A method for grading prediction of rock burst in coal mining area and application thereof

Abstract

The present application provides a kind of coal mining area rock burst grading prediction method, the method is aimed at the phenomenon that rock burst accident can occur in the process of coal mining in coal mining area, in combination with the index information of three aspects of conventional impact rock burst disaster prediction index N, microseismic impact rock burst index S and coal mining area impact rock burst index X, the weighted correlation degree of three aspects of index information is obtained by data processing and calculation, and the rock burst danger of each grid in the coal mining area to be mined is finally determined by the weighted correlation degree size.The present application method is applied to the rock burst prediction of sharp corner coal pillar influence area or large dip angle coal seam large mining height working face mining area, which can effectively predict the probability of coal mine rock burst, and the prediction method is scientific and reliable with high accuracy.

Description

Technical Field

[0001] This invention belongs to the field of coal mine rockburst hazard prediction, specifically involving a method for predicting rockburst grading in coal mining areas and its application, which is used to guide the prevention and control of coal mine rockburst hazards and safe production in coal mines. Background Technology

[0002] Currently, shallow coal resources are becoming increasingly depleted, and the frequency and intensity of coal and rock dynamic disasters such as rockbursts induced by deep mining are showing an increasing trend. Rockbursts are dynamic phenomena that cause sudden and violent destruction of the coal and rock mass surrounding the roadway or working face due to the instantaneous release of elastic deformation energy. Furthermore, due to unreasonable planning and mining practices in the early stages of coal resource development, the mining of many coal mine working faces is now constrained by geological and mining conditions such as irregular coal pillars, greatly increasing the risk of rockbursts.

[0003] Currently, coal mining areas face various working conditions, such as "sharp-angled coal pillars" and "high-dipping coal seams with large mining heights (coal seam dip angle ≥ 25° and working face mining height 3.5-7m)". Each working condition presents different specific problems, leading to variations in hazard prediction methods. Existing technologies include: Patent application number 202111542356.4 provides a microseismic prediction index and method for rockburst hazard; Patent application number 202010254926.9 provides a rockburst hazard prediction method for typical rockburst mines; and Patent application number 201910107736.1 provides a method for predicting the degree of rockburst hazard in coal mines. This method divides the structural diagram into several grid units; collects the first and second index information from each grid unit; calculates the structural dynamic stability index and disturbance intensity index for each grid unit; calculates the hazard index for each grid unit based on this; and classifies the network units according to a pre-established hazard level classification criterion, outputting the classification results for each network unit. All of the above patent applications pertain to methods for predicting the degree of rockburst risk in coal mines. They can effectively predict rockburst disasters in coal mines to a certain extent. However, given the various working conditions currently occurring in coal mining areas, they cannot effectively adapt to specific working conditions and provide prediction results that are more in line with reality.

[0004] For example, some coal mines have sharp-angled coal pillars formed between two or more working faces due to the oblique arrangement of the mining faces. The stress distribution of sharp-angled coal pillars is more complex than that of conventional coal pillars, and the risk of rockbursts in the areas affected by sharp-angled coal pillars is naturally greatly increased. Similarly, in the western mining areas of my country, there are large-angled coal seams with high mining heights (when the dip angle of the coal seam is greater than or equal to 25°, it is considered a large-angled coal seam, and when the single mining height of the coal seam is 3.5-7m, it is considered a high-mining face). The probability and intensity of rockbursts in large-angled coal seams with high mining heights are greater, and conventional rockburst prediction methods have certain limitations in evaluating their rockburst risk.

[0005] This invention proposes a method for predicting rockburst in stages, which is applicable to, but not limited to, the prediction of rockburst in the two common coal mining areas mentioned above. Summary of the Invention

[0006] To predict the hazards (including dangerous areas and degree of danger) of rockburst disasters in coal mining areas, this invention provides a method for classifying and predicting rockbursts in coal mining areas. This method addresses the possibility of rockburst accidents during coal mining and combines information from three aspects: a conventional indicator N affecting rockburst disaster prediction, an indicator S affecting rockbursts due to microseismic activity, and an indicator X affecting rockbursts in specific coal mining areas. The three indicators are processed and weighted correlations are calculated. The magnitude of the weighted correlation degree is used to determine the rockburst hazard of each grid in the coal mining area. This prediction method can effectively predict the probability of rockburst occurrence in coal mines.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: a method for predicting rockburst in coal mining areas, comprising the following steps:

[0008] Step 1: Create a structural schematic diagram of the area to be predicted, including a plan view and a cross-sectional view;

[0009] Step 2: Divide the area of ​​the coal mine working face where rockburst risk prediction is to be carried out into several small prediction unit grids;

[0010] The unit grid is a parallelogram, with a grid height equal to the width of the tunnel, and a grid length of 4m, 8m, or 12m.

[0011] Step 3: Establish a rockburst prediction index system, which specifically includes three aspects: conventional rockburst influence index N, microseismic rockburst influence index S, and mining area rockburst influence index X.

[0012] Step 4: Collect the specific values ​​of each sub-index of the conventional impact rockburst index N in the unit grid of the working face prediction area, and then determine the impact index corresponding to each sub-index. Sum the impact indices to obtain the conventional rockburst impact index in each grid.

[0013] The conventional index N affecting rockburst specifically includes the following six sub-indices: coal seam burial depth N1, fault drop height N2, coal seam rockburst tendency N3, roof rockburst tendency N4, degree of activity of hard roof N5, and maximum principal stress N6; the influence index corresponding to each sub-indicator is as follows:

[0014] (1) Rockburst impact index I determined by coal seam burial depth sub-index N1 N1

[0015] Coal seam burial depth is a commonly used indicator of rockburst influencing factors. Generally, the greater the coal seam burial depth, the greater the probability and intensity of rockburst. Therefore, when the coal seam burial depth is less than 400m, the influence index of rockburst occurrence is defined as I. N1 =1; When the coal seam burial depth is greater than or equal to 400m and less than 600m, the impact index of rockburst is determined to be I. N1 =2; When the coal seam burial depth is greater than or equal to 600m and less than 800m, the impact index of rockburst is determined to be I. N1 =3; When the coal seam burial depth is greater than or equal to 800m, the impact index of rockburst is determined to be I. N1 =4;

[0016] (2) The rockburst impact index I determined by the fault elevation height sub-index N2 N2

[0017] Encountering faults during coal mine working faces can induce rockburst accidents, and the magnitude of the rockburst is closely related to the fault displacement height. Therefore, when there is no fault influence, its impact index on rockburst is defined as 0; when the fault displacement height is greater than 0 and less than or equal to 3m, the impact index for rockburst is determined as I. N2 =1; When the fault drop height is greater than 3m and less than or equal to 10m, the impact index of rockburst is determined to be I. N2 =2; When the fault drop height is greater than 10m and less than or equal to 25m, the impact index of rockburst is determined to be I. N2 =3; When the fault drop height is greater than 25m, the impact index of rockburst is determined to be I. N2 =4;

[0018] (3) Rockburst Influence Index I determined by the coal seam rockburst tendency sub-index N3 N3

[0019] The rockburst tendency of a coal seam has a certain influence on the occurrence of rockbursts. The stronger the rockburst tendency, the more likely it is to induce rockburst hazards. Therefore, the rockburst influence index is determined using the rockburst tendency (obtained from sampling tests at the coal seam of the predicted coal mine working face) as follows: When the coal seam has "no rockburst tendency," the rockburst influence index is defined as I. N3 =0; when the coal seam has a "weak tendency to rockburst", the impact index for rockburst is determined to be I. N3 =1; When the coal seam has a "strong tendency to rockburst", the impact index for rockburst is determined to be I. N3 =3;

