Method and device for classifying rock burst
By collecting target parameters from coal mine monitoring areas and determining the values of influencing factors, quantitative analysis methods were used to solve the problem that rockburst classification relied on subjective judgment by experts, achieving higher classification accuracy and reducing classification difficulty.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA COAL RES INST
- Filing Date
- 2022-08-24
- Publication Date
- 2026-07-10
AI Technical Summary
The classification of rockbursts in the current technology relies on the subjective judgment and experience of experts. The classification criteria are complex, difficult, and have low accuracy.
By collecting target parameters in the coal mine monitoring area, the values of influencing factors are determined. Based on the values of these influencing factors, rockbursts are classified. Quantitative analysis methods are used to reduce the difficulty of classification and improve accuracy.
It enables quantitative classification of rockbursts, reduces the difficulty of classification, improves the accuracy of classification, and can more accurately identify rockburst types.
Smart Images
Figure CN115409101B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of coal mining technology, and in particular to a method and apparatus for classifying rockbursts. Background Technology
[0002] Rockburst, also known as rock burst, refers to the sudden and destructive phenomenon that occurs in exposed rock masses at depths during underground mining or in areas with high tectonic stress. Rockburst is one of the major safety hazards faced by coal mines. Currently, the classification of rockburst largely relies on the subjective judgment and experience of experts, and the classification standards are quite complex, making classification difficult. Summary of the Invention
[0003] The present invention aims to at least partially solve one of the technical problems in the above-mentioned technologies.
[0004] Therefore, one objective of this invention is to propose a classification method for rockbursts, which can determine the values of influencing factors based on the values of target parameters, and then determine the target category of rockbursts based on the values of influencing factors. This method can achieve rockburst classification based on quantitative analysis, reducing the difficulty of rockburst classification and helping to improve the accuracy of rockburst classification.
[0005] The second objective of this invention is to provide a classification device for rockbursts.
[0006] The third objective of this invention is to provide an electronic device.
[0007] The fourth objective of this invention is to provide a computer-readable storage medium.
[0008] The first aspect of this invention proposes a method for classifying rockbursts, which involves collecting the values of target parameters within a monitoring area of a coal mine; determining the values of influencing factors affecting rockburst classification based on the values of the target parameters; and determining the target category of rockbursts within the monitoring area based on the values of the influencing factors.
[0009] According to the rockburst classification method of this invention, the values of target parameters within the monitoring area of a coal mine are collected. Based on the values of the target parameters, the values of influencing factors affecting rockburst classification are determined. Based on the values of the influencing factors, the target category of rockburst within the monitoring area is determined. Therefore, the values of influencing factors can be determined based on the values of target parameters, and then the target category of rockburst can be determined based on the values of the influencing factors. Rockburst classification can be achieved through quantitative analysis, reducing the difficulty of rockburst classification and helping to improve the accuracy of rockburst classification.
[0010] In addition, the classification method for rockbursts proposed in the above embodiments of the present invention may also have the following additional technical features:
[0011] In one embodiment of the present invention, determining the target category of rockburst within the monitoring area based on the values of the influencing factors includes: determining the value of a category index of a predetermined category of rockburst within the monitoring area based on the values of the influencing factors; and determining the target category from the predetermined categories based on the value of the category index.
[0012] In one embodiment of the present invention, determining the category index of a set category of rockburst in the monitoring area based on the values of the influencing factors includes: determining the subordinate influencing factors belonging to the category index from the influencing factors; obtaining a first sum of the values of the subordinate influencing factors and a second sum of the upper limit values of the subordinate influencing factors; and determining the ratio of the first sum to the second sum as the value of the category index.
[0013] In one embodiment of the present invention, determining the target category from the set categories based on the value of the category index includes: determining the set category corresponding to the largest category index as the target category.
[0014] In one embodiment of the present invention, determining the target category from the set categories based on the value of the category index includes: sorting the values of the category index from largest to smallest; identifying that among the values of the top n target category indices, the difference between any two target category indices is less than or equal to a set threshold, and determining the set category corresponding to each target category index as the target category, where n is a positive integer greater than 1.
[0015] In one embodiment of the present invention, the defined categories include gravity-type rockburst, structural rockburst, roof-type rockburst, and coal pillar-type rockburst.
[0016] In one embodiment of the present invention, determining the values of influencing factors affecting rockburst classification based on the values of the target parameters includes: determining the subordinate target parameters belonging to the influencing factors from the target parameters; and determining the values of the influencing factors based on the values of the subordinate target parameters.
[0017] In one embodiment of the present invention, determining the values of influencing factors affecting rockburst classification based on the values of the target parameter includes: identifying the target parameter value within a target set range; and obtaining the value of the influencing factor based on the mapping relationship between the target set range and the values of the influencing factor.
