and F is defined as follows: W F represents the probability that the vibration warning indicator belongs to the B-level (weak hazard) category. M F represents the probability of belonging to the medium risk level C. S Let F represent the probability of belonging to the D strong hazard level. The D strong hazard level warning is the most important, followed by the C medium hazard level warning, and finally the B weak hazard level warning. Therefore, different weights need to be assigned to the three warning levels, and the comprehensive value F of the vibration warning index i is finally calculated. icom The formula is as follows:

[0087] Equation (14)

[0088] The weighting formula for vibration early warning index i is as follows:

[0089] Equation (15)

[0090] In the formula, a i F represents the weight of vibration early warning index i. icom This is the comprehensive value of vibration early warning index i.

[0091] S6. Establish a set of earthquake early warning indicators for different zones, collectively referred to as mine earthquake precursor indicators, and assess the comprehensive hazard level of the mine earthquake precursor indicators.

[0092] The precursory indicator for mine earthquakes is W. For roadways with open access, ,in Each represents the b-value, A(b)-value, total fault area A(t), seismic absence, algorithm complexity AC-value, and mine seismic activity scale ΔF. For solid coal roadways, ,in Each represents the value of A(b), the total fault area A(t), the algorithm complexity AC, and the seismic activity scale ΔF.

[0093] Establish an impact hazard assessment vector V={v1, v2, v3, v4}, where v1=0.125, v2=0.375, v3=0.625, v4=0.875, and v1~v4 represent the numerical values ​​of hazard levels of none, weak, medium, and strong, respectively.

[0094] An evaluation matrix R (where m=6) is established to represent the membership degree of each vibration early warning indicator in the levels of no, weak, moderate, and strong. Matrix R contains... This represents the membership degree of the i-th vibration warning indicator in the j-th (1-4) hazard level of vector V. Calculated from equations (10) to (13), i.e. Equal to G(W) ij ).

[0095] Equation (16)

[0096] The weights of each vibration early warning index are calculated using equation (15), resulting in a weight vector. For an open roadway, the weight vector is:

[0097]

[0098] In the formula, ɑ 1~ ɑ6 represents the weights of b value, A(b) value, total fault area A(t), seismic absence, algorithm complexity AC value, and mine seismic activity scale ΔF, respectively.

[0099] For a solid coal roadway, the weight vector is:

[0100]

[0101] In the formula, ɑ 1~ ɑ4 represents the value of A(b), the total fault area A(t), the algorithm complexity AC, and the seismic activity scale ΔF, respectively.

[0102] Multiplying the indicator evaluation matrix by the indicator weight vector yields the fuzzy comprehensive evaluation vector:

[0103]

[0104] In the formula, b1 represents the sum of the products of the membership probability of the six indicators and their corresponding weights when the hazard level is A, i.e., the probability of belonging to hazard level A when all six indicators are considered. b2 represents the sum of the products of the membership probability of the six indicators and their corresponding weights when the hazard level is B, i.e., the probability of belonging to hazard level B when all six indicators are considered. b3 represents the sum of the products of the membership probability of the six indicators and their corresponding weights when the hazard level is C, i.e., the probability of belonging to hazard level C when all six indicators are considered. b4 represents the sum of the products of the membership probability of the six indicators and their corresponding weights when the hazard level is D, i.e., the probability of belonging to hazard level D when all six indicators are considered.

[0105] The Maximum Membership Principle (MMDP) and Variable Fuzzy Pattern Recognition (VFPR) are used to ensure the reliability and reasonableness of the results. To make the Maximum Membership Principle (MMDP) more effective, an index is introduced. Determine if the Maximum Membership Degree Principle (MMDP) is accurate:

[0106] Equation (17)

[0107] In the formula, , That is, the maximum probability in the fuzzy comprehensive evaluation vector B. That is, the second largest probability in the fuzzy comprehensive evaluation vector B. The following situations can be considered:

[0108] like If so, it means that the MMDP principle is completely valid;

[0109] like If so, it means that the MMDP principle is very effective;

[0110] like If so, it means that the MMDP principle is valid;

[0111] like If so, it means the MMDP principle is invalid;

[0112] like If the condition is met, it means that the MMDP principle is completely invalid.