[0020] (4) The rockburst impact index I determined by the sub-index N4 of roof impact tendency N4

[0021] The impact tendency of the coal seam roof also has a certain influence on the occurrence of rockbursts. Therefore, the rockburst influence index is determined using the impact tendency of the coal seam roof strata (obtained from sampling and testing at the coal seam roof of the predicted coal mine working face) as follows: When the coal seam roof has "no impact tendency," the rockburst influence index is defined as I. N4 =0; When the coal seam roof has a "weak tendency to rockburst", the impact index for rockburst is determined to be I. N4 =1; When the coal seam roof has a "strong tendency to rockburst", the impact index for rockburst is determined to be I. N4 =3;

[0022] (5) Rockburst impact index I determined by the sub-index N5 of the degree of activity of the hard roof. N5

[0023] The hardness and activity of the coal seam roof are another key factor inducing rockburst disasters. Based on coal mining experience and expert research, the activity of the hard roof is jointly controlled by three factors: the hardness of the roof (uniaxial compressive strength of the hard rock strata), the distance between the hard roof and the coal seam, and the intensity of disturbance during coal seam mining. Based on the analysis of relevant data on the activity of hard roofs in multiple mining areas across the country, the coupling relationship between the coal seam hard roof activity index and the above three influencing factors is shown in Table 1.

[0024] Table 1. Coupling relationship between the hard roof activity index N5 and roof hardness, mining disturbance intensity, and distance between the hard roof and the coal seam.

[0025]

[0026] (6) Rockburst Influence Index I determined by the maximum principal stress sub-index N6 N6

[0027] Rockbursts are essentially a dynamic phenomenon involving the instantaneous release of stress or energy within coal and rock masses. Therefore, the maximum principal stress within the predicted grid unit of the working face is another crucial factor in determining its rockburst hazard. When the maximum principal stress is less than 10 MPa, the influence index for rockburst occurrence is defined as I. N6 =1; When the maximum principal stress is greater than or equal to 10 MPa and less than 15 MPa, the influence index of rockburst is determined to be I. N6 =2; When the maximum principal stress is greater than or equal to 15MPa and less than 20MPa, the influence index of rockburst is determined to be I. N6 =3; When the maximum principal stress is greater than 20 MPa, the influence index of rockburst is determined to be I. N6 =4;

[0028] Step 5: Collect the specific values ​​of each sub-index of the rockburst index S of the microseismic influence in the predicted area grid of the working face, and then determine the influence index corresponding to each sub-index. Sum the influence indices to obtain the rockburst influence index of the microseismic influence in each grid.

[0029] The microseismic impact index S specifically includes the following three sub-indices: the coupled impact index S1 of microseismic frequency, microseismic energy and mining speed, the amplitude S2 of the maximum microseismic event, and the peak vibration velocity S3 of the maximum microseismic event.

[0030] (1) The rockburst impact index I determined by the coupled sub-indices S1 of microseismic frequency, microseismic energy and mining speed. S1 In coal mining, microseismic activity and mining speed are also important factors affecting the risk of rockburst. Microseismic monitoring data includes the daily frequency and energy of microseismic activity. Based on the coupled influence of these two factors, the rockburst coupling influence index I is derived. S1 As shown in Table 2.

[0031] Table 2. Rockburst Influence Index Determined by Coupling of Microseismic Frequency, Microseismic Energy, and Mining Speed

[0032]

[0033] (2) The amplitude sub-index S2 of the maximum micro-seismic event determines the rockburst influence index I. S2

[0034] The amplitude of the maximum microseismic event is also an important factor reflecting the degree of rockburst hazard, which is the velocity variable in the microseismic signal waveform. When the amplitude of the maximum microseismic event is less than 0.2 mm / s, its corresponding rockburst influence index is defined as I. S2 =1; when the amplitude of the maximum microseismic event is greater than or equal to 0.2 mm / s and less than 0.4 mm / s, its corresponding rockburst influence index is determined to be I. S2 =2; When the amplitude of the maximum microseismic event is greater than or equal to 0.4 mm / s and less than 0.6 mm / s, its corresponding rockburst influence index is determined to be I. S2 =3; When the amplitude of the maximum microseismic event is greater than or equal to 0.6 mm / s, its corresponding rockburst influence index is determined to be I. S2 =4;

[0035] (3) Determine the rockburst influence index I by using the peak vibration velocity sub-index S3 of the maximum microseismic event. S3

[0036] The peak velocity of the largest microseismic event is also a significant factor influencing the occurrence of rockbursts; therefore, it can be used as an influence index for predicting rockburst hazard. The rockburst influence index is defined as I when the peak velocity is less than 0.5 m / s. S3 =1; When the peak velocity of the mass particles is greater than or equal to 0.5 m / s and less than 1 m / s, the corresponding impact index of rockburst is determined to be I. S3 =2; when the peak particle vibration velocity is greater than or equal to 1 m / s and less than 2 m / s, the corresponding rockburst influence index is determined to be I. S3 =3; When the peak particle vibration velocity is greater than or equal to 2 m / s, the corresponding rockburst influence index is determined to be I. S3 =4.

[0037] Step 6: Collect the specific parameter values ​​of each sub-indicator of the rockburst index X in the mining area within the predicted grid of the working face, and then determine the influence index corresponding to each sub-indicator parameter value. Sum the influence indices of each sub-indicator on rockburst to obtain the influence index of the mining area on rockburst in each predicted grid.

[0038] When the mining area is within the influence zone of a sharp-angled coal pillar, the specific impact index X of the mining area on rockburst is the impact index X of the sharp-angled coal pillar on rockburst. P Sharp-angled coal pillars affect the rockburst index X P Specifically, it includes the following four sub-indicators: the coupling influence index X of the angle of the sharp-angled coal pillar and the coal thickness of the sharp-angled coal pillar. P1 Sharp-angled coal pillar width X P2 Regularity of sharp-angled coal pillars X P3 and the moisture content of sharp-angled coal pillars XP4 :

[0039] (1) X, a coupled sub-index of sharp-angled coal pillar angle and coal thickness P1 Determined rockburst impact index I XP1

[0040] The angle of the sharp-angled coal pillar and the coal thickness are both important factors affecting the risk of rockburst. Different angles of the sharp-angled coal pillar during coal seam mining can lead to stress concentration and induce rockburst accidents. Combined with the influence of coal thickness, the rockburst influence index I under the coupled effects of these two factors is determined. XP1 As shown in Table 3.

