Mine micro-seismic composite early warning method, device, equipment and medium

Abstract

The invention discloses a mine micro-seismic composite early warning method, device and equipment and a medium, and relates to the technical field of mine micro-seismic early warning, and the method comprises the steps: collecting the current frequency data and current energy data of a micro-seismic event of a mine based on a preset sliding time window, and generating a dynamic frequency early warning threshold according to the frequency trend data of the current frequency data; generating a dynamic energy early warning threshold value according to the historical energy statistical value of the historical microseismic event of the same mine within the preset statistical time; based on the three-dimensional coordinates of the micro-seismic events and according to the spatial distribution density and the continuity condition of the micro-seismic time, identifying a spatial dense region, and obtaining a clustering region of the micro-seismic events; judging whether each micro-seismic parameter of the micro-seismic event in the clustering region is smaller than a corresponding dynamic frequency early warning threshold, a dynamic energy early warning threshold, a micro-seismic event experience threshold of the clustering region, a clustering energy threshold and a depth deviation threshold of the clustering region; if not, mine micro-seismic early warning is carried out. And accurate mine micro-seismic early warning is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of mine microseismic early warning, and particularly relates to a mine microseismic composite early warning method, device, equipment and medium. Background Art

[0002] Traditional mine microseismic early warning methods mainly rely on monitoring data of a single dimension (such as event frequency or energy value), lacking the joint analysis of time, space and energy. At present, traditional systems such as microseismic monitors only monitor the number of events or the peak energy during early warning monitoring, resulting in frequent false alarms during the active period of geological structures. For example, the normal activity of a fault zone is misjudged as a precursor to rock burst, and the process of progressive rock layer rupture is missed, such as the spatial aggregation characteristics not reaching the fixed threshold.

[0003] In mine / mine microseismic early warning, the early warning indicators in the monitoring data of a single dimension are based on fixed thresholds (such as the number of events or the energy upper limit), which cannot dynamically adapt to changes in geological conditions and are prone to false alarms or missed alarms. False alarms cause production losses, and missed alarms are likely to lead to safety accidents. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a mine microseismic composite early warning method, device, equipment and medium, which can realize the comprehensive early warning of mine microseismic by integrating multiple indicators and avoid missed alarms and false alarms. The specific solutions are as follows:

[0005] In a first aspect, the present application discloses a mine microseismic composite early warning method, including:

[0006] Collecting the current frequency data and current energy data of microseismic events in a mine based on a preset sliding time window, so as to generate a dynamic frequency early warning threshold according to the frequency trend data of the current frequency data;

[0007] Generating a dynamic energy early warning threshold according to the historical energy statistical value of historical microseismic events in the same mine within a preset statistical time; wherein, the preset statistical time is dynamically updated according to the current time;

[0008] Identifying a space dense area based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time, so as to obtain the clustering area of the microseismic events;

[0009] Judging whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency early warning threshold, the dynamic energy early warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area;

[0010] If not, then conduct mine microseismic early warning.

[0011] Optionally, generating a dynamic frequency warning threshold according to the frequency trend data of the current frequency data includes:

[0012] Determine the frequency moving average and frequency standard deviation of the microseismic events, and generate a dynamic frequency warning threshold based on the sum of the frequency moving average and twice the frequency standard deviation.

[0013] Optionally, generating a dynamic energy warning threshold according to the historical energy statistical value of the historical microseismic events in the same mine within a preset statistical time includes:

[0014] Generate corresponding dynamic single - energy warning thresholds and dynamic total - energy warning thresholds respectively according to the historical maximum energy of the historical microseismic events in the same mine within a preset statistical time, the corresponding first energy coefficient, the historical total energy statistical value, and the corresponding second energy coefficient.

[0015] Optionally, identifying a spatially dense area based on the three - dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time to obtain the clustering area of the microseismic events includes:

[0016] Obtain the three - dimensional coordinates of the microseismic events on the geodetic space rectangular coordinate system; wherein, the geodetic space rectangular coordinate system takes the intersection of the vertical plane where the prime meridian is located and the earth's equatorial plane as the zero point, the x - axis represents the direction along the equatorial plane pointing to the 90° east longitude direction, the y - axis represents the direction along the equatorial plane pointing to the 90° north latitude direction, takes the sea level as the zero point of the z - axis direction, and the z - axis represents the direction from the sea level pointing to the center of the earth;

[0017] Take each of the microseismic events as a microseismic point, and perform spatial dense area identification processing on each of the microseismic points through a density clustering algorithm according to a preset neighborhood radius, a preset microseismic point number threshold, and the three - dimensional coordinates of the microseismic points to obtain the clustering area of the microseismic events.