[0018] In one embodiment of the present invention, the method further includes: obtaining engineering measures corresponding to the target category; and executing the engineering measures within the monitoring area.
[0019] A second aspect of the present invention provides a classification device for rockbursts, comprising: a data acquisition module for acquiring the values of target parameters within a monitoring area of a coal mine; a first determination module for determining the values of influencing factors affecting rockburst classification based on the values of the target parameters; and a second determination module for determining the target category of rockbursts within the monitoring area based on the values of the influencing factors.
[0020] The rockburst classification device of this invention collects the values of target parameters within a monitoring area of a coal mine. Based on the values of the target parameters, it determines the values of influencing factors affecting rockburst classification, and based on the values of these influencing factors, it determines the target category of rockbursts within the monitoring area. Therefore, the values of influencing factors can be determined based on the values of the target parameters, and then the target category of rockbursts can be determined based on the values of these influencing factors. This allows for rockburst classification based on quantitative analysis, reducing the difficulty of rockburst classification and helping to improve its accuracy.
[0021] In addition, the rockburst classification device proposed in the above embodiments of the present invention may also have the following additional technical features:
[0022] In one embodiment of the present invention, the second determining module is further configured to: determine the value of the category index of the set category of rockburst in the monitoring area based on the value of the influencing factor; and determine the target category from the set category based on the value of the category index.
[0023] In one embodiment of the present invention, the second determining module is further configured to: determine the subordinate influencing factors belonging to the category index from the influencing factors; obtain a first sum of the values of the subordinate influencing factors and a second sum of the upper limit values of the subordinate influencing factors; and determine the ratio of the first sum to the second sum as the value of the category index.
[0024] In one embodiment of the present invention, the second determining module is further configured to: determine the set category corresponding to the maximum category index as the target category.
[0025] In one embodiment of the present invention, the second determining module is further configured to: sort the values of the category indices from largest to smallest; identify that among the values of the top n target category indices, the difference between any two target category indices is less than or equal to a set threshold, and determine the set category corresponding to each target category index as the target category, wherein n is a positive integer greater than 1.
[0026] In one embodiment of the present invention, the defined categories include gravity-type rockburst, structural rockburst, roof-type rockburst, and coal pillar-type rockburst.
[0027] In one embodiment of the present invention, the first determining module is further configured to: determine the membership target parameter belonging to the influencing factor from the target parameters; and determine the value of the influencing factor based on the value of the membership target parameter.
[0028] In one embodiment of the present invention, the first determining module is further configured to: identify the target parameter value within a target setting range; and obtain the value of the influencing factor based on the mapping relationship between the target setting range and the value of the influencing factor.
[0029] In one embodiment of the present invention, it further includes an execution module, which is configured to: obtain engineering measures corresponding to the target category; and execute the engineering measures within the monitoring area.
[0030] A third aspect of the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the method for classifying rockbursts as described in the first aspect of the present invention.
[0031] The electronic device of this invention executes a computer program stored in a memory via a processor to collect the values of target parameters within the monitoring area of a coal mine. Based on the values of the target parameters, it determines the values of influencing factors affecting rockburst classification, and based on the values of these influencing factors, it determines the target category of rockburst within the monitoring area. Thus, the values of influencing factors can be determined based on the values of the target parameters, and subsequently, the target category of rockburst can be determined based on these influencing factors. This allows for rockburst classification based on quantitative analysis, reducing the difficulty of rockburst classification and contributing to improved accuracy.
[0032] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for classifying rockbursts as described in the first aspect of this invention.
[0033] The computer-readable storage medium of this invention stores a computer program, which is executed by a processor, to collect the values of target parameters within a monitoring area of a coal mine. Based on the values of the target parameters, it determines the values of influencing factors affecting rockburst classification, and based on the values of these influencing factors, determines the target category of rockburst within the monitoring area. Therefore, the values of influencing factors can be determined based on the values of the target parameters, and then the target category of rockburst can be determined based on these influencing factors. This allows for rockburst classification based on quantitative analysis, reducing the difficulty of rockburst classification and contributing to improved accuracy.
[0034] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description
[0035] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:
[0036] Figure 1 This is a flowchart illustrating a method for classifying rockbursts according to an embodiment of the present invention.
[0037] Figure 2 This is a flowchart illustrating a method for classifying rockbursts according to another embodiment of the present invention;
[0038] Figure 3 This is a flowchart illustrating a method for classifying rockbursts according to another embodiment of the present invention;
[0039] Figure 4 This is a schematic diagram of a rockburst classification device according to an embodiment of the present invention;
[0040] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation
[0041] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0042] The following description, in conjunction with the accompanying drawings, outlines the classification method, apparatus, electronic device, and storage medium for rockbursts according to embodiments of the present invention.