[0041] Table 3. Coupling sub-index of sharp-angled coal pillar angle and coal thickness X P1 Determined rockburst impact index I XP1

[0042]

[0043] (2) Determination of coal pillar width sub-index X P2 Rockburst Impact Index I XP2

[0044] Coal pillar width is also one of the important factors affecting the risk of rockburst in coal mines. Based on mining experience and relevant theoretical analysis, the rockburst influence index can be determined as follows: Define coal pillar width (i.e. Figure 2 When the width of the coal pillar (as indicated) is greater than 0m and less than 5m, its corresponding rockburst influence index is determined to be I. XP2 =1; When the width of the coal pillar is greater than or equal to 5m and less than 25m, its corresponding rockburst influence index is determined to be I. XP2 =4; When the width of the coal pillar is greater than or equal to 25m and less than 40m, its corresponding rockburst influence index is determined to be I. XP2 =3; When the width of the coal pillar is greater than or equal to 40m and less than 60m, its corresponding rockburst influence index is determined to be I. XP2 =2;

[0045] (3) Sub-index of coal pillar regularity X P3 Determined rockburst impact index I XP3

[0046] The regularity of coal pillars is also a significant factor contributing to rockburst hazards. Based on field experience, coal pillar regularity can be categorized into four types: "regular," "relatively regular," "irregular," and "extremely irregular." Specifically, a coal pillar is considered "extremely irregular" when it is triangular, "irregular" when it is quadrilateral, "relatively regular" when it is pentagonal, and "regular" when it is hexagonal. When the regularity of a coal pillar is defined as "regular," the rockburst impact index is determined to be I.XP3 =0.5; when the regularity of the coal pillar is "relatively regular", the rockburst influence index is determined to be I. XP3 =1; When the regularity of the coal pillar is "irregular", the rockburst impact index is determined to be I. XP3 =2; When the regularity of the coal pillar is "extremely irregular", the rockburst impact index is determined to be I. XP3 =3;

[0047] (4) Sub-index of water content of coal pillar X P4 Determined rockburst impact index I XP4

[0048] The moisture content of coal pillars is also a crucial factor influencing the risk of rockburst. The moisture content of coal pillars in the predicted area (obtained from borehole tests within the predicted coal pillar grid) can be used to determine the rockburst influence index. A weak moisture content is defined as a coal pillar moisture content greater than or equal to 0 and less than 0.1 L / (s·m), and the rockburst influence index I is determined accordingly. XP4 =1; When the water content of the coal pillar is greater than or equal to 0.1 L / (s·m) and less than 1 L / (s·m), it is considered to have medium water content, and the rockburst influence index I is determined. XP4 =2; When the water content of the coal pillar is greater than or equal to 1 L / (s·m) and less than 5 L / (s·m), it is considered to have strong water content, and the rockburst influence index I is determined. XP4 =3; When the water content of the coal pillar is greater than 5 L / (s·m), it is considered extremely water-bearing, and the rockburst influence index I is determined. XP4 =4.

[0049] When the mining area is a steeply inclined coal seam with a high mining height, the specific impact of the mining area on rockburst index X is as follows: [Specific details regarding the impact of steeply inclined coal seam with high mining height on rockburst index X]. B Large-angle and high-extraction mining affects the rockburst index X. B Specifically, it includes: coal seam dip angle X B1 Thickness of coal seam with high mining height X B2 The degree of drastic change in coal seam thickness at high mining height X B3 X, depth of coal face spalling or blasting situation in high-mining coal seams B4 .

[0050] (1) Coal seam dip angle sub-index X B1 Determined rockburst impact index I XB1

[0051] The dip angle of a coal seam is the dominant factor inducing rockbursts in coal mines. Generally, a coal seam with a dip angle greater than or equal to 25° is considered a steeply dipped coal seam. Due to the special structure of steeply dipped coal seams, roof deformation and energy accumulation are easily induced during mining, leading to rockburst accidents. The larger the dip angle, the more likely rockbursts are to be induced during coal mine mining. This is determined by the sub-index X of the coal seam dip angle. B1 Determined rockburst impact index I XB1 As shown in Table 4:

[0052] Table 4. Coal Seam Dip Angle Sub-index X B1 Determined rockburst impact index I XB1

[0053] [25,35) 1.5 [35,45) 3 [45,55) 4.5 [55,65) 6 [65,75) 7.5 [75,90] 9

[0054] (2) Sub-index of coal seam thickness at steep inclination and high mining height X B2 Determined rockburst impact index I XB2

[0055] Thick coal seams with steep inclination and high mining height are a significant cause of rockburst hazards in coal mines. The thicker the coal seam, the more easily rockbursts are induced during mining operations. This is further explained by the sub-index X of thick coal seams with steep inclination and high mining height. B2 Determined rockburst impact index I XB2 As shown in Table 5:

[0056] Table 5 Sub-index of Coal Seam Thickness at High Mining Heights and Dipping Angles (X) B2 Determined rockburst impact index I XB2

[0057]

[0058]

[0059] (3) Sub-index X of the degree of drastic change in coal seam thickness at high mining height B3 Determined rockburst impact index I XB3

[0060] The degree of drastic variation in coal seam thickness at high mining heights is also a significant cause of rockburst hazards in coal mines. This is determined by the sub-index X representing the degree of drastic variation in coal seam thickness at high mining heights. B3 Determined rockburst impact index I XB3 As shown in Table 6:

[0061] Table 6 Sub-indicators of the drastic variation in coal seam thickness at high mining heights (X) B3 Determined rockburst impact index I XB3

[0062]

[0063] (4) Sub-index X of coal face spalling depth or blasting situation in high-mining coal face B4 Determined rockburst impact index I XB4

[0064] Coal wall spalling is also a significant factor reflecting the risk of rockburst at a coal mine working face. The depth of coal wall spalling can be used to describe its severity; the deeper the spalling, the greater the risk of rockburst. Rockburst blasting, caused by the instantaneous ejection of coal from the face due to stress and energy accumulation, poses the greatest risk of rockburst, with an established influence index of 4. The sub-index X represents the depth of coal wall spalling or the severity of rockburst blasting at the mining height. B4 Determined rockburst impact index I XB4 As shown in Table 7.

[0065] Table 7 Sub-indicators for Coal Wall Spalling Depth or Blasting Situation in High-Mining Coal Walls (X) B4 Determined rockburst impact index I XB4

[0066]

[0067] Step 7: Based on the above steps, collect the influence index of each sub-indicator of each indicator data in the prediction area on rockburst, that is, obtain the influence index of each indicator in each grid: Conventional Rockburst Influence Index I N Microseismic impact on rockburst index I S Impact of mining area on rockburst impact index I X ,in The influence index series of the three evaluation indicators for each grid is used as a comparison series, which is U. 网1 =(I N网1 I S网1 I X网1 ), U 网2 =(I N网2 I S网2 I X网2 ), ..., U 网n =(I N网n I S网n I X网n This facilitates data processing and calculation;

[0068] When the mining area is affected by a sharp-angled coal pillar, the impact index I of the mining area on rockburst is... X The impact index I of sharp-angled coal pillars on rockburst. XP Based on the impact index of each sub-indicator on rockburst based on the collected data of each indicator in the prediction area, the impact index of each indicator within each grid is obtained: Conventional Impact Rockburst Impact Index I N Microseismic impact on rockburst index I SThe impact of sharp-angled coal pillars on rockburst index I XP The influence index series of the three evaluation indicators for each grid is used as a comparison series to obtain the comparison series for each grid, which is U. 网1 =(I N网1 I S网1 I XP网1 ), U 网2 =(I N网2 I S网2 I XP网2 ), ..., U 网n =(I N网n I S网n I XP网n ).

[0069] When the mining area is a steeply inclined coal seam with a high mining height, the impact index I of the mining area on rockburst is... X The impact index I of large-angle and high-extraction mining on rockburst. XB Based on the impact index of each sub-indicator on rockburst based on the collected data of each indicator in the prediction area, the impact index of each indicator within each grid is obtained: Conventional Impact Rockburst Impact Index I N Microseismic impact on rockburst index I S Large-angle, high-extraction mining affects the rockburst index I. XB The influence index series of the three evaluation indicators for each grid is used as a comparison series to obtain the comparison series for each grid, which is U. 网1 =(I N网1 I S网1 I XB网1 ), U 网2 =(I N网2 I S网2 I XB网2 ), ..., U 网n =(I N网n I S网n I XB网n ).