[0018] Optionally, before determining whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area, it further includes:

[0019] Take the current frequency data as the first microseismic parameter, the current energy data as the second microseismic parameter, count the total frequency data of the microseismic events in the clustering area as the third microseismic parameter, count the regional energy value of the microseismic events in the clustering area as the fourth microseismic data, and count the current average depth mean value and historical average depth mean value of the z - coordinate in the three - dimensional coordinates of the microseismic events in the clustering area as the fifth microseismic data.

[0020] Optionally, determining whether each microseismic parameter of the microseismic events in the clustering region is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering region, the clustering energy threshold of the clustering region, and the depth deviation threshold of the clustering region includes:

[0021] Determining whether the first microseismic parameter is less than the dynamic frequency warning threshold to obtain a first warning judgment result;

[0022] Determining whether the second microseismic parameter is less than the dynamic energy warning threshold to obtain a second warning judgment result;

[0023] Determining whether the third microseismic parameter is less than the microseismic event experience threshold to obtain a third warning judgment result;

[0024] Determining whether the fourth microseismic parameter is less than the clustering energy threshold to obtain a fourth warning judgment result;

[0025] Determining whether the fifth microseismic parameter is less than the depth deviation threshold to obtain a fifth warning judgment result;

[0026] Correspondingly, if not, then performing mine microseismic warning includes:

[0027] If there is any one or several warning judgment results greater than the corresponding threshold, then performing the corresponding type of mine microseismic warning.

[0028] Optionally, the mine microseismic composite warning method further includes:

[0029] If each microseismic parameter is less than the corresponding threshold, then prohibiting mine microseismic warning.

[0030] In a second aspect, the present application discloses a mine microseismic composite warning device, including:

[0031] A first dynamic threshold generation module, configured to collect the current frequency data and current energy data of the microseismic events of the mine based on a preset sliding time window, so as to generate a dynamic frequency warning threshold according to the frequency trend data of the current frequency data;

[0032] A second dynamic threshold generation module, configured to generate a dynamic energy warning threshold according to the historical energy statistical value of the historical microseismic events of the same mine within a preset statistical time; wherein, the preset statistical time is dynamically updated according to the current time;

[0033] A clustering module, configured to identify a spatially dense region based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time, so as to obtain the clustering region of the microseismic events;

[0034] A composite judgment module, configured to judge whether each microseismic parameter of the microseismic events in the clustering region is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering region, the clustering energy threshold of the clustering region, and the depth deviation threshold of the clustering region;

[0035] An early warning module, configured to perform mine microseismic early warning if the judgment result is negative.

[0036] In a third aspect, the present application discloses an electronic device, including:

[0037] A memory, configured to store a computer program;

[0038] A processor, configured to execute the computer program to implement the steps of the mine microseismic composite early warning method disclosed above.

[0039] In a fourth aspect, the present application discloses a computer-readable storage medium, configured to store a computer program; wherein, when the computer program is executed by a processor, the steps of the mine microseismic composite early warning method disclosed above are implemented.

[0040] It can be seen that the present application discloses a mine microseismic composite early warning method, including: collecting current frequency data and current energy data of microseismic events in a mine based on a preset sliding time window to generate a dynamic frequency warning threshold according to the frequency trend data of the current frequency data; generating a dynamic energy warning threshold according to the historical energy statistical value of historical microseismic events in the same mine within a preset statistical time; wherein, the preset statistical time is dynamically updated according to the current time; identifying a spatially dense region based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time to obtain the clustering region of the microseismic events; judging whether each microseismic parameter of the microseismic events in the clustering region is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering region, the clustering energy threshold of the clustering region, and the depth deviation threshold of the clustering region; if the judgment result is negative, then perform mine microseismic early warning. Thus, by using dynamic thresholds, the sensitivity of static thresholds to geological condition changes is overcome, and the dynamic update of the preset statistical time enables the energy warning threshold to be adaptively adjusted according to the mining progress. Further, three-dimensional coordinate density clustering can exclude non-associated events with discrete distributions through continuity conditions, and perform multi-dimensional comprehensive judgment on dynamic frequency, energy threshold, experience threshold, clustering energy threshold, and depth deviation threshold to achieve accurate mine microseismic early warning. Description of the Drawings

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on the provided drawings.

