Coal seam outburst danger early warning method and device based on multi-scale micro-seismic information fusion

Abstract

The invention provides a coal seam outburst risk early warning method and device based on multi-scale micro-seismic information fusion, and relates to the technical field of coal seam outburst risk early warning. The method comprises the following steps: arranging a micro-seismic sensor network, collecting micro-seismic signals in a tunneling process, and eliminating interference signals by using a filtering technology; dividing the working face space into a plurality of areas by taking the center of the driving working face as a reference point, and endowing each area with different equivalent coefficients according to the distance from the driving working face; combining the prominent potential energy and the balance coefficient, establishing a quantitative relation between the micro-seismic signal energy and the risk degree, and calculating the equivalent risk degree of the micro-seismic signal; calculating the risk degree of the micro-seismic signal in the continuous time interval through an accumulation summation mode; and setting an early warning threshold value by adopting a critical value method, comparing the current risk degree with the early warning threshold value in real time, and triggering early warning when an early warning condition is met. According to the invention, the reasonable equivalent value is set according to the signal distance, and the early warning accuracy and effectiveness of high-risk operation areas such as a coal mine can be remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of coal seam outburst hazard early warning, and in particular to a coal seam outburst hazard early warning method and device based on multi-scale microseismic information fusion. Background Art

[0002] Coal seam outburst is one of the main dynamic disasters faced by coal mines, with the characteristics of rapid occurrence and strong destructiveness. Therefore, how to accurately predict and warn of coal seam outburst danger is an important engineering and technical problem that needs to be solved in the process of coal seam excavation.

[0003] The danger of coal seam outburst can be predicted by collecting microseismic signals, but the current methods have limitations, namely, they only focus on local short-range signals or blindly cover signals in the entire area, ignoring the complexity of the disaster mechanism, resulting in limited prediction accuracy. Summary of the invention

[0004] In view of the above problems, the purpose of the present invention is to provide a coal seam outburst hazard warning method and device based on multi-scale microseismic information fusion, setting reasonable equivalent values ​​according to the signal distance to improve the accuracy and effectiveness of the warning.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] On the one hand, a coal seam outburst hazard early warning method based on multi-scale microseismic information fusion is provided, the method comprising the following steps:

[0007] S1. Arrange a microseismic sensor network to collect microseismic signals during tunneling and use filtering technology to remove interference signals;

[0008] S2. Taking the center of the excavation working face as the reference point, the working face space is divided into multiple areas, and each area is assigned a different equivalent coefficient according to the distance from the excavation working face;

[0009] S3. Combine the outstanding potential energy and balance coefficient to establish the quantitative relationship between the microseismic signal energy and the hazard level, and calculate the equivalent hazard level of the microseismic signal;

[0010] S4, calculating the risk level of microseismic signals within a continuous time interval by cumulative summation;

[0011] S5. Use the critical value method to set the warning threshold, compare the current risk level with the warning threshold in real time, and trigger the warning when the warning conditions are met.

[0012] Optionally, the step S1 specifically includes:

[0013] The microseismic sensor network is arranged according to the length l of the excavation working face and the microseismic influence range L. The microseismic influence range L is set to twice the length l of the excavation working face. Specifically, microseismic sensors are arranged within a range of 200m in front of, on both sides of, and behind the excavation working face.

[0014] Optionally, the step S2 specifically includes:

[0015] Taking the center of the excavation working face as the reference point, a segmented concentric sphere is constructed to divide the working face space into multiple areas, each area having a different distance from the excavation working face;

[0016] According to the distance between each area and the tunneling working face, the influence of microseismic signals on the tunneling working face is divided into several different levels, and each level is assigned an equivalent coefficient.

[0017] Optionally, in step S2, the working face space is divided into 5 areas, and each area is assigned an equivalent coefficient ξ according to the distance from the excavation working face. The specific setting is: the microseismic signal energy is equally selected in the area 0-100m away from the excavation working face, 50% of the microseismic signal energy is selected in the area 100-200m, 6.25% of the microseismic signal energy is selected in the area 200-500m, 0.006% of the microseismic signal energy is selected in the area 500-1000m, and the influence of microseismic signals in areas greater than 1000m is ignored.