[0043] Figure 1 This is a flowchart illustrating a method for classifying rockbursts according to an embodiment of the present invention.
[0044] like Figure 1 As shown, the classification method for rockbursts according to an embodiment of the present invention includes:
[0045] S101, Collect the values of target parameters within the monitoring area of the coal mine.
[0046] It should be noted that there are no restrictions on the monitoring area or target parameters. For example, there can be at least one monitoring area or target parameter.
[0047] In one implementation, the monitoring area includes, but is not limited to, underground roadways, longwall faces, rest and / or office areas for underground personnel, and areas where mining equipment is located, wherein the mining equipment includes coal mining machines.
[0048] In one implementation, the target parameters include, but are not limited to, mining depth h1, coal seam thickness h2, working face or roadway advancing towards a fault with a drop greater than 3m, and distance L between the working face or face and the fault. d A working face or roadway advancing towards a syncline or anticline with a drastic change in the dip angle of the coal seam (>15°), the distance L between the working face or the face and the syncline. z The working face or roadway advancing towards the part of the coal seam that has eroded, merged, or changed in thickness, at a distance L from the part of the coal seam that has changed in thickness. b The ratio γ of the stress increment caused by tectonic activity to the normal stress value in the mining area, the distance d between the hard, thick rock strata in the overlying fracture zone and the coal seam, and the tensile strength R of the roof. t The width d of the coal pillar in the section, and the horizontal distance h between the working face and the coal pillar left over from the mining of the upper protective layer. z Characteristic parameter L of the roof strata thickness within 100m above the coal seam st wait.
[0049] In one implementation, the total thickness h of the i-th type of rock layer within a 100m range of the top plate can be used as the basis. i The weak surface reduction coefficient r of the i-th rock stratum i The characteristic parameter L of the roof strata thickness within a 100m range above the coal seam was obtained. st Where 1≤i≤n, i and n are positive integers, and n is the total number of rock strata within a 100m range of the roof.
[0050] For example, the characteristic parameter L of the roof strata thickness within 100m above the coal seam. st The formula for calculating the value of is as follows:
[0051]
[0052] For example, the weak surface reduction coefficient r of the i-th type of rock stratum i It can be determined based on Table 1.
[0053] Table 1 Strength ratio and weak surface index ratio of coal-bearing strata
[0054] rock strata sandstone mudstone shale coal Goaf rockfall Strength ratio 1.0 0.82 0.58 0.34 0.2 Weakness decrease coefficient ratio 1.0 0.62 0.29 0.31 0.04
[0055] S102, Based on the values of the target parameters, determine the values of the influencing factors affecting the classification of rockbursts.
[0056] It should be noted that influencing factors can affect the classification of rockbursts, and there are no strict limitations on these factors. For example, influencing factors include, but are not limited to, the rockburst occurrence mechanism, location, load, and surrounding conditions. Among these, load-related factors are also called force source factors.
[0057] Among them, the influencing factors of the rockburst mechanism include, but are not limited to, material instability and structural instability.
[0058] Among them, the factors affecting the location of rockbursts can be divided into roof rockbursts, floor rockbursts, and coal seam rockbursts from the perspective of coal and rock strata location, and into roadway rockbursts, mining face rockbursts, roadway rockbursts in front of mining face, and roadway rockbursts behind mining face from the perspective of tunneling and mining.
[0059] Among them, the load factors affecting rockburst include, but are not limited to, static load and dynamic load.
[0060] Among them, the factors affecting the surrounding conditions of rockbursts include, but are not limited to, fault rockbursts, coal seam phase transition zone rockbursts, and syncline axis rockbursts.
[0061] It should be noted that there are no strict restrictions on the range of values for influencing factors. For example, the range of values for influencing factors can be {0,1,2,3}.
[0062] In one implementation, the values of influencing factors affecting rockburst classification are determined based on the values of target parameters. This includes identifying the target parameter values within a target range and obtaining the values of the influencing factors based on the mapping relationship between the target range and the values of the influencing factors. Therefore, this method can obtain the values of the influencing factors by querying the mapping relationship based on the target parameter values within the target range.
[0063] It is understandable that the target parameter values can be pre-divided into multiple set ranges, and a mapping relationship between the set ranges and the values of influencing factors can be established, with the mapping relationship stored in the set storage space. It should be noted that different target parameters can be divided into different set ranges.
[0064] S103, Based on the values of influencing factors, determine the target category of rockburst within the monitoring area.
[0065] In one implementation, the target category of rockburst within the monitoring area is determined based on the values of influencing factors, including determining the target category from multiple predefined categories based on the values of influencing factors.
[0066] In one implementation, a target category is determined from multiple set categories based on the values of influencing factors, including obtaining the probability that the target category of rockburst in the monitoring area is a set category based on the values of influencing factors, and determining the set category corresponding to the highest probability as the target category.