[0070] Step 8: Assign weight values ​​δ to the three evaluation indicators. Based on the relevant values ​​of each indicator during previous rockburst events and field experience, the influence index I of conventional factors affecting rockbursts can be defined. N The influence index I of microseismic impact on rockburst S Impact Index I of Mining Area on Rockburst X The weights are as follows: That is, the weight sequence is δ = (0.305, 0.289, 0.406).

[0071] Step 9: Based on the varying intensity of rockburst disasters, the rockburst assessment level is divided into four levels. Based on this, a classification of rockburst hazard levels for each grid is established, defining the rockburst hazard level U = {U1, U2, U3, U4} to evaluate the rockburst hazard in the predicted area. U1 = (7, 3, 3), U2 = (9, 6, 7), U3 = (12, 9, 13), and U4 = (18, 13, 14) represent no rockburst hazard, weak rockburst hazard, moderate rockburst hazard, and strong rockburst hazard, respectively. U1, U2, U3, and U4 are reference sequences.

[0072] Step 10: To reduce the differences in the numerical values ​​of the indicators in the original data series, and to decrease its dispersion and data fluctuation amplitude, so as to make the data evaluation more accurate, the comparison series and reference series obtained in steps 7 and 9 are dimensionless processed using formulas (1)-(3). That is, the data to be processed is subjected to two weakening operator calculations and interval value transformations to obtain the dimensionless quantized comparison series u. 网1 u 网2 、…、u 网n And the reference sequence u1, u2, u3, u4:

[0073]

[0074] In the formula, U 1弱1 Let U1 be a buffered sequence after first-order weakening. 1弱1 (t) is the t-th element of the buffered sequence of sequence U1 after first-order weakening, where t = 1, 2, ..., n.

[0075]

[0076] In the formula, U 1弱2 For sequence U 1弱1 After the second-order weakened buffer sequence, U 1弱2 (t) is a sequence U 1弱1 The t-th element of the buffer sequence after second-order weakening, where t = 1, 2, ..., n;

[0077]

[0078] Step 11: Calculate the comparison sequences u after dimensionless quantization. 网1 u 网2 、…、u 网n By calculating the absolute differences between the values ​​and the reference sequences u1, u2, u3, and u4, the minimum and maximum absolute differences are obtained. The correlation coefficients for each grid are then calculated using these absolute differences and the formula.

[0079]

[0080] In equation (4): ξi (j) represents the comparison sequence u 网i The j-th element and the reference sequence u i The correlation coefficient of the j-th element; |u 网i (j)-u i (j)| is a sequence u i sum sequence u 网i The absolute difference at point j; min|u 网i (j)-u i (j)| is u i with u 网i The minimum absolute difference at points j = 1, 2, ..., n; max|u 网1 (j)-u i (j)| is u i with u 网i The maximum absolute difference at points j = 1, 2, ..., n; ρ is the resolution coefficient, which is generally taken as 0.5;

[0081] Step 12: Using the correlation coefficients of each grid obtained in Step 11, calculate the weighted correlation degree of each grid based on formula (5). The larger the weighted correlation degree, the closer it is to the corresponding rockburst hazard level. The rockburst hazard level of each grid is then determined. The rockburst hazard is verified using the drill cuttings method. The verification results indicate that the prediction result is highly accurate.

[0082]

[0083] In equation (5): γ i For reference sequence u i Compare the sequence u 网i The weighted correlation degree; δ(j) is the weight of each evaluation index.

[0084] An application of a method for predicting rockburst grading in coal mining areas, specifically for predicting the risk of rockburst grading in mining areas affected by sharp-angled coal pillars.

[0085] An application of a method for predicting rockburst risk in coal mining areas, specifically for predicting the risk of rockburst in steeply inclined coal seams with high mining height.

[0086] Compared with existing prediction methods, the prediction calculation principle of this invention is different. This invention determines the risk of rockburst by calculating weighted correlation degree and comparing magnitudes, which is more scientific. This invention takes into account three aspects of indicator information: conventional rockburst impact indicators, microseismic indicators, and mining area impact indicators. Based on this, it predicts the rockburst risk of specific mining areas, and the selection of indicator information is more targeted and specific.

[0087] The advantages of this invention are:

[0088] To address the issue that conventional rockburst prediction methods often lack accuracy in predicting rockburst in areas affected by sharp-angled coal pillars and in mining areas of steeply inclined coal seams with high mining heights, a new rockburst hazard prediction method applicable to both conditions has been invented. The new method features a more scientific and reasonable index system (considering the specific influences of each working condition while utilizing real-time data from microseismic monitoring), and its prediction principle is more scientific, reliable, and accurate. Attached Figure Description

[0089] Figure 1 This is a flowchart of the method of the present invention;

[0090] Figure 2 This is a schematic diagram of the 240m track roadway structure of the 14320 working face in a mine in Yanzhou mining area, Shandong Province, in an embodiment of the present invention.

[0091] Figure 3 This is a grid division diagram of the prediction unit for the 240m track roadway at the 14320 working face of a mine in Yanzhou Mining Area, Shandong Province, in an embodiment of the present invention.

[0092] Figure 4 This is a diagram showing the predicted rockburst hazard in the 240m track roadway of the 14320 working face of a mine in Yanzhou Mining Area, Shandong Province, according to an embodiment of the present invention.

[0093] Figure 5 This is a bar chart showing the powder discharge rate of boreholes 7-8m deep within each grid in this embodiment of the invention. Detailed Implementation

[0094] The technical solution of the present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings, such as... Figure 1 As shown, a method for predicting rockburst in coal mining areas includes the following steps:

[0095] Step 1: Create a structural diagram of the region to be predicted.

[0096] The structural schematic diagram of the area to be predicted can be created using software such as AutoCAD or 3D Max, clearly showing the basic structure of the coal mine working face. The area to be predicted is the 240m track roadway of the 14320 working face in a mine in the Yanzhou mining area of ​​Shandong Province. This track roadway, together with the goaf of the adjacent working face, forms two sharp-angled coal pillars, 1 and 2. These sharp-angled coal pillars are prone to stress concentration and stress imbalance, significantly impacting the stress concentration in the track roadway. Therefore, this mining area is affected by the sharp-angled coal pillars. Figure 2 The diagram shows the predicted structure of the 240m track roadway at the 14320 working face of a mine in Yanzhou Mining Area, Shandong Province.

[0097] Step 2: Divide the area of ​​the coal mine working face where rockburst risk prediction is to be carried out into parallelogram-shaped small prediction unit grids. The grid height is the width of the roadway, and the grid length can be 4m, 8m, or 12m, etc.

[0098] When dividing the prediction area of ​​a coal mine working face into prediction units, based on the experience of on-site inclined mining (the inclined angle of working face mining is generally around 15°), it can be divided into parallelogram small grid units with a length of 4m, 8m or 12m (12m is taken in this case). Correspondingly, the prediction area in the working face structure diagram is divided into several parallelogram grid units according to the corresponding proportion. Figure 3 The image shows the grid division diagram of the 240m track roadway prediction unit in the 14320 working face of a mine in Yanzhou Mining Area, Shandong Province.