[0018] Optionally, the step S3 specifically includes:

[0019] Set the outburst potential energy Q, which represents the energy limit that prevents outburst, and is calculated by the gas expansion calculation formula. ; In the formula, p0 is the atmospheric pressure in the tunnel, p is the gas pressure, V0 is the gas content involved in the outburst, and n is the methane insulation coefficient;

[0020] For each microseismic signal, according to its microseismic signal energy E, equivalent coefficient ξ, outburst potential energy Q and balance coefficient λ, the formula is used The equivalent hazard degree W is calculated, where the equivalent coefficient ξ is determined according to the distance between the microseismic signal and the excavation working face.

[0021] Optionally, in step S3, the equivalent risk W of a single microseismic signal is calculated by the following formula:

[0022] ;

[0023] Among them, the balance coefficient λ is determined through accident cases. When the accident occurs, the equivalent hazard level is considered to be 1. λ is calculated based on the microseismic signal energy E, equivalent coefficient ξ, and outburst potential energy Q at this time.

[0024] Optionally, the step S4 specifically includes:

[0025] In the continuous time interval Δt, the hazard level W(Δt) of the microseismic signal is calculated by cumulative summation, W(Δt)=ΣW, where Δt is selected according to the disturbance rheological stability time range determined by the difference in coal quality characteristics.

[0026] Optionally, the step S5 specifically includes:

[0027] Based on long-term monitoring data, determine the maximum value of the risk level W when a blowout, stuck drill, or outburst power event occurs. max With the minimum value W min ;

[0028] Set the warning threshold to 0.75W max In the real-time monitoring process, the currently calculated W(Δt) value is compared with the warning threshold. min With 0.75W max When the time is between, the warning is triggered.

[0029] On the other hand, a coal seam outburst hazard warning device based on multi-scale microseismic information fusion is provided, which is used to implement any of the above methods, and the device comprises:

[0030] The signal acquisition module is used to arrange the microseismic sensor network, collect microseismic signals during the excavation process, and use filtering technology to eliminate interference signals;

[0031] The area division module is used to divide the working face space into multiple areas with the center of the excavation working face as the reference point. Each area is assigned a different equivalent coefficient according to the distance from the excavation working face;

[0032] The first calculation module is used to combine the outburst potential energy and the balance coefficient to establish a quantitative relationship between the microseismic signal energy and the hazard level, and calculate the equivalent hazard level of the microseismic signal;

[0033] The second calculation module is used to calculate the danger level of the microseismic signal within a continuous time interval by cumulative summation;

[0034] The judgment and warning module is used to set the warning threshold using the critical value method, compare the current danger level with the warning threshold in real time, and trigger the warning when the warning conditions are met.

[0035] In another aspect, an electronic device is provided, the electronic device comprising:

[0036] processor;

[0037] A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are loaded and executed by the processor, the steps of the above-mentioned coal seam outburst hazard warning method are implemented.

[0038] On the other hand, a computer-readable storage medium is provided, in which program code is stored. The program code can be called by a processor to execute the steps of the above-mentioned coal seam outburst hazard warning method.

[0039] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0040] In the embodiment of the present invention, by arranging a microseismic sensor network in a specific area, the focus is on microseismic monitoring of the excavation working face; the working face space is divided into multiple areas, and a segmented concentric spherical model is innovatively constructed; different equivalent coefficients are assigned according to the distance of the signal to accurately reflect the contribution of the signal to the danger; the equivalent danger of the microseismic signal is calculated in combination with the potential energy and the balance coefficient, and a quantitative relationship between the energy and danger of the microseismic signal is established; the danger of the microseismic signal is dynamically accumulated in real time to ensure the timeliness and accuracy of the assessment; the critical value method is used to set the warning threshold, and the current danger is compared with the warning threshold in real time, and the warning is triggered when the warning conditions are met. The present invention breaks through the limitations of the existing coal seam outburst hazard prediction methods, sets reasonable equivalent values ​​according to the distance of the signal, and can significantly improve the accuracy and effectiveness of warnings in high-risk operating areas such as coal mines, providing a strong guarantee for safe production. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 It is a flow chart of a coal seam outburst hazard early warning method based on multi-scale microseismic information fusion provided by an embodiment of the present invention;