[0042] Figure 1 Flowchart of a mine microseismic composite early warning method disclosed in this application;

[0043] Figure 2 Schematic structural diagram of a mine microseismic composite early warning device disclosed in this application;

[0044] Figure 3 Structural diagram of an electronic device disclosed in this application. Specific embodiments

[0045] The following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0046] Traditional mine microseismic early warning methods mainly rely on single-dimensional monitoring data (such as event frequency or energy value), lacking the joint analysis of time, space, and energy. Currently, traditional systems such as microseismic monitors only monitor the number of events or the peak energy during early warning monitoring, resulting in frequent false alarms during active geological periods, such as normal activities in fault zones being misjudged as precursors of rock bursts, and the process of gradual rock layer rupture being missed, such as those with spatial aggregation characteristics but not reaching the fixed threshold.

[0047] In mine / mine microseismic early warning, the early warning indicators in single-dimensional monitoring data are based on fixed thresholds (such as the number of events or energy upper limit), which cannot dynamically adapt to changes in geological conditions and are prone to false alarms or missed alarms. False alarms cause production losses, and missed alarms are likely to lead to safety accidents.

[0048] Therefore, the present invention provides a mine microseismic composite early warning solution, which can comprehensively achieve the comprehensive early warning of mine microseisms by integrating multiple indicators, avoiding missed alarms and false alarms.

[0049] Refer to Figure 1 As shown, the embodiments of the present invention disclose a mine microseismic composite early warning method, including:

[0050] Step S11: Collect the current frequency data and current energy data of the microseismic events in the mine based on a preset sliding time window, so as to generate a dynamic frequency warning threshold according to the frequency trend data of the current frequency data.

[0051] In this embodiment, the frequency moving average and frequency standard deviation of the microseismic events are determined, and a dynamic frequency warning threshold is generated based on the sum of the frequency moving average and twice the frequency standard deviation. It can be understood that the double-stage risk judgment process is entered. Specifically, the preset sliding time window is set to 24 hours, and the current frequency data and current energy data of the microseismic events in the mine are collected based on the preset sliding time window, that is, the daily frequency data and daily energy data of the microseismic events are collected. Then, the frequency moving average and frequency standard deviation of the daily frequency data are calculated as the corresponding frequency trend data, and then the daily frequency warning threshold is generated based on the frequency moving average, frequency standard deviation, and the single-day frequency warning threshold setting formula. It should be noted that since the daily frequency warning threshold is determined according to the frequency data of the microseismic events on the same day, the frequency warning threshold for each day may be the same as that of the previous day or may not be the same, and it is actually dynamically changing. Therefore, the generated frequency warning threshold is a dynamic frequency warning threshold. Among them, the calculation formula for the frequency moving average is as follows:

[0052] ;

[0053] Among them, represents the frequency moving average on the th day, represents the number of hours in a day on the th day, represents the number of microseismic events at the

[0054] hour.

[0055] ;

[0056] Among them, represents the frequency standard deviation on the th day, reflecting the discreteness of the number of microseismic events on the same day.

[0057] Finally, the single-day frequency warning threshold setting formula is as follows:

[0058] ;

[0059] Among them, represents the dynamic frequency warning threshold.

[0060] Step S12: Generate a dynamic energy warning threshold based on the historical energy statistical values of historical microseismic events in the same mine within a preset statistical time; wherein, the preset statistical time is dynamically updated according to the current time.