[0113] Since invalid events exist in the feature values ​​of each warning level, variable fuzzy pattern recognition (VFPR) is used to supplement them, and a comprehensive MMDP-VFPR principle model is established:

[0114] Equation (18)

[0115] In the formula, v j This represents v1~v4 in the impact hazard assessment vector, b jLet b1~b4 represent the values ​​in the fuzzy comprehensive evaluation vector, and max{b j} represents the maximum value among b1~b4. Equation (18) indicates that V c When V is greater than or equal to 0.5 index =max{b j}. V c When V is less than 0.5, index =(b1v1+b2v2+b3v3+b4v4) / (b1+b2+b3+b4).

[0116] S7. Determine the comprehensive hazard coefficient of force-seismic zones based on the weight allocation of static early warning indicators and mine earthquake precursor indicators.

[0117] Determine the hazard level coefficients for each indicator. Let Vi (i=1, 2, 3, 4, 5) represent the hazard level coefficients for stress value (within 100 meters), stress value (outside 100 meters), stress rate increase (within 100 meters), stress rate increase (outside 100 meters), and mine earthquake precursor indicators, respectively. The Vi values ​​corresponding to each impact hazard level are: no hazard level Vi=0.125, weak hazard level Vi=0.375, moderate hazard level Vi=0.625, and strong hazard level Vi=0.875.

[0118] The assessment of stress value and stress rate increase hazard level includes two areas: inside and outside the working face (within 100 meters). The hazard level of the two areas needs to be assessed based on stress value and stress rate increase indicators. The weight of the area inside the working face (within 100 meters) is 0.7, and the weight of the area outside the working face (outside 100 meters) is 0.3.

[0119] Weighting of stress value (σ), stress rate increase (Δσ), and precursory indicators of mine tremors: Let Ai (i=1,2,3) represent the weights of stress value, stress rate increase, and precursory indicators of mine tremors, respectively. For roadways with access to the open, which are significantly affected by roof fracturing from adjacent working faces, the mine tremor parameters can be appropriately larger. For roadways with access to the open, A1=0.2, A2=0.2, and A3=0.6 are used. For roadways with solid coal seams, which are relatively less affected by dynamic load disturbances, smaller values ​​can be used. For roadways with solid coal seams, A1=0.3, A2=0.3, and A3=0.4 are used.

[0120] Determine the overall risk factor:

[0121]

[0122] S8. Conduct a comprehensive assessment of the force-seismic zoning hazard level and develop prevention and control measures.

[0123] In step S8, the danger level of rockburst is divided into 4 danger levels. Different prevention and control measures need to be taken for rockbursts of different danger levels, as shown in Table 2.

[0124] Table 2. Criteria for Early Warning and Countermeasures for Rockburst Hazards

[0125]