[0043] Figure 2 is a schematic diagram of the spatial division of a working surface provided by an embodiment of the present invention;

[0044] Figure 3 It is a schematic structural diagram of a coal seam outburst hazard warning device with multi-scale microseismic information fusion provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the word "exemplary" is used to present concepts in a specific way.

[0047] The embodiment of the present invention provides a coal seam outburst hazard early warning method based on multi-scale microseismic information fusion, such as Figure 1 As shown, the method comprises the following steps:

[0048] S1. Arrange a microseismic sensor network to collect microseismic signals during excavation and use filtering technology to eliminate interference signals.

[0049] First, the microseismic sensors are arranged. The range of the microseismic sensors is determined by the length l of the excavation working face and the microseismic influence range L. It is generally believed that the microseismic influence range L is a function of the length l of the excavation working face, and L is set to 2l. As an optional implementation, the microseismic sensors are arranged within a range of 200m in front of, on both sides of, and behind the excavation working face.

[0050] During excavation operations, microseismic signals are collected during the excavation process, and filtering technology is used to eliminate interference signals generated by human activities to ensure that only signals reflecting the actual fracture state of coal and rock are retained and focused on, thereby improving the accuracy and reliability of monitoring data.

[0051] S2. Taking the center of the excavation working face as the reference point, the working face space is divided into multiple areas, and each area is assigned a different equivalent coefficient according to the distance from the excavation working face.

[0052] In this step, a segmented concentric sphere is constructed with the center of the excavation working face as the reference point, and the working face space is divided into multiple areas, each area has a different distance from the excavation working face; according to the distance between each area and the excavation working face, the influence of the microseismic signal on the excavation working face is divided into multiple different levels, and each level is assigned an equivalent coefficient.

[0053] Specifically, refer to Figure 2As shown, the working face space is divided into five areas, and each area is assigned an equivalent coefficient according to the distance from the excavation working face. The basis for setting the equivalent coefficient is that the farther the distance, the smaller the impact of the vibration signal on the excavation working face, and it decays exponentially.

[0054] The specific settings are: the microseismic signal energy is selected at equal values ​​in the area 0-100m away from the excavation working face, 50% of the microseismic signal energy is selected in the area 100-200m, 6.25% of the microseismic signal energy is selected in the area 200-500m, 0.006% of the microseismic signal energy is selected in the area 500-1000m, and the influence of microseismic signals is ignored in areas greater than 1000m.

[0055] For each microseismic signal, its inherent energy E (i.e., microseismic signal energy E) is used as the basis, and an equivalent coefficient is introduced to reflect the contribution of signal characteristics to the danger of outburst. According to the distance from the excavation working face, the impact of the microseismic signals in these concentric circles on the excavation working face is divided into five different levels, and each level is assigned an equivalent coefficient to reflect the change of signal attenuation or propagation characteristics.

[0056] by Figure 2 For example, the energy decays exponentially with distance. If the range of level I is set to 0~100 (average value 50m), the range of level II is 100~200 (average value 150), which is 100m more than before, 100 / 50=2, and the energy value is 1 / 2 of the original value; the range of level III is 200~500 (average 250m), which is 200m more, 200 / 50=4, and the energy decay rate is 1 / 24=1 / 16=6.25%; the range of level IV is 500~1000 (average 750m), which is 700m more, 700 / 50=14, and the energy decay rate is 1 / 214=1 / 16384=0.006%; the energy of level V is the area beyond 1000m, and the energy can be ignored. Therefore, the value of ξ is related to the distance, and can be 1, 0.5, 0.0625, 0.00006, etc.