[0061] In this embodiment, a corresponding dynamic single - energy warning threshold and a dynamic total - energy warning threshold are respectively generated according to the historical energy maximum value of historical microseismic events in the same mine within a preset statistical time and the corresponding first energy coefficient, as well as the historical total - energy statistical value and the corresponding second energy coefficient. It can be understood that the preset sliding time window is set to 24 hours. The historical total - energy statistical value and the single - time historical energy value of historical microseismic events in the same mine are statistically calculated through the preset sliding window (24 hours). The preset statistical time generally ranges from two weeks to one year according to the actual situation of the mine. In this embodiment, the preset statistical time is one month backward from the current time. The dynamic single - energy warning threshold is set to be greater than 0.5 times the dynamic single - energy warning threshold. Therefore, the first energy coefficient is 0.5. The dynamic total - energy warning threshold is set to be greater than 3 times the historical total - energy statistical value. Therefore, the second energy coefficient is 3.

[0062] Step S13: Based on the three - dimensional coordinates of the microseismic events, identify the space - dense area according to the spatial distribution density and continuity conditions of the microseismic time, so as to obtain the clustering area of the microseismic events.

[0063] In this embodiment, the three-dimensional coordinates of the microseismic events on the geodetic space rectangular coordinate system are obtained; wherein, the origin of the geodetic space rectangular coordinate system is the intersection point of the vertical plane where the prime meridian is located and the equatorial plane of the earth. The x-axis represents the direction pointing to 90° east longitude along the equatorial plane, the y-axis represents the direction pointing to 90° north latitude along the equatorial plane, the origin of the z-axis direction is the sea level, and the z-axis represents the direction pointing from the sea level to the center of the earth. Each of the microseismic events is used as a microseismic point, and the density clustering algorithm is used to perform spatial dense region identification processing on each of the microseismic points according to the preset neighborhood radius, the preset threshold of the number of microseismic points, and the three-dimensional coordinates of the microseismic points, so as to obtain the clustering region of the microseismic events. It can be understood that the geodetic space rectangular coordinate system is used to provide an absolute spatial positioning reference for the mine microseismic events, ensuring that the data of different monitoring devices have a unified spatial reference. Based on the DBSCAN algorithm, the Euclidean distance between each microseismic point is calculated according to the three-dimensional coordinates of each microseismic point, and the microseismic points with the Euclidean distance less than the preset neighborhood radius are divided into the same class to complete the clustering processing of the microseismic events. Among them, the preset neighborhood radius can be set to 50m. In addition, the minimum number of microseismic points MinPts in the driving face is set to 5, and the minimum number of microseismic points MinPts in the mining face is set to 70% of the historical maximum number of microseismic events to obtain the preset threshold of the number of microseismic points. If the number of microseismic points in a single clustering result is greater than the preset threshold of the number of microseismic points, the corresponding clustering region is obtained. After the above processing, the clustering region of the microseismic events is obtained. In this way, the clustering of the microseismic events simultaneously satisfies the spatial distribution density condition and the continuity condition.

[0064] Specifically, the process of clustering each microseismic event using the DBSCAN algorithm is as follows:

[0065] In DBSCAN, all microseismic points are potential candidate points, and it is necessary to check one by one whether they meet the conditions of core points. Generally speaking, it is necessary to traverse each microseismic point in the dataset and check whether the number of microseismic points within the preset neighborhood radius of each microseismic point reaches or exceeds MinPts. If so, it is marked as a core point. To efficiently find each point, a spatial index (such as KD tree, ball tree, etc.) is used to accelerate the query. In the actual operation of this embodiment, in order to balance performance and effect, it is to traverse each microseismic event for discrimination, that is, all microseismic events are used as an arbitrary point P to traverse and calculate:

[0066] ;

[0067] Among them, represents the set of microseismic events that meet the preset neighborhood radius condition, and Q represents the microseismic event whose distance from point P is less than or equal to the preset neighborhood radius.

[0068] The distance between microseismic events is calculated using the Euclidean distance:

[0069] ;

[0070] Among them, represents the three-dimensional coordinates of the microseismic event P and the three-dimensional coordinates of the microseismic event Q.

[0071] Furthermore, based on the preset microseismic point number threshold MinPts, it is judged whether each clustering result meets the requirements of the frequency condition:

[0072] The early warning determination condition is: .

[0073] Step S14: Judge whether each microseismic parameter of the microseismic events in the clustering region is respectively less than the corresponding dynamic frequency early warning threshold, the dynamic energy early warning threshold, the microseismic event experience threshold of the clustering region, the clustering energy threshold of the clustering region, and the depth deviation threshold of the clustering region.

