Coal mine geological disaster monitoring and early warning method and system

Abstract

The invention relates to a coal mine geological disaster monitoring and early warning method and system. Relates to the technical field of intelligent mines, and comprises the following steps: obtaining a blasting plan, extracting blasting time information in the blasting plan, and setting pre-sampling time according to the blasting time information; background bottom noise waveform data are acquired and stored according to the pre-sampling time, and background bottom noise features are acquired according to background bottom noise waveforms; extracting blasting vibration waveform data according to the blasting time information, and continuously monitoring post-blasting vibration data after blasting is finished; extracting vibration characteristics in the vibration data after blasting, comparing the vibration characteristics with background noise characteristics, and judging whether abnormal characteristic components exist or not; according to the method, pre-acquisition is carried out before blasting, background bottom noise waveform data generated during operation of equipment and personnel in a mining area are obtained, and components of frequencies in the background bottom noise waveform data are taken as reference samples for geological seismic wave filtering, so that more accurate geological seismic wave signals and post-blasting vibration signals are obtained.

Description

Technical Field

[0001] The present application relates to the field of intelligent mining technology, and in particular to a method and system for monitoring and early warning of geological disasters in coal mines. Background Art

[0002] Mine geological hazards are a significant safety hazard in the mining industry. Their occurrence is often linked to a variety of factors, including the geological structure, topographical characteristics, and human activities within the mining area. These hazards not only threaten the lives of mine workers but can also cause severe damage to the surrounding environment, leading to significant economic losses. Therefore, accurately predicting the risk of mine geological hazards is crucial for ensuring safe mine production and protecting the surrounding environment.

[0003] The existing invention patent with publication number CN120375553A discloses a mining area geological disaster monitoring and early warning system and method, wherein the early warning system runs in each node of the geological disaster monitoring network. The nodes of the geological disaster monitoring network include mining area nodes, mining supervision area nodes and mine early warning data nodes. The early warning system includes a mining area data acquisition module, a data transmission module, a data processing module, an early warning analysis module and a cloud interaction module. In this way, a networked approach is adopted to connect mining enterprises, mining supervision departments and mining data early warning departments in series, so that the data between the three can be effectively updated and interacted, greatly improving the accuracy and timeliness of early warning of geological disasters in mining areas.

[0004] However, at present, mining still requires blasting to clear obstacles in the mining process. The high-frequency geological shock waves generated after blasting will affect the subsequent period of time. The vibration data collected by the system contains a variety of low-frequency noise and high-frequency noise, which seriously affects the accuracy of the system's prediction of geological disasters such as landslides and collapses. Summary of the Invention

[0005] Based on this, it is necessary to provide a coal mine geological disaster monitoring and early warning method and system that can provide early warning of earthquake disasters after blasting operations to address the above technical problems.

[0006] In a first aspect, the present application provides a method for monitoring and early warning of coal mine geological disasters, the method comprising: Obtain the blasting plan, extract the blasting time information in the blasting plan, and set the pre-sampling time according to the blasting time information; Acquire and store background noise waveform data according to the pre-sampling time, and obtain background noise characteristics according to the background noise waveform; Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after the blasting is completed; Extract vibration features from post-blasting vibration data, compare the vibration features with background noise features, and determine whether there are abnormal characteristic components; If yes, obtain GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset range; If so, an alarm message is output.

[0007] In one embodiment, the specific steps of obtaining a blasting plan, extracting blasting time information in the blasting plan, and setting a pre-sampling time according to the blasting time information include: Obtain the coordinates of the detonation point in the blasting plan, as well as the planned detonation time interval; The preset vibration sensors within the preset range around the detonation point position coordinates are marked, and several sampling time points are set before the starting time point of the planned detonation time interval and used as pre-sampling time.

[0008] In one embodiment, the specific steps of acquiring and storing background noise waveform data according to the pre-sampling time, and acquiring background noise characteristics according to the background noise waveform include: Sampling the preset vibration sensor marked at the pre-sampling time according to the pre-sampling time to obtain a plurality of background noise waveform data corresponding to the pre-sampling time; Perform FFT transformation on the background noise waveform data, count the amplitude data corresponding to each characteristic frequency band, and determine the first amplitude range according to the frequency of occurrence of the amplitude data.