[0057] S3. Combine the outstanding potential energy and balance coefficient to establish the quantitative relationship between the energy and hazard level of microseismic signals and calculate the equivalent hazard level of microseismic signals.

[0058] Set the outburst potential energy Q, which represents the energy limit that prevents outburst, and is calculated by the gas expansion formula. ; In the formula, p0 is the atmospheric pressure in the tunnel, p0=0.1 MP; p is the gas pressure, unit MPa; V0 is the gas content involved in the outburst, unit cm 3 / g; n is the adiabatic coefficient of methane, n=1.31.

[0059] For each microseismic signal, according to its microseismic signal energy E, equivalent coefficient ξ, outburst potential energy Q and balance coefficient λ, the formula is used The equivalent hazard degree W is calculated, where the equivalent coefficient ξ is determined according to the distance between the microseismic signal and the excavation working face.

[0060] Specifically, the equivalent hazard W of a single microseismic signal is calculated by the following formula:

[0061] .

[0062] In view of the complex heterogeneity of coal rock structure, it is difficult to directly obtain the formula for accurately calculating λ. Therefore, an approximate value based on practical experience is used as a substitute to ensure the effectiveness and practicality of the analysis.

[0063] The selection of λ is determined by accident cases (dynamic manifestation events such as blowholes, drill jams, and outbursts). When an accident occurs, the equivalent hazard level is considered to be 1. The microseismic signal energy E at this time is obtained by weighted summation, and the equivalent coefficient ξ is determined based on the distance. The outburst potential energy Q is calculated using the gas expansion formula to obtain λ. This λ value can be used as the balance coefficient for subsequent hazard prediction.

[0064] For example, setting 1×10 3 The equivalent hazard level of the microseismic signal energy of J is W=1, and λ=0.41 is calculated. This balance coefficient can reflect the influence of mining disturbance load on the outburst.

[0065] S4. Calculate the risk level of microseismic signals within continuous time intervals by cumulative summation.

[0066] In the continuous time interval Δt, the hazard level W(Δt) of the microseismic signal is calculated by cumulative summation, W(Δt)=ΣW, where Δt is selected according to the difference in coal quality characteristics and the stable time range of disturbance rheology.

[0067] When evaluating the hazard level W(Δt) of microseismic signals within a continuous time interval Δt, the cumulative summation method is adopted, that is, W(Δt)=Σw (each signal), where the time scale Δt is selected based on the disturbance rheological stability time range determined by the difference in coal quality characteristics, and is usually set based on the actual experience value of the mine, ranging from 1 hour to 24 hours. This calculation process is a dynamic continuous accumulation. For example, when Δt is set to 1 hour, the W(1h) calculated at 7 o'clock represents the cumulative effect of all signals from 6 o'clock to 7 o'clock, and the calculation result at 7:10 covers the cumulative value of the signals from 6:10 to 7:10, thereby ensuring the timeliness and accuracy of the evaluation.

[0068] S5. Use the critical value method to set the warning threshold, compare the current risk level with the warning threshold in real time, and trigger the warning when the warning conditions are met.

[0069] In this step, based on the long-term monitoring data, the maximum value W of the risk level when the blowout, stuck drill, or outburst power manifestation event occurs is determined. max With the minimum value W min ;

[0070] Set the warning threshold to 0.75W max In the real-time monitoring process, the currently calculated W(Δt) value is compared with the warning threshold. min With 0.75W max When the time is between, the warning is triggered.

[0071] In the embodiment of the present invention, by arranging a microseismic sensor network in a specific area, the focus is on microseismic monitoring of the excavation working face; the working face space is divided into multiple areas, and a segmented concentric spherical model is innovatively constructed; different equivalent coefficients are assigned according to the distance of the signal to accurately reflect the contribution of the signal to the danger; the equivalent danger of the microseismic signal is calculated in combination with the potential energy and the balance coefficient, and a quantitative relationship between the energy and danger of the microseismic signal is established; the danger of the microseismic signal is dynamically accumulated in real time to ensure the timeliness and accuracy of the assessment; the critical value method is used to set the warning threshold, and the current danger is compared with the warning threshold in real time, and the warning is triggered when the warning conditions are met. The present invention breaks through the limitations of the existing coal seam outburst hazard prediction methods, sets reasonable equivalent values ​​according to the distance of the signal, and can significantly improve the accuracy and effectiveness of warnings in high-risk operating areas such as coal mines, providing a strong guarantee for safe production.