[0067] In one implementation, the values of influencing factors can be input into a classification model, which then outputs the probability that the target category of the rockburst within the monitoring area is a predetermined category. It should be noted that the classification model is a pre-trained model, and no excessive limitations are imposed on it.
[0068] Understandably, rockbursts can be pre-classified into multiple categories without much restriction on the categories. For example, the categories could include gravity-type rockbursts, structural rockbursts, roof-type rockbursts, and coal pillar-type rockbursts.
[0069] The following section introduces gravity-type rockbursts, tectonic rockbursts, roof-type rockbursts, and coal pillar-type rockbursts.
[0070] Gravity-induced rockbursts have the following characteristics:
[0071] (1) It is likely to occur in the thick coal seams with a tendency to impact in deep mines. The impact area is often the relatively weak area of the roadway, that is, the roadway area affected by external static stress such as geological structure, coal seam phase change zone, adjacent roadway group, and goaf.
[0072] (2) It has spontaneity and time delay, meaning that it may occur in the absence of obvious external disturbances, after the roadway has been formed and stabilized for a long time, and some accidents occur after the roadway has undergone secondary support.
[0073] Tectonic rockbursts have the following characteristics:
[0074] (1) Its occurrence mechanism is that the mining influence causes the stick-slip friction between discontinuous surfaces in the structure to turn into sliding friction, which in turn leads to dynamic instability. Essentially, it belongs to the instability of coal and rock mass structure. Its sliding manifestation and failure characteristics are similar to the stick-slip phenomenon. The process is unsteady and accompanied by energy release.
[0075] (2) Its formation process is that the mining disturbance and the movement of the roof strata during coal seam mining change the stress state of the fault, increasing the probability of fault activation. The mining of the working face increases the supporting pressure of the coal body in front of it. At the same time, the evolution of the mining stress and the movement of the roof strata cause the fault zone rock mass to undergo slow deformation, and the strain energy in the working face coal body accumulates. As the working face gradually approaches the fault, this accumulation of stress and strain energy deepens. Before the fault slips, the stress of the coal body and its bearing capacity just reach a critical balance. Then, even a small mining disturbance will disrupt this balance, causing the loss of bearing capacity in the local high-stress zone of the working face coal body, resulting in a reduction in the supporting force on the fault rock mass, and thus increasing the shear stress of the fault zone. When the shear stress exceeds its friction strength, the fault will slip. At the same time, the rapid slip of the fault forms an impact effect on the working face coal body, which in turn triggers the impact instability of the coal and rock mass.
[0076] Top-plate rockbursts have the following characteristics:
[0077] (1) Its basic top is usually a hard, thick sandstone layer, making it difficult for the top plate to collapse.
[0078] (2) Its formation process is that as the working face continues to advance, the roof of the goaf behind the mining face is prone to be exposed in a large area. The roof of the large area of exposure suddenly breaks, forming a dynamic load, which induces the occurrence of this type of rockburst disaster.
[0079] Coal pillar type rockburst has the following characteristics:
[0080] (1) The locations where it occurs mainly include roadways located within coal pillars, working faces advancing towards coal pillars, roadways and working faces located below coal pillars, etc.
[0081] (2) Its formation process is that the protective coal pillars left in the same layer during the coal seam mining process are affected by the goaf and the stress concentration occurs. When both sides are goafs, the pressure of the coal pillar support will be higher due to superposition. The coal pillars left in the upper layer will also transmit the concentrated stress downward. The continuous accumulation of stress induces the occurrence of this type of rockburst disaster.
[0082] In summary, the rockburst classification method according to embodiments of the present invention involves collecting the values of target parameters within the monitoring area of a coal mine, determining the values of influencing factors affecting rockburst classification based on the values of the target parameters, and determining the target category of rockbursts within the monitoring area based on the values of the influencing factors. Therefore, the values of influencing factors can be determined based on the values of the target parameters, and then the target category of rockbursts can be determined based on the values of the influencing factors. This allows for rockburst classification based on quantitative analysis, reducing the difficulty of rockburst classification and contributing to improved accuracy.
[0083] Figure 2This is a flowchart illustrating a method for classifying rockbursts according to another embodiment of the present invention.
[0084] like Figure 2 As shown, the classification method for rockbursts according to an embodiment of the present invention includes:
[0085] S201, Collect the values of target parameters within the monitoring area of the coal mine.
[0086] The details of step S201 can be found in the above embodiments and will not be repeated here.
[0087] S202, determine the subordinate target parameters that belong to the influencing factors from the target parameters.
[0088] In embodiments of the present invention, there is a subordinate relationship between the target parameter and the influencing factor, and at least one target parameter belongs to one influencing factor. The subordinate relationship between the target parameter and the influencing factor can be established in advance and stored in a set storage space. The subordinate relationship is not subject to many restrictions.