[0099] Step 3: Establish a rockburst prediction index system, which includes three aspects: conventional rockburst index N, microseismic rockburst index S, and mining area rockburst index X.

[0100] (1) Conventional indicators of rockburst (N): Specifically, they include six sub-indicators: coal seam burial depth (N1), fault drop height (N2), coal seam rockburst tendency (N3), roof rockburst tendency (N4), hard roof activity degree (N5), and maximum principal stress (N6).

[0101] (2) Microseismic impact on rockburst index (S): Specifically includes three sub-indicators: microseismic frequency, microseismic energy and mining speed coupled impact index (S1), amplitude of the maximum microseismic event (S2) and peak vibration velocity of the maximum microseismic event (S3).

[0102] (3) The impact of the mining area on rockburst index X is the impact of the sharp-angled coal pillar on the rockburst index (X P Specifically, this includes the coupled influence index of the angle of the sharp-angled coal pillar and the coal thickness of the sharp-angled coal pillar (X). P1 ), width of the angular coal pillar (X) P2 ), regularity of sharp-angled coal pillars (X) P3 ) and the water content of the pointed coal pillar (X) P4 ), 4 sub-indicators.

[0103] Step 4: Collect the specific values ​​of each sub-index of the conventional impact rockburst index (N) within the unit grid of the working face prediction area, and then determine the impact index corresponding to each sub-index. Sum the impact indices to obtain the conventional rockburst impact index within each grid.

[0104] The specific values ​​of each sub-indicator of the conventional impact rockburst index in each grid were collected and determined. Table 8 shows the specific index data of the conventional impact rockburst index in the prediction grid, and Table 9 shows the impact index of the conventional impact rockburst index in the prediction grid.

[0105] Table 8. Specific data on common indicators affecting rockburst within grids 1 to 20.

[0106]

[0107] Table 9. Influence index of conventional factors affecting rockburst within grids 1 to 20.

[0108]

[0109]

[0110] Step 5: Collect the specific values ​​of each sub-index of the rockburst index (S) of the microseismic influence in the predicted area grid of the working face, and then determine the influence index corresponding to each sub-index. Sum the influence indices to obtain the influence index of the microseismic influence on rockburst in each grid.

[0111] The specific values ​​of each sub-indicator of the microseismic impact on rockburst index in each grid were collected and determined. Table 10 shows the specific index data of the microseismic impact on rockburst index in the prediction grid, and Table 11 shows the impact index of the microseismic impact on rockburst index in the prediction grid.

[0112] Table 10 Specific data on the impact of microseismic events on rockburst within grids 1 to 20

[0113]

[0114]

[0115] Table 11 Influence index of microseismic effects on rockburst within grids 1 to 20

[0116]

[0117] Step Six: Collect the specific parameter values ​​of each sub-indicator of the rockburst index X in the mining area within the predicted grid of the working face, and then determine the influence index corresponding to each sub-indicator parameter value. Sum the influence indices of each sub-indicator on rockburst to obtain the influence index of the mining area on rockburst in each predicted grid.

[0118] The specific values ​​of each sub-indicator and its influence index of the mining area affecting rockburst in each grid were collected and determined. Table 12 shows the specific index data of the mining area affecting rockburst in the prediction grid, and Table 13 shows the influence index of the mining area affecting rockburst in the prediction grid.

[0119] Table 12 Specific Indicators Affecting Rockburst in Mining Areas Within Grids 1 to 20

[0120]

[0121] Table 13 Impact Index of Mining Areas within Grids 1-20 on Rockburst

[0122]

[0123] Step 7: Based on the above steps, collect the influence index of each sub-indicator of each indicator data in the prediction area on rockburst, that is, obtain the influence index of each indicator in grid 1 to grid 20: I N I S I X ,in This yields the comparison sequence from grid 1 to grid 20, which are U 网1 =(14, 10, 12), U 网2 =(14, 10, 12), U 网3 =(14, 10, 12), U 网4 =(14, 10, 12), U 网5 =(14, 10, 12), U 网6 =(14, 10, 13), U 网7 =(14, 10, 13), U 网8 =(14, 10, 13), U 网9 =(14, 10, 13), U 网10 =(14, 12, 14), U 网11 =(14, 12, 14), U 网12 =(14, 12, 14), U 网13 =(14, 12, 14), U 网14 =(14, 12, 14), U 网15 =(17, 12, 13), U 网16 =(17, 12, 13), U 网17 =(14, 12, 13), U 网18 =(14, 12, 13), U 网19 =(14, 12, 13), U 网20 = (14, 12, 13). The influence index of each indicator in grid 1 to grid 20 is shown in Table 14.

[0124] Table 14 Influence Index of Each Indicator within Grid 1 to Grid 20

[0125]

[0126] Step 8: Assign weights to the three evaluation indicators.

[0127] Assigning weight values ​​δ to the three evaluation indicators, and based on the relevant values ​​of each indicator during previous rockburst events and field experience, the influence index I of conventional factors affecting rockburst can be defined. N The influence index I of microseismic impact on rockburst S Impact Index I of Mining Area on Rockburst X The weights are as follows: That is, the weight sequence is δ = (0.305, 0.289, 0.406).

[0128] Step 9: Establish a predictive grid classification of rockburst hazard levels.

[0129] Based on the varying intensity of rockburst disasters, rockburst assessment levels are divided into four levels. An original reference sequence U is defined to evaluate the rockburst hazard in the predicted area, i.e., U = {U1, U2, U3, U4}, where U1 = (7, 3, 3), U2 = (9, 6, 7), U3 = (12, 9, 13), and U4 = (18, 13, 14) represent no rockburst hazard, weak rockburst hazard, moderate rockburst hazard, and strong rockburst hazard, respectively, as shown in Table 15.

[0130] Table 15 Classification of Rockburst Hazard Levels

[0131]

[0132] Note: U1 = No rockburst hazard, U2 = Weak rockburst hazard, U3 = Moderate rockburst hazard, U4 = Strong rockburst hazard.

[0133] Step 10: Perform dimensionless processing on the reference sequence and the comparison sequence.

[0134] To reduce the differences in the numerical values ​​of the indicators in the original sequence, decrease its dispersion and data fluctuation, and make the data evaluation more accurate, the original reference sequence U1 is subjected to two weakening operator calculations, the calculation process of which is shown in formula (1) and formula (2). Then, interval value transformation is performed, the calculation process of which is shown in formula (3), resulting in u1 = (0.667, 0.333, 0.333). The calculation process of U2, U3 and U4 is the same as that of U1 (i.e., it is also processed according to formulas 1-3), and the calculation results are u2 = (0.185, 0.593, 0.407), u3 = (0.394, 0.212, 0.606), u4 = (0.467, 0.533, 0.067).

[0135] The comparison sequences can be quantized without a specific dimension, and the calculation process is the same as for U1 (i.e., processed according to formulas 1-3) to obtain the comparison sequence u. 网1 =(0.111, 0.444, 0.556), u 网2 =(0.111, 0.444, 0.556), u 网3 =(0.111, 0.444, 0.556), u 网4 =(0.111, 0.444, 0.556), u 网5 =(0.111, 0.444, 0.556), u 网6 =(0.309, 0.346, 0.654), u 网7 =(0.309, 0.346, 0.654), u 网8 =(0.309, 0.346, 0.654), u 网9 =(0.309, 0.346, 0.654), u 网10 =(0.367, 0.267, 0.633), u 网11 =(0.367, 0.267, 0.633), u 网12 =(0.367, 0.267, 0.633), u 网13 =(0.367, 0.267, 0.633), u 网14 =(0.367, 0.267, 0.633), u 网15 =(0.778, 0.889, 0.111), u 网16 =(0.778, 0.889, 0.111), u 网17 =(0.111, 0.444, 0.556), u 网18 =(0.111, 0.444, 0.556), u 网19 =(0.111, 0.444, 0.556), u 网20= (0.111, 0.444, 0.556).