[0009] In one embodiment, the unmarked preset vibration sensor is sampled at intervals according to the pre-sampling time to obtain a plurality of background noise correction waveform data corresponding to a portion of the pre-sampling time; Perform FFT transformation on the background noise correction waveform data, count the correction amplitude data corresponding to each correction characteristic frequency band, and determine the correction amplitude range based on the correction amplitude data; The first amplitude range and the corrected amplitude range are intersected to obtain the corrected amplitude range, and a correspondence is established between the corrected amplitude range and the characteristic frequency to obtain the background noise feature.

[0010] In one embodiment, the specific steps of extracting blasting vibration waveform data based on blasting time information and continuously monitoring post-blasting vibration data after the blasting is completed include: Obtaining the location of the detonation point according to the blasting plan, and obtaining the vibration sensor closest to the detonation point according to the location of the detonation point as a reference sensor for obtaining a reference blasting signal; Obtaining the geological seismic wave obtained by the reference sensor after the first blast as the reference original waveform; Perform FFT transformation on the original reference waveform, and digitally filter the transformed original reference waveform according to the background noise characteristics; The frequency components obtained after digital filtering are used as blasting vibration waveform data.

[0011] In one embodiment, the specific steps of extracting vibration features from post-blasting vibration data, comparing the vibration features with background noise features, and determining whether abnormal feature components exist include: Read the post-blasting vibration data continuously collected by the preset vibration sensor after the blasting is completed, and perform FFT transformation on the post-blasting vibration data to obtain vibration characteristics; The frequency characteristics contained in the background noise characteristics and the corresponding corrected amplitude range are used to filter the post-blasting vibration data; Determine whether blasting is completed when post-blasting vibration data is obtained; If not, the waveform after the primary filtering is subjected to secondary filtering according to the blasting vibration waveform data; Determine whether the waveform after secondary filtering still contains abnormal waveform components; If so, it means that there are abnormal characteristic components in the vibration characteristics; If not, it means that there is no abnormal characteristic component in the vibration characteristics.

[0012] In one embodiment, the specific steps of obtaining GNSS ranging data and determining whether a change in the GNSS ranging data exceeds a preset range include: Read the change value of the GNSS ranging data obtained at each sampling point; Determine whether the cumulative displacement of the change value exceeds the preset warning range.

[0013] In a second aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: Obtain the blasting plan, extract the blasting time information in the blasting plan, and set the pre-sampling time according to the blasting time information; Acquire and store background noise waveform data according to the pre-sampling time, and obtain background noise characteristics according to the background noise waveform; Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after the blasting is completed; Extract vibration features from post-blasting vibration data, compare the vibration features with background noise features, and determine whether there are abnormal characteristic components; If yes, obtain GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset range; If so, an alarm message is output.

[0014] In a third aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps: Obtain the blasting plan, extract the blasting time information in the blasting plan, and set the pre-sampling time according to the blasting time information; Acquire and store background noise waveform data according to the pre-sampling time, and obtain background noise characteristics according to the background noise waveform; Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after the blasting is completed; Extract vibration features from post-blasting vibration data, compare the vibration features with background noise features, and determine whether there are abnormal characteristic components; If yes, obtain GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset range; If so, an alarm message is output.

[0015] In a fourth aspect, the present application further provides a computer program product, the computer program product comprising a computer program, which, when executed by a processor, implements the following steps: Obtain the blasting plan, extract the blasting time information in the blasting plan, and set the pre-sampling time according to the blasting time information; Acquire and store background noise waveform data according to the pre-sampling time, and obtain background noise characteristics according to the background noise waveform; Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after the blasting is completed; Extract vibration features from post-blasting vibration data, compare the vibration features with background noise features, and determine whether there are abnormal characteristic components; If yes, obtain GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset range; If so, an alarm message is output.