[0089] In one implementation, determining the subordinate target parameters belonging to the influencing factors from the target parameters includes obtaining the membership relationship between the target parameters and the influencing factors, and determining the subordinate target parameters belonging to the influencing factors from the target parameters based on the membership relationship.
[0090] For example, influencing factors include G i S i R i P i , where i is a positive integer, and the membership relationship is shown in Table 2.
[0091] Table 2 Classification of Rockburst
[0092]
[0093]
[0094] The target parameters belonging to influencing factor G1 include mining depth h1.
[0095] The target parameters belonging to influencing factor G2 include the coal seam thickness h2.
[0096] The target parameters belonging to influencing factor S1 include the working face or roadway advancing towards a fault with a drop greater than 3m, and the distance L between the working face or face and the fault. d .
[0097] The target parameters belonging to influencing factor S2 include working faces or roadways advancing towards synclines or anticlines with drastic changes in coal seam dip angle (>15°), and the distance L between the working face or face and the syncline. z .
[0098] The target parameters belonging to influencing factor S3 include the working face or roadway advancing towards the coal seam erosion, merging, or thickness change section, and the distance L to the coal seam change section. b .
[0099] The target parameters belonging to influencing factor S4 include the ratio γ of the stress increment caused by the structure in the mining area to the normal stress value.
[0100] The target parameters belonging to influencing factor R1 include the distance d between the hard, thick rock strata in the overlying fracture zone and the coal seam.
[0101] The target parameters belonging to influencing factor R2 include the characteristic parameter L of the roof strata thickness within 100m above the coal seam. st .
[0102] The target parameters belonging to influencing factor R3 include the tensile strength R of the top plate. t .
[0103] The target parameters belonging to influencing factor P1 include the distance d between the hard, thick rock strata in the overlying fracture zone and the coal seam.
[0104] The target parameters belonging to influencing factor P2 include the horizontal distance h between the working face and the coal pillar left by the mining of the upper protective layer. z .
[0105] S203, based on the values of the membership target parameters, determine the values of the influencing factors.
[0106] The relevant content of step S203 can be found in step S102, and will not be repeated here.
[0107] In one implementation, the values of influencing factors are determined based on the values of the membership target parameters, including identifying the target setting range in which the values of the membership target parameters fall, and obtaining the values of the influencing factors based on the mapping relationship between the target setting range and the values of the influencing factors.
[0108] For example, continuing with Table 2, the influencing factor G i S i R i P i The value range of can be {0, 1, 2, 3}.
[0109] Taking influencing factor G1 and mining depth h1 as examples, when h1≤400m, the value of influencing factor G1 is 0; when 400m800m, the value of influencing factor G1 is 3.<h1>
[0110] For other mapping relationships, please refer to the examples of influencing factor G1 and mining depth h1, which will not be repeated here.
[0111] S204, Based on the values of influencing factors, determine the value of the category index for the set category of rockburst in the monitoring area.
[0112] It should be noted that the relevant content regarding the category setting can be found in the above embodiments, and will not be repeated here.
[0113] It should be noted that each set category can correspond to a category index. The value of the category index is correlated with the probability that the target category of rockburst in the monitoring area is the set category. For example, the value of the category index is positively correlated with the probability that the target category of rockburst in the monitoring area is the set category.
[0114] For example, continuing with Table 2, the classifications for gravity-type rockburst, structural rockburst, roof-type rockburst, and coal pillar-type rockburst are gravity index G, structural index S, roof index R, and coal pillar index P, respectively.
[0115] In one implementation, the category index of the set category of rockburst in the monitoring area is determined based on the values of the influencing factors, including determining the subordinate influencing factors belonging to the category index from the influencing factors, and determining the value of the category index based on the values of the subordinate influencing factors.
[0116] It should be noted that there is a subordinate relationship between influencing factors and category indices. At least one influencing factor belongs to a category index. The subordinate relationship between influencing factors and category indices can be established in advance and stored in a designated storage space. There are no excessive restrictions on the subordinate relationship.
[0117] In one implementation, determining the subordinate influencing factors belonging to the category index from the influencing factors includes obtaining the membership relationship between the influencing factors and the category index, and determining the subordinate influencing factors belonging to the category index from the influencing factors based on the membership relationship.
[0118] For example, continuing with Table 2, the influencing factors belonging to the gravity index G include influencing factors G1 and G2; the influencing factors belonging to the structural index S include influencing factors S1, S2, S3, and S4; the influencing factors belonging to the roof index R include influencing factors R1, R2, and R3; and the influencing factors belonging to the coal pillar index P include influencing factors P1 and P2.
[0119] In one implementation, the value of the category index is determined based on the values of the membership factors, including determining the average value of the membership factors as the value of the category index.