[0136] Step 11: Calculate and compare the sequence u 网1 Correlation coefficient with reference series.

[0137] Calculate the comparison sequence u 网1 The absolute difference between the comparison sequence u1 and the reference sequence u1. Similarly, the comparison sequence u can also be obtained. 网1 The absolute differences between the values ​​and the reference sequences u2, u3, and u4 are used to calculate the correlation coefficient of grid 1 using the obtained absolute differences and formula (4). The calculation results are shown in Table 16.

[0138] Table 16. Grid 1 Association Coefficient Values

[0139]

[0140] Step 12: Calculate the weighted correlation degree of each grid and determine the rockburst hazard level of each grid based on the weighted correlation degree.

[0141] The reference sequence u1 and the comparison sequence u1 are calculated using equation (5). 网1 The weighted correlation values ​​of u2, u3 and u4 and the comparison sequence u 网1 The weighted correlation calculation process and u1 and u 网1 The calculations are the same, and the results are shown in Table 17.

[0142] Table 17 Weighted Association Degree of Grid 1

[0143] γ 0.746 0.765 0.756 0.516

[0144] Note: U1 = No rockburst hazard, U2 = Weak rockburst hazard, U3 = Moderate rockburst hazard, U4 = Strong rockburst hazard.

[0145] As can be seen from the table above, γ U2 >γ U3 >γ U1 >γ U4 Since the greater the weighted correlation, the closer it is to the corresponding rockburst hazard level, γ U2 If the value is the largest, then grid 1 can be determined to be at a low risk of rockburst. Similarly, the correlation coefficients and weighted correlation coefficients of the remaining grids can be calculated (i.e., processed according to formulas 4 and 5). The calculation results are shown in Table 18, which can be used to determine the rockburst hazard level in each grid.

[0146] Table 18 Weighted correlation coefficients of grids 1 to 20

[0147]

[0148]

[0149] As shown in Table 18, the rockburst hazard of each grid is shown in Table 19.

[0150] Table 19 Rockburst Hazard Levels for Grids 1-20

[0151]

[0152] Note: U1 = No rockburst hazard, U2 = Weak rockburst hazard, U3 = Moderate rockburst hazard, U4 = Strong rockburst hazard.

[0153] Table 19 shows the rockburst hazard of each grid. Figure 4 This is a prediction map of the rockburst hazard zone for the 240m track roadway in the 14320 working face. To verify the accuracy of this prediction method, the rockburst hazard was verified during mining using the drill cuttings method. Specifically, a borehole was drilled at the center of each grid, 1m above the ground, with a diameter of 42mm and a depth of 14m, and the amount of cuttings removed per meter of borehole was recorded. Figure 5 The bar chart shows the dust removal rate at a depth of 7-8m in each grid. It can be seen that grids 1-5 and 17-20 have relatively low dust removal rates, ranging from 5.8-6.3 kg / m, corresponding to a weak rockburst risk. Grids 6-14 have moderate dust removal rates, ranging from 6.9-7.5 kg / m, corresponding to a moderate rockburst risk. Grids 15-16 have the highest dust removal rates, ranging from 7.9-8.4 kg / m, corresponding to a strong rockburst risk. Based on these verification results, the accuracy of this method's predictions is considered high.

[0154] The scope of protection of this invention is not limited to the embodiments described above. Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its scope and spirit. If these modifications and variations fall within the scope of the claims of this invention and their equivalents, then the intent of this invention also includes these modifications and variations.

Claims

1. A method for predicting and classifying rockbursts in coal mining areas, characterized in that, Includes the following steps: Step 1: Establish a structural diagram of the region to be predicted; Step 2: Divide the area of ​​the coal mine working face where rockburst risk prediction is to be carried out into several small prediction unit grids; Step 3: Establish a rockburst prediction index system, which specifically includes three aspects: conventional rockburst influence index N, microseismic rockburst influence index S, and mining area rockburst influence index X. Step 4: Collect the specific values ​​of each sub-index of the conventional impact rockburst index N in the unit grid of the working face prediction area, and then determine the impact index corresponding to each sub-index. Sum the impact indices to obtain the conventional rockburst impact index in each grid. Step 5: Collect the specific values ​​of each sub-index of the rockburst index S of the microseismic impact on the predicted area grid of the working face, and then determine the impact index corresponding to each sub-index. Sum the impact indices to obtain the rockburst impact index of the microseismic impact on each grid. Step 6: Collect the specific parameter values ​​of each sub-indicator of the rockburst index X in the mining area within the predicted grid of the working face, and then determine the influence index corresponding to each sub-indicator parameter value. Sum the influence indices of each sub-indicator on rockburst to obtain the influence index of the mining area on rockburst in each predicted grid. Step 7: Based on the above steps, collect the influence index of each sub-indicator of each indicator data in the prediction area on rockburst, that is, obtain the influence index of each indicator in each grid: Conventional Rockburst Influence Index I N Microseismic impact on rockburst index I S Impact of mining area on rockburst impact index I X ,in The influence index series of the three evaluation indicators for each grid is used as a comparison series, which is U. 网1 =(I N网1 I S网1 I X网1 ), U 网2 =(I N网2 I S网2 I X网2 ), ..., U 网n =(I N网n I S网n I X网n ); Step 8: Assign weight values ​​to the three evaluation indicators, including the influence index I on conventional impacts of rockburst. N The weight is The influence index I of microseismic impact on rockburst S The weight is Impact Index I of Mining Area on Rockburst X The weight is Based on the relevant values ​​of various indicators during previous rockburst events and field experience, three weights were assigned values, resulting in a weighted series. The sum of the three weight values ​​is 1; Step 9: Based on the varying intensity of rockburst disasters, the rockburst assessment level is divided into four levels. Based on this, a rockburst hazard classification is established for each grid, defining the rockburst hazard level U = {U1, U2, U3, U4} to evaluate the rockburst hazard in the predicted area. U1, U2, U3, and U4 represent no rockburst hazard, weak rockburst hazard, moderate rockburst hazard, and strong rockburst hazard, respectively. Step 10: To reduce the differences in the numerical values ​​of the various indicators in the original data series, and to decrease its dispersion and data fluctuation amplitude, so as to make the data evaluation more accurate, the comparison series and reference series obtained in steps 7 and 9 are dimensionless processed using formulas (1)-(3). That is, the data to be processed is subjected to two weakening operator calculations and interval value transformations to obtain the dimensionless quantized comparison series u. 网1 u 网2 、…、u 网n And the reference sequence u1, u2, u3, u4: In equation (1), U 1弱1 Let U1 be a buffered sequence after first-order weakening. 1弱1 (t) is the t-th element of the buffered sequence of sequence U1 after first-order weakening, where t = 1, 2, ..., n; In the formula, U 1弱2 For sequence U 1弱1 After the second-order weakened buffer sequence, U 1弱2 (t) is a sequence U 1弱1 The t-th element of the buffer sequence after second-order weakening, where t = 1, 2, ..., n; Step 11: Calculate the comparison sequences u after dimensionless quantization. 网1 u 网2 、…、u 网n The absolute differences between the values ​​and the reference sequences u1, u2, u3, and u4 are used to derive the minimum and maximum absolute differences. The correlation coefficients of each grid are then calculated using the absolute differences and formula (4). In equation (4): ξ i (j) represents the comparison sequence u 网i The j-th element and the reference sequence u i The correlation coefficient of the j-th element; |u 网i (j)-u i (j)| is a sequence u i Sum of sequences u 网i The absolute difference at point j; min|u 网i (j)-u i (j)| is u i with u 网i The minimum absolute difference at points j = 1, 2, ..., n; max|u 网1 (j)-u i (j)| is u i with u 网i The maximum absolute difference at points j = 1, 2, ..., n; ρ is the resolution coefficient; Step 12: Using the correlation coefficients of each grid obtained in Step 11, calculate the weighted correlation degree of each grid based on formula (5). The larger the weighted correlation degree, the closer it is to the corresponding rockburst hazard level. Thus, the rockburst hazard level of each grid is determined. In equation (5): γ i For reference sequence u i Compare the sequence u 网i The weighted correlation degree; δ(j) is the weight of each evaluation index.