[0074] In this embodiment, before judging whether each microseismic parameter of the microseismic events in the clustering region is respectively less than the corresponding dynamic frequency early warning threshold, the dynamic energy early warning threshold, the microseismic event experience threshold of the clustering region, the clustering energy threshold of the clustering region, and the depth deviation threshold of the clustering region, it further includes: taking the current frequency data as the first microseismic parameter, taking the current energy data as the second microseismic parameter, counting the total frequency data of the microseismic events in the clustering region as the third microseismic parameter, counting the regional energy value of the microseismic events in the clustering region as the fourth microseismic data, and counting the current average depth mean value and historical average depth mean value of the z coordinate in the three-dimensional coordinates of the microseismic events in the clustering region as the fifth microseismic data. Therefore, the process of judging whether each microseismic parameter of the microseismic events in the clustering region meets the early warning is as follows:

[0075] Determine whether the first microseismic parameter is less than the dynamic frequency warning threshold to obtain a first warning determination result; determine whether the second microseismic parameter is less than the dynamic energy warning threshold to obtain a second warning determination result; determine whether the third microseismic parameter is less than the microseismic event experience threshold to obtain a third warning determination result; determine whether the fourth microseismic parameter is less than the clustering energy threshold to obtain a fourth warning determination result; determine whether the fifth microseismic parameter is less than the depth deviation threshold to obtain a fifth warning determination result. Wherein, the microseismic event experience threshold is a preset total microseismic event frequency value in the clustering area, and the clustering energy threshold is the 80th percentile of the preset historical area energy value. Calculate the difference between the historical average depth mean and the current average depth mean, and divide the difference by the historical average depth mean to obtain the current depth deviation, and determine whether the current depth deviation is less than the depth deviation threshold, where the depth deviation threshold is set to 10%, and the historical average depth mean is the depth mean for the 7 days forward from the current time.

[0076] Step S15: If not, then perform mine microseismic warning.

[0077] In this embodiment, if any one or several warning determination results are greater than the corresponding thresholds, then perform the corresponding type of mine microseismic warning. If all the microseismic parameters are less than the corresponding thresholds, then prohibit the mine microseismic warning.

[0078] It can be seen that the present application discloses a mine microseismic composite warning method, including: collecting the current frequency data and current energy data of the microseismic events of the mine based on a preset sliding time window to generate a dynamic frequency warning threshold according to the frequency trend data of the current frequency data; generating a dynamic energy warning threshold according to the historical energy statistical value of the historical microseismic events of the same mine within a preset statistical time; wherein, the preset statistical time is dynamically updated according to the current time; identifying a space dense area based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time to obtain the clustering area of the microseismic events; determining whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area; if not, then perform mine microseismic warning. Thus, by using dynamic thresholds to overcome the sensitivity of static thresholds to geological condition changes, the preset statistical time is dynamically updated to make the energy warning threshold adaptively adjust with the mining progress. Further, the three-dimensional coordinate density clustering can exclude non-associated events with discrete distributions through continuity conditions, and comprehensively judge the dynamic frequency, energy threshold, experience threshold, clustering energy threshold, and depth deviation threshold in multiple dimensions to achieve accurate mine microseismic warning.

[0079] Refer toFigure 2 As shown in the figure, the present application also correspondingly discloses a mine microseismic composite early warning device, including:

[0080] A first dynamic threshold generation module 11, configured to collect current frequency data and current energy data of mine microseismic events based on a preset sliding time window, so as to generate a dynamic frequency early warning threshold according to the frequency trend data of the current frequency data;

[0081] A second dynamic threshold generation module 12, configured to generate a dynamic energy early warning threshold according to the historical energy statistical value of historical microseismic events in a preset statistical time of the same mine; wherein, the preset statistical time is dynamically updated according to the current time;

[0082] A clustering module 13, configured to identify a spatially dense area based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time, so as to obtain the clustering area of the microseismic events;

[0083] A composite judgment module 14, configured to judge whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency early warning threshold, the dynamic energy early warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area;

[0084] An early warning module 15, configured to, if not, perform mine microseismic early warning.