[0120] In one implementation, the category index of the set category of rockburst in the monitoring area is determined based on the values of the influencing factors. This includes determining the subordinate influencing factors that belong to the category index from the influencing factors, obtaining a first sum of the values of the subordinate influencing factors, and a second sum of the upper limit values of the subordinate influencing factors, and determining the ratio of the first sum to the second sum as the value of the category index.
[0121] It should be noted that the upper limit of the subordinate influencing factor refers to the maximum possible value of the subordinate influencing factor, that is, the upper limit of the value range of the subordinate influencing factor. No strict restrictions are placed on the upper limit of the subordinate influencing factor; different subordinate influencing factors may correspond to different upper limits.
[0122] Continuing with Table 2 as an example, influencing factor G i S i R i P i The value range of is {0, 1, 2, 3}, and the influencing factor G i S i R i P i The upper limit for each is 3. The calculation formulas for the gravity index G, structural index S, roof index R, and coal pillar index P are as follows:
[0123] G = (G1 + G2) / 6.
[0124] S = (S1 + S2 + S3 + S4) / 12.
[0125] R = (R1 + R2 + R3) / 9.
[0126] P = (P1 + P2) / 6.
[0127] For example, influencing factor G i S i R i P i The values of are shown in Table 3.
[0128] Table 3 Examples of rockburst classification
[0129]
[0130] The values of gravity index G, structural index S, roof index R, and coal pillar index P are as follows:
[0131] G=(G1+G2) / 6=(2+2) / 6=0.67.
[0132] S=(S1+S2+S3+S4) / 12=(1+1) / 12=0.17.
[0133] R=(R1+R2+R3) / 9=(3+2+2) / 9=0.78.
[0134] P = (P1 + P2) / 6 = 2 / 6 = 0.33.
[0135] S205, Based on the value of the category index, determine the target category from the set categories.
[0136] In one implementation, the value of the category index is positively correlated with the probability that the target category of rockburst within the monitoring area is a predetermined category. Based on the value of the category index, the target category is determined from the predetermined categories, including identifying the predetermined category corresponding to the highest category index as the target category. Therefore, this method can directly identify the predetermined category corresponding to the highest category index as the target category.
[0137] For example, if the values of gravity index G, structural index S, roof index R, and coal pillar index P are 0.67, 0.17, 0.78, and 0.33 respectively, then the roof index R is the largest category index, and roof-type rockburst can be determined as the target category.
[0138] In one implementation, the value of the category index is positively correlated with the probability that the target category of rockburst within the monitoring area corresponds to a predetermined category. Based on the category index value, the target category is determined from the predetermined categories. This includes sorting the category index values from largest to smallest, identifying the top n target category index values, and determining that the difference between any two target category index values is less than or equal to a predetermined threshold. The predetermined category corresponding to each target category index is then determined as the target category, where n is a positive integer greater than 1. Therefore, this method can determine the predetermined categories corresponding to the top n target category indices as target categories when the differences between their values are small, improving the accuracy of rockburst classification.
[0139] It should be noted that there are no strict restrictions on the threshold setting; for example, the threshold can be set to 10% of the target category index.
[0140] For example, if the values of gravity index G, structural index S, roof index R, and coal pillar index P are 0.67, 0.17, 0.68, and 0.33 respectively, then the category indices can be sorted from largest to smallest. The sorting result is 0.68, 0.67, 0.33, and 0.17. If the difference between 0.68 and 0.67 is within 10%, then both roof-type rockburst and gravity-type rockburst can be determined as target categories.
[0141] In summary, the rockburst classification method according to embodiments of the present invention determines the category index value of a set category of rockbursts within the monitoring area based on the values of influencing factors, and then determines the target category from the set categories based on the category index value. Therefore, the category index value can be determined based on the values of influencing factors, and the target category can be determined based on the category index value. This allows for rockburst classification based on quantitative analysis, which helps improve the accuracy of rockburst classification.
[0142] Figure 3 This is a flowchart illustrating a method for classifying rockbursts according to another embodiment of the present invention.
[0143] like Figure 3 As shown, the classification method for rockbursts according to an embodiment of the present invention includes:
[0144] S301, Collect the values of target parameters within the monitoring area of the coal mine.
[0145] S302, Based on the values of the target parameters, determine the values of the influencing factors affecting the classification of rockbursts.
[0146] S303, based on the values of influencing factors, determine the target category of rockburst within the monitoring area.
[0147] The relevant content of steps S301-S303 can be found in the above embodiments, and will not be repeated here.
[0148] S304, Obtain the engineering measures corresponding to the target category.
[0149] S305, Implement engineering measures within the monitored area.
[0150] It should be noted that the engineering measures include monitoring measures and prevention and control measures.