2. The method for predicting rockburst in coal mining areas as described in claim 1, characterized in that: The unit grid is a parallelogram, with a grid height equal to the width of the tunnel and a grid length of 4m, 8m, or 12m.

3. The method for predicting rockburst in coal mining areas as described in claim 1, characterized in that: The conventional rockburst influencing index N in step four specifically includes the following six sub-indices: coal seam burial depth N1, fault drop height N2, coal seam rockburst tendency N3, roof rockburst tendency N4, hard roof activity degree N5, and maximum principal stress N6; the influence index corresponding to each sub-indicator is as follows: 1) Rockburst Influence Index I determined based on coal seam burial depth sub-index N1 N1 ; When the coal seam burial depth is less than 400m, the impact index of rockburst is determined to be I. N1 =1; When the coal seam burial depth is greater than or equal to 400m and less than 600m, the impact index of rockburst is determined to be I. N1 =2; When the coal seam burial depth is greater than or equal to 600m and less than 800m, the impact index of rockburst is determined to be I. N1 =3; When the coal seam burial depth is greater than or equal to 800m, the impact index of rockburst is determined to be I. N1 =4; 2) Rockburst Influence Index I determined based on the fault elevation height sub-index N2 N2 ; When there is no fault influence, its influence index on rockburst is 0; when the fault drop height is greater than 0 and less than or equal to 3m, the influence index for rockburst is determined to be I. N2 =1; When the fault drop height is greater than 3m and less than or equal to 10m, the impact index of rockburst is determined to be I. N2 =2; When the fault drop height is greater than 10m and less than or equal to 25m, the impact index of rockburst is determined to be I. N2 =3; When the fault drop height is greater than 25m, the impact index of rockburst is determined to be I. N2 =4; 3) Rockburst Influence Index I determined based on coal seam rockburst tendency sub-index N3 N3 ; When the coal seam has a "no tendency to rockburst", the impact index for rockburst is determined as I. N3 =0; When the coal seam has a "weak tendency to rockburst", the impact index for rockburst is determined to be I. N3 =1; When the coal seam has a "strong tendency to rockburst", the impact index for rockburst is determined to be I. N3 =3; 4) Rockburst Influence Index I determined based on the roof impact tendency sub-index N4 N4 ; When the coal seam roof has a "no tendency to rockburst", the impact index for rockburst is determined as I. N4 =0; When the coal seam roof has a "weak tendency to rockburst", the impact index for rockburst is determined to be I. N4 =1; When the coal seam roof has a "strong tendency to rockburst", the impact index for rockburst is determined to be I. N4 =3; 5) Rockburst impact index I determined based on the hard roof activity sub-index N5. N5 ; The degree of activity of a hard roof is determined by three factors: the hardness of the roof, the distance between the hard roof and the coal seam, and the intensity of disturbance during coal seam mining. The rockburst influence index (I) is used to measure this degree of activity. N5 ; 6) Rockburst Influence Index I determined based on the maximum principal stress sub-index N6 N6 ; When the maximum principal stress is less than 10 MPa, the influence index of rockburst is determined as I. N6 =1; When the maximum principal stress is greater than or equal to 10 MPa and less than 15 MPa, the influence index of rockburst is determined to be I. N6 =2; When the maximum principal stress is greater than or equal to 15MPa and less than 20MPa, the influence index of rockburst is determined to be I. N6 =3; When the maximum principal stress is greater than 20 MPa, the influence index of rockburst is determined to be I. N6 =4.

4. The method for predicting rockburst in coal mining areas as described in claim 1, characterized in that: The microseismic impact index S on rockburst in step five specifically includes the following three sub-indices: the coupled impact index S1 of microseismic frequency, microseismic energy, and mining speed; the amplitude S2 of the maximum microseismic event; and the peak particle velocity S3 of the maximum microseismic event. The influence indexes corresponding to each sub-indicator are as follows: 1) Determine the rockburst influence index I based on the coupling of microseismic frequency, microseismic energy, and mining speed. S1 ; 2) Determine the rockburst influence index I based on the amplitude sub-index S2 of the maximum microseismic event. S2 ; When the amplitude of the maximum microseismic event is less than 0.2 mm / s, its corresponding rockburst influence index is determined to be I. S2 =1; when the amplitude of the maximum microseismic event is greater than or equal to 0.2 mm / s and less than 0.4 mm / s, its corresponding rockburst influence index is determined to be I. S2 =2; When the amplitude of the maximum microseismic event is greater than or equal to 0.4 mm / s and less than 0.6 mm / s, its corresponding rockburst influence index is determined to be I. S2 =3; When the amplitude of the maximum microseismic event is greater than or equal to 0.6 mm / s, its corresponding rockburst influence index is determined to be I. S2 =4; 3) Determine the rockburst influence index I based on the peak velocity sub-index S3 of the maximum microseismic event. S3 ; When the peak particle vibration velocity is less than 0.5 m / s, the corresponding rockburst influence index is determined to be I. S3 =1; When the peak velocity of the mass particles is greater than or equal to 0.5 m / s and less than 1 m / s, the corresponding impact index of rockburst is determined to be I. S3 =2; when the peak particle vibration velocity is greater than or equal to 1 m / s and less than 2 m / s, the corresponding rockburst influence index is determined to be I. S3 =3; When the peak particle velocity is greater than or equal to 2 m / s, the corresponding rockburst influence index is determined to be I. S3 =4.