[0085] It can be seen that the present application discloses collecting current frequency data and current energy data of mine microseismic events based on a preset sliding time window, so as to generate a dynamic frequency early warning threshold according to the frequency trend data of the current frequency data; generating a dynamic energy early warning threshold according to the historical energy statistical value of historical microseismic events in a preset statistical time of the same mine; wherein, the preset statistical time is dynamically updated according to the current time; identifying a spatially dense area based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time, so as to obtain the clustering area of the microseismic events; judging whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency early warning threshold, the dynamic energy early warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area; if not, perform mine microseismic early warning. Thus, it can be seen that by using dynamic thresholds to overcome the sensitivity of static thresholds to geological condition changes, the dynamic update of the preset statistical time enables the energy early warning threshold to be adaptively adjusted with the mining progress. Further, three-dimensional coordinate density clustering can exclude discrete and non-associated events through continuity conditions, and comprehensively judge multiple dimensions such as dynamic frequency, energy threshold, experience threshold, clustering energy threshold, and depth deviation threshold to achieve accurate mine microseismic early warning.

[0086] Further, an embodiment of the present application also discloses an electronic device. Figure 3 FIG. 20 is a structural diagram of an electronic device 20 shown according to an exemplary embodiment. The content in the figure should not be considered as any limitation on the scope of use of the present application.

[0087] Figure 3 FIG. 20 is a schematic structural diagram of an electronic device 20 provided by an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. Among them, the memory 22 is used to store a computer program, and the computer program is loaded and executed by the processor 21 to implement the relevant steps in the mine microseismic composite warning method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0088] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows is any communication protocol applicable to the technical solution of the present application, and no specific limitation is imposed on it here; the input / output interface 25 is used to obtain external input data or output data to the outside, and its specific interface type can be selected according to specific application needs, and no specific limitation is made here.

[0089] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 may be implemented in at least one of the following hardware forms: DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the wake state, also known as the CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a GPU (Graphics Processing Unit), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an AI (Artificial Intelligence) processor, and the AI processor is used to process computational operations related to machine learning.

[0090] In addition, as a carrier for storing resources, the memory 22 can be a read-only memory, a random access memory, a magnetic disk, an optical disc, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0091] Among them, the operating system 221 is used to manage and control each hardware device and the computer program 222 on the electronic device 20, so as to enable the processor 21 to perform operations and processing on the massive data 223 in the memory 22. It can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program that can be used to complete the mine microseismic composite early warning method executed by the electronic device 20 disclosed in any of the foregoing embodiments, the computer program 222 can further include computer programs that can be used to complete other specific tasks. The data 223 can include not only the data transmitted by external devices received by the electronic device, but also the data collected by its own input / output interface 25, etc.

[0092] Furthermore, the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the mine microseismic composite early warning method disclosed above is implemented. For the specific steps of this method, reference can be made to the corresponding content disclosed in the foregoing embodiments, and details will not be repeated here.

[0093] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts between the various embodiments, reference can be made to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and reference can be made to the description of the method part for related parts.

[0094] Those skilled in the art may further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application. The steps of the methods or algorithms described in combination with the embodiments disclosed herein can be directly implemented by hardware, software modules executed by a processor, or a combination of both. The software modules can be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, removable disks, CD-ROM (Compact Disc-Read Only Memory), or any other form of storage medium known in the technical field.

[0095] Finally, it should also be noted that in this document, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0096] The above provides a detailed introduction to the solution provided by the present invention. Specific examples are used herein to elaborate on the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A mine microseismic composite early warning method, characterized in that, Including: Collecting current frequency data and current energy data of microseismic events in a mine based on a preset sliding time window, so as to generate a dynamic frequency warning threshold according to the frequency trend data of the current frequency data; Generating a dynamic energy warning threshold according to the historical energy statistical value of historical microseismic events in a preset statistical time for the same mine; wherein, the preset statistical time is dynamically updated according to the current time; Identifying a spatially dense area based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time, so as to obtain the clustering area of the microseismic events; Judging whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area; If not, then carry out mine microseismic warning.

2. The microseismic composite early warning method for mine according to claim 1, wherein The generating of the dynamic frequency warning threshold according to the frequency trend data of the current frequency data includes: Determining the frequency moving average value and frequency standard deviation of the microseismic events, and generating a dynamic frequency warning threshold based on the sum of the frequency moving average value and twice the frequency standard deviation.