[0151] In one implementation, obtaining the engineering measures corresponding to the target category includes retrieving the engineering measures corresponding to the target category from an engineering measures library based on the target category. It should be noted that the engineering measures library is used to store multiple engineering measures.
[0152] In one implementation, based on the target category, the engineering measures corresponding to the target category are retrieved from the engineering measures library. This includes using the target category as the query key to search the mapping relationship or mapping table between the set categories and engineering measures in the engineering measures library, and determining the retrieved engineering measures as the engineering measures corresponding to the target category. It is understood that a mapping relationship or mapping table between the set categories and engineering measures can be pre-established and stored in the engineering measures library. The mapping relationship or mapping table can be set according to actual conditions, and no further limitations are imposed here.
[0153] For example, the engineering measures corresponding to the target category can be determined based on Table 4.
[0154] Table 4 Engineering Measures for Rockburst
[0155]
[0156] In one implementation, obtaining the engineering measures corresponding to the target category includes determining, in response to the target category including structural rockburst, that the engineering measures include fault grouting, and / or, in response to the target category including roof rockburst, that the engineering measures include surface hydraulic fracturing, underground slot pre-fracturing, roof blasting, roof blasting pre-fracturing, roof hydraulic fracturing, etc., and in response to the target category including coal pillar rockburst, determining that the engineering measures include pillarless or small coal pillar roadway protection.
[0157] In summary, according to the rockburst classification method of this invention, after determining the target category of rockburst within the monitoring area, the corresponding engineering measures can be obtained and implemented within the monitoring area. Therefore, based on the target category of rockburst within the monitoring area, targeted engineering measures can be obtained and implemented, improving the monitoring and prevention effectiveness of rockburst within the monitoring area, reducing the probability of rockburst occurrence, and ensuring production safety within the monitoring area.
[0158] To achieve the above embodiments, the present invention also proposes a classification device for rockbursts.
[0159] Figure 4 This is a schematic diagram of a rockburst classification device according to an embodiment of the present invention.
[0160] like Figure 4 As shown, the rockburst classification device 100 of this embodiment includes: a data acquisition module 110, a first determination module 120, and a second determination module 130.
[0161] The acquisition module 110 is used to acquire the values of target parameters within the monitoring area of the coal mine;
[0162] The first determining module 120 is used to determine the values of the influencing factors affecting the classification of rockbursts based on the values of the target parameters;
[0163] The second determining module 130 is used to determine the target category of rockburst within the monitoring area based on the values of the influencing factors.
[0164] In one embodiment of the present invention, the second determining module 130 is further configured to: determine the value of the category index of the set category of rockburst in the monitoring area based on the value of the influencing factor; and determine the target category from the set category based on the value of the category index.
[0165] In one embodiment of the present invention, the second determining module 130 is further configured to: determine the subordinate influencing factors belonging to the category index from the influencing factors; obtain the sum of the values of the subordinate influencing factors and the maximum value of the values of the subordinate influencing factors; and determine the ratio of the sum to the maximum value as the value of the category index.
[0166] In one embodiment of the present invention, the second determining module 130 is further configured to: determine the set category corresponding to the maximum category index as the target category.
[0167] In one embodiment of the present invention, the second determining module 130 is further configured to: sort the values of the category indices from largest to smallest; identify that among the values of the top n target category indices, the difference between any two target category indices is less than or equal to a set threshold, and determine the set category corresponding to each target category index as the target category, wherein n is a positive integer greater than 1.
[0168] In one embodiment of the present invention, the defined categories include gravity-type rockburst, structural rockburst, roof-type rockburst, and coal pillar-type rockburst.
[0169] In one embodiment of the present invention, the first determining module 120 is further configured to: determine the subordinate target parameters belonging to the influencing factor from the target parameters; and determine the value of the influencing factor based on the value of the subordinate target parameters.
[0170] In one embodiment of the present invention, the first determining module 120 is further configured to: identify the target parameter value within a target setting range; and obtain the value of the influencing factor based on the mapping relationship between the target setting range and the value of the influencing factor.
[0171] In one embodiment of the present invention, the rockburst classification device 100 further includes an execution module, which is configured to: acquire engineering measures corresponding to the target category; and execute the engineering measures within the monitoring area.
[0172] It should be noted that for details not disclosed in the rockburst classification device of this embodiment, please refer to the details disclosed in the rockburst classification method of this embodiment, which will not be repeated here.
[0173] In summary, the rockburst classification device of this invention collects the values of target parameters within the monitoring area of a coal mine, determines the values of influencing factors affecting rockburst classification based on the values of the target parameters, and determines the target category of rockbursts within the monitoring area based on the values of the influencing factors. Therefore, the values of influencing factors can be determined based on the values of the target parameters, and then the target category of rockbursts can be determined based on the values of the influencing factors. Rockburst classification can be achieved through quantitative analysis, reducing the difficulty of rockburst classification and helping to improve the accuracy of rockburst classification.