[0072] Accordingly, an embodiment of the present invention also provides a coal seam outburst hazard warning device based on multi-scale microseismic information fusion, such as Figure 3 As shown, the device comprises:

[0073] The signal acquisition module 201 is used to arrange a microseismic sensor network, collect microseismic signals during the excavation process, and use filtering technology to remove interference signals;

[0074] The area division module 202 is used to divide the working face space into multiple areas with the center of the excavation working face as the reference point, and each area is assigned a different equivalent coefficient according to the distance from the excavation working face;

[0075] The first calculation module 203 is used to combine the outburst potential energy and the balance coefficient to establish a quantitative relationship between the microseismic signal energy and the hazard level, and calculate the equivalent hazard level of the microseismic signal;

[0076] The second calculation module 204 is used to calculate the risk level of the microseismic signal within a continuous time interval by cumulative summation;

[0077] The judgment and warning module 205 is used to set the warning threshold by adopting the critical value method, compare the current danger level with the warning threshold in real time, and trigger the warning when the warning condition is met.

[0078] For ease of explanation, Figure 3 Only the main components of the device are shown. The device of this embodiment can be used to perform Figure 1 The technical solution of the method embodiment shown has similar implementation principles and technical effects, which will not be repeated here.

[0079] In an exemplary embodiment, the present invention further provides an electronic device, the electronic device comprising:

[0080] processor;

[0081] A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are loaded and executed by the processor, the steps of the above-mentioned coal seam outburst hazard warning method are implemented.

[0082] In an exemplary embodiment, the present invention further provides a computer-readable storage medium, wherein at least one instruction is stored in the computer-readable storage medium, and the at least one instruction is loaded and executed by a processor to implement the steps of the above-mentioned coal seam outburst hazard early warning method. For example, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0083] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0084] References in the specification to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments", etc. indicate that the described embodiments may include a particular feature, structure, or characteristic, but not every embodiment may include the particular feature, structure, or characteristic. In addition, when a particular feature, structure, or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the relevant art to implement such feature, structure, or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0085] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0086] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0087] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0088] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0089] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0090] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0091] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0092] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0093] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A coal seam outburst hazard early warning method based on multi-scale microseismic information fusion, characterized in that: The following steps are involved: S1. Arrange a microseismic sensor network to collect microseismic signals during tunneling and use filtering technology to remove interference signals; S2. Taking the center of the excavation working face as the reference point, the working face space is divided into multiple areas, and each area is assigned a different equivalent coefficient according to the distance from the excavation working face; S3. Combine the outstanding potential energy and balance coefficient to establish the quantitative relationship between the microseismic signal energy and the hazard level, and calculate the equivalent hazard level of the microseismic signal; S4, calculating the risk level of microseismic signals within a continuous time interval by cumulative summation; S5. Use the critical value method to set the warning threshold, compare the current risk level with the warning threshold in real time, and trigger the warning when the warning conditions are met.

2. The method for coal seam outburst hazard early warning based on multi-scale microseismic information fusion according to claim 1 is characterized in that: The step S1 specifically includes: The microseismic sensor network is arranged according to the length l of the excavation working face and the microseismic influence range L. The microseismic influence range L is set to twice the length l of the excavation working face. Specifically, microseismic sensors are arranged within a range of 200m in front of, on both sides of, and behind the excavation working face.

3. The method for coal seam outburst hazard early warning based on multi-scale microseismic information fusion according to claim 1 is characterized in that: The step S2 specifically includes: Taking the center of the excavation working face as the reference point, a segmented concentric sphere is constructed to divide the working face space into multiple areas, each area having a different distance from the excavation working face; According to the distance between each area and the tunneling working face, the influence of microseismic signals on the tunneling working face is divided into several different levels, and each level is assigned an equivalent coefficient.