3. The mine microseismic composite early warning method according to claim 1, wherein The generating of the dynamic energy warning threshold according to the historical energy statistical value of historical microseismic events in a preset statistical time for the same mine includes: Generating a corresponding dynamic single energy warning threshold and a dynamic total energy warning threshold respectively according to the historical energy maximum value and the corresponding first energy coefficient of historical microseismic events in a preset statistical time for the same mine, as well as the historical total energy statistical value and the corresponding second energy coefficient.

4. The mine microseismic composite early warning method according to claim 1, wherein, The identifying of the spatially dense area based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time, so as to obtain the clustering area of the microseismic events, includes: Obtaining the three-dimensional coordinates of the microseismic events on the geodetic space rectangular coordinate system; wherein, the geodetic space rectangular coordinate system takes the intersection point of the vertical plane where the prime meridian is located and the equatorial plane of the earth as the zero point, the x-axis represents the direction along the equatorial plane pointing to 90° east longitude, the y-axis represents the direction along the equatorial plane pointing to 90° north latitude, takes the sea level as the zero point of the z-axis direction, and the z-axis represents the direction from the sea level pointing to the center of the earth; Taking each of the microseismic events as a microseismic point, and performing spatial dense area identification processing on each of the microseismic points through a density clustering algorithm according to a preset neighborhood radius, a preset microseismic point number threshold, and the three-dimensional coordinates of the microseismic point, so as to obtain the clustering area of the microseismic events.

5. The mine microseismic composite early warning method according to claim 4, wherein Before judging whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area, further includes: Taking the current frequency data as the first microseismic parameter, taking the current energy data as the second microseismic parameter, counting the total frequency data of microseismic events in the clustering area as the third microseismic parameter, counting the regional energy value of microseismic events in the clustering area as the fourth microseismic data, and counting the current average depth mean value and historical average depth mean value of the z coordinate in the three-dimensional coordinates of microseismic events in the clustering area as the fifth microseismic data.

6. The mine microseismic composite early warning method according to claim 5, wherein, The judging whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area includes: Judging whether the first microseismic parameter is less than the dynamic frequency warning threshold to obtain a first warning judgment result; Judging whether the second microseismic parameter is less than the dynamic energy warning threshold to obtain a second warning judgment result; Judging whether the third microseismic parameter is less than the microseismic event experience threshold to obtain a third warning judgment result; Judging whether the fourth microseismic parameter is less than the clustering energy threshold to obtain a fourth warning judgment result; Judging whether the fifth microseismic parameter is less than the depth deviation threshold to obtain a fifth warning judgment result; Correspondingly, the if not, then carrying out mine microseismic warning includes: If there is any one or several warning judgment results greater than the corresponding threshold, then carry out the corresponding type of mine microseismic warning.

7. The mine microseismic composite early warning method according to any one of claims 1 to 6, characterized in that, It also includes: If each of the microseismic parameters is less than the corresponding threshold, then prohibit mine microseismic warning.

8. A mine microseismic composite early warning device, characterized in that, It includes: A first dynamic threshold generation module, configured to collect the current frequency data and current energy data of microseismic events in a mine based on a preset sliding time window, and generate a dynamic frequency warning threshold according to the frequency trend data of the current frequency data; A second dynamic threshold generation module, configured to generate a dynamic energy warning threshold according to the historical energy statistical value of historical microseismic events in the same mine within a preset statistical time; wherein, the preset statistical time is dynamically updated according to the current time; A clustering module, configured to identify a space dense area based on the three-dimensional coordinates of the microseismic events and according to the spatial distribution density and continuity conditions of the microseismic time, so as to obtain the clustering area of the microseismic events; A composite judgment module, configured to judge whether each microseismic parameter of the microseismic events in the clustering area is respectively less than the corresponding dynamic frequency warning threshold, the dynamic energy warning threshold, the microseismic event experience threshold of the clustering area, the clustering energy threshold of the clustering area, and the depth deviation threshold of the clustering area; An early warning module, configured to, if not, then carry out mine microseismic warning.

9. An electronic device, characterized in that, It includes: A memory, configured to store a computer program; A processor, configured to execute the computer program to implement the steps of the mine microseismic composite warning method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, For storing a computer program; wherein, when the computer program is executed by the processor, the steps of the mine microseismic composite warning method according to any one of claims 1 to 7 are implemented.

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