[0174] To achieve the above embodiments, such as Figure 5 As shown, an embodiment of the present invention proposes an electronic device 200, including: a memory 210, a processor 220, and a computer program stored in the memory 210 and executable on the processor 220. When the processor 220 executes the program, it implements the above-mentioned method for classifying rockbursts.
[0175] The electronic device of this invention executes a computer program stored in a memory via a processor to collect the values of target parameters within the monitoring area of a coal mine. Based on the values of the target parameters, it determines the values of influencing factors affecting rockburst classification, and based on the values of these influencing factors, it determines the target category of rockburst within the monitoring area. Thus, the values of influencing factors can be determined based on the values of the target parameters, and subsequently, the target category of rockburst can be determined based on these influencing factors. This allows for rockburst classification based on quantitative analysis, reducing the difficulty of rockburst classification and contributing to improved accuracy.
[0176] To implement the above embodiments, this invention proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for classifying rockbursts.
[0177] The computer-readable storage medium of this invention stores a computer program, which is executed by a processor, to collect the values of target parameters within a monitoring area of a coal mine. Based on the values of the target parameters, it determines the values of influencing factors affecting rockburst classification, and based on the values of these influencing factors, determines the target category of rockburst within the monitoring area. Therefore, the values of influencing factors can be determined based on the values of the target parameters, and then the target category of rockburst can be determined based on these influencing factors. This allows for rockburst classification based on quantitative analysis, reducing the difficulty of rockburst classification and contributing to improved accuracy.
[0178] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.
[0179] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.
[0180] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.
[0181] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.
[0182] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0183] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.
Claims
1. A method for classifying rockbursts, characterized in that, include: Collect the values of target parameters within the monitoring area of the coal mine; Based on the values of the target parameters, the values of the influencing factors affecting the classification of rockbursts are determined. These influencing factors include the rockburst occurrence mechanism, location, load, and surrounding conditions. The rockburst occurrence mechanism influencing factors include material instability and structural instability. The rockburst occurrence location influencing factors are classified from the perspective of coal and rock strata location into roof rockburst, floor rockburst, and coal seam rockburst, and from the perspective of tunneling and mining into roadway rockburst, mining face rockburst, roadway rockburst in front of the mining face, and roadway rockburst behind the mining face. The rockburst occurrence load influencing factors include static load and dynamic load. The rockburst occurrence surrounding conditions influencing factors include fault rockburst, coal seam phase change zone rockburst, and syncline axis rockburst. Determining the target category of rockburst within the monitoring area based on the values of the influencing factors includes: determining the category index value of a set category of rockburst within the monitoring area based on the values of the influencing factors; sorting the category index values from largest to smallest; identifying that among the top n target category index values, the difference between any two target category index values is less than or equal to a set threshold, and determining the set category corresponding to each target category index as the target category, where n is a positive integer greater than 1.
2. The method according to claim 1, characterized in that, The determination of the category index value for the set category of rockburst in the monitoring area based on the values of the influencing factors includes: Determine the influencing factors belonging to the category index from the influencing factors; Obtain the first sum of the values of the subordinate influencing factors, and the second sum of the upper limit values of the subordinate influencing factors; The ratio of the first sum to the second sum is determined as the value of the category index.
3. The method according to claim 1, characterized in that, The determination of the target category of rockburst within the monitoring area based on the values of the influencing factors includes: The category corresponding to the maximum category index is determined as the target category.
4. The method according to any one of claims 1-3, characterized in that, The defined categories include gravity-type rockburst, tectonic rockburst, roof-type rockburst, and coal pillar-type rockburst.
5. The method according to claim 1, characterized in that, The determination of the values of influencing factors affecting rockburst classification based on the values of the target parameters includes: Determine the membership target parameters belonging to the influencing factors from the target parameters; The values of the influencing factors are determined based on the values of the membership target parameters.
6. The method according to claim 1, characterized in that, The determination of the values of influencing factors affecting rockburst classification based on the values of the target parameters includes: Identify the target parameter's value within the target setting range; Based on the mapping relationship between the target setting range and the values of the influencing factors, the values of the influencing factors are obtained.
7. The method according to claim 1, characterized in that, Also includes: Obtain the engineering measures corresponding to the target category; The engineering measures shall be implemented within the monitored area.
8. A classification device for rockbursts, employing the classification method for rockbursts as described in any one of claims 1-7, characterized in that, include: The data acquisition module is used to collect the values of target parameters within the monitoring area of the coal mine. The first determining module is used to determine the values of the influencing factors affecting the classification of rockbursts based on the values of the target parameters. The second determining module is used to determine the target category of rockburst within the monitoring area based on the values of the influencing factors.