4. The method for coal seam outburst hazard early warning based on multi-scale microseismic information fusion according to claim 3 is characterized in that: In step S2, the working face space is divided into five areas, and each area is assigned an equivalent coefficient ξ according to the distance from the excavation working face. The specific setting is: the microseismic signal energy is equally selected in the area 0-100m away from the excavation working face, 50% of the microseismic signal energy is selected in the area 100-200m, 6.25% of the microseismic signal energy is selected in the area 200-500m, 0.006% of the microseismic signal energy is selected in the area 500-1000m, and the influence of microseismic signals is ignored in areas greater than 1000m.

5. The method for coal seam outburst hazard early warning based on multi-scale microseismic information fusion according to claim 1 is characterized in that: The step S3 specifically includes: Set the outburst potential energy Q, which represents the energy limit that prevents outburst, and is calculated by the gas expansion calculation formula. ; In the formula, p0 is the atmospheric pressure in the tunnel, p is the gas pressure, V0 is the gas content involved in the outburst, and n is the methane insulation coefficient; For each microseismic signal, according to its microseismic signal energy E, equivalent coefficient ξ, outburst potential energy Q and balance coefficient λ, the formula is used The equivalent hazard degree W is calculated, where the equivalent coefficient ξ is determined according to the distance between the microseismic signal and the excavation working face, and the balance coefficient λ is determined through accident cases.

6. The method for coal seam outburst hazard early warning based on multi-scale microseismic information fusion according to claim 5 is characterized in that: In step S3, the equivalent risk W of a single microseismic signal is calculated by the following formula: ； Among them, the balance coefficient λ is determined through accident cases. When the accident occurs, the equivalent hazard level is considered to be 1. λ is calculated based on the microseismic signal energy E, equivalent coefficient ξ, and outburst potential energy Q at this time.

7. The method for coal seam outburst hazard early warning based on multi-scale microseismic information fusion according to claim 1 is characterized in that: The step S4 specifically includes: In the continuous time interval Δt, the hazard level W(Δt) of the microseismic signal is calculated by cumulative summation, W(Δt)=ΣW, where Δt is selected according to the disturbance rheological stability time range determined by the difference in coal quality characteristics.

8. The method for coal seam outburst hazard early warning based on multi-scale microseismic information fusion according to claim 1 is characterized in that: The step S5 specifically includes: Based on long-term monitoring data, determine the maximum value of the risk level W when a blowout, stuck drill, or outburst power event occurs. max With the minimum value W min ; Set the warning threshold to 0.75W max In the real-time monitoring process, the currently calculated W(Δt) value is compared with the warning threshold. min With 0.75W max When the time is between, the warning is triggered.

9. A coal seam outburst hazard warning device based on multi-scale microseismic information fusion, the device being used to implement the method as claimed in any one of claims 1 to 8, characterized in that: The device comprises: The signal acquisition module is used to arrange the microseismic sensor network, collect microseismic signals during the excavation process, and use filtering technology to eliminate interference signals; The area division module is used to divide the working face space into multiple areas with the center of the excavation working face as the reference point. Each area is assigned a different equivalent coefficient according to the distance from the excavation working face; The first calculation module is used to combine the outburst potential energy and the balance coefficient to establish a quantitative relationship between the microseismic signal energy and the hazard level, and calculate the equivalent hazard level of the microseismic signal; The second calculation module is used to calculate the danger level of the microseismic signal within a continuous time interval by cumulative summation; The judgment and warning module is used to set the warning threshold using the critical value method, compare the current danger level with the warning threshold in real time, and trigger the warning when the warning conditions are met.

10. An electronic device, characterized in that: The electronic device comprises: processor; A memory having computer-readable instructions stored thereon, wherein the computer-readable instructions, when loaded and executed by the processor, implement the method according to any one of claims 1 to 8.

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