[0126] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for monitoring and early warning of rockbursts by force-seismic zoning, characterized in that, Includes the following steps: S1. Determine the critical values ​​and hazard levels of various static early warning indicators in the area 100 meters ahead of the working face; In step S1, the static early warning index includes stress value (σ) and stress increase rate (Δσ). The stress change law of the surrounding rock of the roadway in front of the working face is obtained in real time through the monitoring system. Due to the influence of the advance support pressure, the early warning value is different in different areas. The working face is divided into two areas with 100 meters ahead as the boundary, the critical value is determined and the hazard level is evaluated. S2. Assign weights to the same static early warning indicators within and outside 100 meters ahead of the working face; the stress value has a weight of 0.7 within 100 meters ahead of the working face and a weight of 0.3 outside 100 meters ahead of the working face; the stress increase has a weight of 0.7 within 100 meters ahead of the working face and a weight of 0.3 outside 100 meters ahead of the working face. S3. Determine the vibration early warning indicators for open roadways and solid coal roadways; S4. Classify the danger levels of each vibration early warning indicator; S5. Perform weight allocation for each of the vibration early warning indicators; S6. Establish a set of vibration early warning indicators for different zones, collectively referred to as mine earthquake precursor indicators, and evaluate the comprehensive hazard level of the mine earthquake precursor indicators. S7. Based on the weighting of the static early warning indicators and mine seismic precursor indicators, determine the comprehensive force-seismic zoning hazard coefficient: ； In the formula, The combined risk factor for force-seismic zoning, This is the stress value. For stress growth rate, The weighting of indicators for mine tremors. The stress value within 100 meters. The stress value is measured at a distance of 100 meters. The stress increase rate within 100 meters, The stress increase rate at a distance of 100 meters. The hazard level coefficient is the early warning indicator for mine tremors. S8. Conduct a comprehensive assessment of the force-seismic zoning hazard level and develop prevention and control measures.

2. The force and shock zoning integrated rock burst monitoring and early warning method according to claim 1, characterized in that: In step S3, due to the different complexity of the stress environment and the different damage mechanisms, the vibration early warning indicators of the open roadway include: b value, A(b) value, total fault area, seismic absence, algorithm complexity AC value, and mine seismic activity scale △F; the vibration early warning indicators of the solid coal roadway include: A(b) value, total fault area, algorithm complexity AC value, and mine seismic activity scale △F.

3. The force and shock zoning integrated rock burst monitoring and early warning method according to claim 1, characterized in that: In the step S4, in order to quantitatively describe the abnormal level of each of the vibration early warning indexes, an exponential distribution function of reliability analysis theory is introduced, and the abnormal index W of each of the vibration early warning indexes is calculated according to the following expression: ij The expression is: In the formula, e is the base of natural logarithm, represents the abnormal membership degree of each index in the statistical time window t, and the value range is 0~1; By using the Gaussian membership function, the membership of each vibration warning indicator to different hazard levels can be further calculated. The hazard levels of the vibration warning indicators are divided according to the maximum membership probability. The hazard levels of the vibration warning indicators are: A. No hazard level, B. Slight hazard level, C. Medium hazard level, and D. Strong hazard level.

4. The force and shock zoning integrated rock burst monitoring and early warning method according to claim 3, characterized in that: The probability that each vibration early warning index belongs to a different hazard level is calculated using the Gaussian membership function, and F is defined as follows. W F represents the probability that the vibration warning index belongs to the B-level (weak hazard) category. M F represents the probability of belonging to the medium risk level C. S The probability of belonging to the D strong hazard level is considered. The D strong hazard level warning is more important, followed by the C medium hazard level warning, and finally the B weak hazard level warning. Therefore, different weights need to be assigned to the three warning levels. Finally, the comprehensive value F of the vibration warning index i is calculated. icom The formula is as follows: The weighting formula for the vibration early warning index i is as follows: In the formula, a i F represents the weight of the vibration early warning index i. icom This is the comprehensive value of the vibration early warning index i.

5. The force and shock zoning integrated rock burst monitoring and early warning method according to claim 2, characterized in that: The precursory index for mine earthquakes is W. For roadways near open ground... ,in Each represents the b-value, A(b)-value, total fault area A(t), seismic absence, algorithm complexity AC-value, and mine seismic activity scale ΔF; for solid coal roadways, ,in Each represents the value of A(b), the total fault area A(t), the algorithm complexity AC, and the seismic activity scale ΔF.

6. The force and shock zoning integrated rock burst monitoring and early warning method according to claim 1, characterized in that: In step S8, the danger level of rockburst is divided into four danger levels, and different prevention and control measures are required for rockbursts of different danger levels.

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