5. The method for predicting rockburst in coal mining areas as described in claim 1, characterized in that: In step six, when the mining area is affected by a sharp-angled coal pillar, the rockburst index X of the mining area is specifically the rockburst index X of the sharp-angled coal pillar. P Sharp-angled coal pillars affect the rockburst index X P Specifically, it includes the following four sub-indicators: the coupling influence index X of the angle of the sharp-angled coal pillar and the coal thickness of the sharp-angled coal pillar. P1 Sharp-angled coal pillar width X P2 Regularity of sharp-angled coal pillars X P3 and the moisture content of sharp-angled coal pillars X P4 The influence indices corresponding to each sub-indicator are as follows: 1) Based on the coupled sub-index X of sharp-angle coal pillar angle and coal thickness P1 Determine the impact index I of rockburst XP1 ; 2) Based on the coal pillar width sub-index X P2 Determine the impact index I of rockburst XP2 ; When the width of the coal pillar is greater than 0m and less than 5m, its corresponding rockburst influence index is determined to be I. XP2 =1; When the width of the coal pillar is greater than or equal to 5m and less than 25m, its corresponding rockburst influence index is determined to be I. XP2 =4; When the width of the coal pillar is greater than or equal to 25m and less than 40m, its corresponding rockburst influence index is determined to be I. XP2 =3; when the width of the coal pillar is greater than or equal to 40m and less than 60m, its corresponding rockburst influence index is determined to be I. XP2 =2; 3) Based on the coal pillar regularity sub-index X P3 Determined rockburst impact index I XP3 ; When the coal pillar is triangular, it is "extremely irregular"; when it is quadrilateral, it is "irregular"; when it is pentagonal, it is "relatively regular"; when it is hexagonal, it is "regular"; and when the regularity of the coal pillar is "regular," the rockburst influence index is determined to be I. XP3 =0.5; when the regularity of the coal pillar is "relatively regular", the rockburst influence index is determined to be I. XP3 =1; When the regularity of the coal pillar is "irregular", the rockburst influence index is determined to be I. XP3 =2; When the regularity of the coal pillar is "extremely irregular", the rockburst influence index is determined to be I. XP3 =3; 4) Based on the coal pillar moisture content sub-index X P4 Determine the impact index I of rockburst XP4 ; When the water content of a coal pillar is greater than or equal to 0 and less than 0.1 L / (s·m), it is considered weakly water-bearing, and the rockburst influence index I is determined accordingly. XP4 =1; When the water content of the coal pillar is greater than or equal to 0.1 L / (s·m) and less than 1 L / (s·m), it is considered to have medium water content, and the rockburst influence index I is determined. XP4 =2; When the water content of the coal pillar is greater than or equal to 1 L / (s·m) and less than 5 L / (s·m), it is considered to have strong water content, and the rockburst influence index I is determined. XP4 =3; When the water content of the coal pillar is greater than 5 L / (s·m), it is considered extremely water-bearing, and the rockburst influence index I is determined. XP4 =4.

6. The method for predicting rockburst in coal mining areas as described in claim 1, characterized in that: In step six, when the mining area is a steeply inclined coal seam with a high mining height, the rockburst index X of the mining area specifically refers to the rockburst index X of steeply inclined coal seam with a high mining height. B Large-angle and high-extraction mining affects the rockburst index X. B Specifically, it includes: coal seam dip angle X B1 Thickness of coal seam with high mining height X B2 The degree of drastic change in coal seam thickness at high mining height X B3 X, depth of coal face spalling or blasting situation in high-mining coal seams B4 The influence indices corresponding to each sub-indicator are as follows: 1) Based on the coal seam dip angle sub-index X B1 Determined rockburst impact index I XB1 ; A coal seam with a dip angle greater than or equal to 25° is considered a steeply dipped coal seam. When the dip angle is between [25°, 35°), the rockburst influence index I is determined accordingly. XB1 The value is 1.5; when the coal seam dip angle is between [35, 45)°, the rockburst influence index I is determined by it. XB1 The value is 3; when the coal seam dip angle is between [45, 55)°, the rockburst influence index I determined by it is 3. XB1 The value is 4.5; when the coal seam dip angle is between [55, 65)°, the rockburst influence index I determined by it is 4.

5. XB1 The value is 6; when the coal seam dip angle is between [65, 75)°, the rockburst influence index I determined by it is 6. XB1 The value is 7.5; when the coal seam dip angle is between [75, 90)°, the rockburst influence index I is determined by it. XB1 It is 9; 2) Based on the sub-index X of coal seam thickness at large dip angles and high mining heights B2 Determined rockburst impact index I XB2 ; When the thickness of a coal seam with a steep dip angle and high mining height is less than 3.5m, its corresponding rockburst influence index I XB2 =0; When the thickness of a coal seam with a steep dip angle and high mining height is between [3.5, 4.5) m, its corresponding rockburst influence index I is 0. XB2 =1; When the thickness of a coal seam with a steep dip angle and high mining height is between [4.5, 6) m, its corresponding rockburst influence index I is 1. XB2 =2; When the thickness of a coal seam with a steep dip angle and high mining height is between [6,7)m, its corresponding rockburst influence index I XB2 =3; 3) Based on the sub-index X of the drastic change in coal seam thickness at high mining height B3 Determined rockburst impact index I XB3 ; When the variation in coal seam thickness at high mining height is not drastic, the determined rockburst impact index I is... XB3 =1; When the thickness variation of a high-mining coal seam is moderately drastic, its determined rockburst influence index I is 1. XB3 =2; When the thickness of the coal seam with high mining height changes drastically, its determined rockburst influence index I is 2. XB3 =3; 4) Sub-index X based on the depth of coal wall spalling or the situation of coal wall blasting in high mining heights B4 Determined rockburst impact index I XB4 ; When the depth of rockfall in a high-mining coal face is less than 0.5m, the determined rockburst influence index I is... XB4 =1; When the depth of rockfall in a high-mining coal wall is greater than or equal to 0.5m but less than 1m, the determined rockburst influence index I is... XB4 =2; When the depth of rockfall in a high-mining coal wall is greater than or equal to 1m, its determined rockburst influence index I XB4 =3; When a blowout occurs, its determined impact index is I. XB4 =4.

7. The method for predicting rockburst in coal mining areas as described in claim 1, characterized in that: In step seven, when the mining area is affected by a sharp-angled coal pillar, the impact index I of the mining area on rockburst is... X The impact index I of sharp-angled coal pillars on rockburst. XP Based on the impact index of each sub-indicator on rockburst based on the collected data of various indicators in the prediction area, the impact index of each indicator within each grid is obtained: Conventional Impact Rockburst Impact Index I N Microseismic impact on rockburst index I S The impact of sharp-angled coal pillars on rockburst index I XP The influence index series of the three evaluation indicators for each grid is used as a comparison series to obtain the comparison series for each grid, which is U. 网1 =(I N网1 I S网1 I XP网1 ), U 网2 =(I N网2 I S网2 I XP网2 ), ..., U 网n =(I N网n I S网n I XP网n ).

8. The method for predicting and classifying rockbursts in coal mining areas as described in claim 1, characterized in that: In step seven, when the mining area is a steeply inclined coal seam with a high mining height, the impact index I on rockburst in the mining area is... X The impact index I of large-angle and high-extraction mining on rockburst. XB Based on the impact index of each sub-indicator on rockburst based on the collected data of various indicators in the prediction area, the impact index of each indicator within each grid is obtained: Conventional Impact Rockburst Impact Index I N Microseismic impact on rockburst index I S Large-angle, high-extraction mining affects the rockburst index I. XB The influence index series of the three evaluation indicators for each grid is used as a comparison series to obtain the comparison series for each grid, which is U. 网1 =(I N网1 I S网1 I XB网1 ), U 网2 =(I N网2 I S网2 I XB网2 ), ..., U 网n =(I N网n I S网n I XB网n ).

9. The application of the method for predicting rockburst classification in coal mining areas as described in any one of claims 1-8, characterized in that: Specifically, it is used for the classification and prediction of rockburst risk in mining areas affected by sharp-angled coal pillars.

10. The application of the method for predicting rockburst classification in coal mining areas as described in any one of claims 1-8, characterized in that: Specifically, it is used for the classification and prediction of rockburst risk in steeply inclined coal seam mining faces with high mining height.

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