[0016] The above-mentioned coal mine geological disaster monitoring and early warning method, device, computer equipment, storage medium and computer program product, through pre-collection before blasting, obtains background noise waveform data generated by equipment and personnel operations in the mining area, and uses the components of each frequency in the background noise waveform data as reference samples for geological seismic wave filtering, thereby obtaining more accurate geological seismic wave signals and post-blasting vibration signals, thereby judging whether there is an abnormality in the post-blasting vibration signal. If so, GNSS ranging is started to measure whether abnormal displacement occurs on the ground surface. If so, an alarm is output to realize early warning of secondary geological disasters after mine blasting. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Schematic diagram of the application environment of the coal mine geological disaster monitoring and early warning method in one embodiment; Figure 2 A schematic diagram of a process for monitoring and early warning of coal mine geological disasters in one embodiment; Figure 3 Schematic diagram of a specific process of step S200 in one embodiment; Figure 4 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0019] The coal mine geological disaster monitoring and early warning method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be integrated with server 104 or placed in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, industrial computers, workstations, and IoT devices. IoT devices can be devices such as vibration sensors and GNSS radars installed in coal mines. Server 104 can be implemented as a standalone server or a server cluster consisting of multiple servers.

[0020] In one embodiment, Figure 2 As shown, a coal mine geological disaster monitoring and early warning method is provided, which is applied to Figure 1 Taking the server 104 in the example as an example, the following steps are included: Step S100: Acquire a blasting plan, extract blasting time information in the blasting plan, and set a pre-sampling time according to the blasting time information.

[0021] Specifically, the steps of step S100 include: Step S110: Obtain the detonation point position coordinates and the planned detonation time interval in the blasting plan.

[0022] Among them, the blasting plan is the plan information manually input by the operator and is used to represent the next mining blasting operation. It includes the location coordinates of the blasting point, the planned detonation time interval, and the blasting point or number data; the planned detonation time interval is used to represent the time period in which the blasting task is performed. Since the specific time of the blasting is affected by many factors on site, a time interval that includes the specific blasting time can be set when inputting the blasting plan to indicate the time for performing the blasting task.

[0023] Step S120: Mark the preset vibration sensors within the preset range around the detonation point position coordinates, and set a number of sampling time points before the start time point of the planned detonation time interval as pre-sampling time points.

[0024] Among them, the sampling point time is the time used to control the preset vibration sensor to obtain ground vibration data in the mining area. The preset vibration sensors in the mining area are marked according to their position coordinates with the blasting point. The preset range is a pre-input or pre-set constant representing the distance. In a specific example, the preset range is a circular area with the position coordinates of the blasting point as the center and the constant representing the distance as the radius. When the blasting point is not unique, the preset distance is a continuous area connected by multiple aforementioned circular areas. The vibration sensors within the preset area are marked, and the preset vibration sensors outside the preset area are not marked. Different sampling strategies are also adopted during subsequent sampling.

[0025] Step S200: Acquire and store background noise waveform data according to the pre-sampling time, and acquire background noise features according to the background noise waveform.

[0026] Specifically, the specific steps of step S200 are as follows: Figure 3 As shown, including: Step S210 : sampling the preset vibration sensor marked with the pre-sampling time according to the pre-sampling time to obtain a plurality of background noise waveform data corresponding to the pre-sampling time.

[0027] In a specific embodiment, the pre-sampling time is set to 15 minutes before the start time of the preset blasting time interval, and the pre-sampling time is determined at a frequency of once per minute. For example, if the start time of the preset blasting time interval is 10:25 in the morning, the pre-sampling time is 10:10 as the first sampling time, a pre-sampling time is set every one minute, and the last pre-sampling is performed at 10:24. The duration of each sampling is set to 10 seconds, that is, sampling starts when each pre-sampling time arrives, and ground vibration data within 10 seconds is continuously collected as background noise waveform data. The purpose of setting up pre-sampling is that since the ground environment at the mining site is relatively complex, in addition to normal low-frequency geological seismic waves, it also includes weak geological seismic waves generated by mining equipment and construction personnel during operation. When collecting relevant data, these low-frequency geological seismic waves will affect the collection of high-frequency geological seismic waves. Therefore, in the embodiment of the present application, a pre-sampling step is adopted, and multiple pre-samplings before blasting are performed to collect the background noise of the ground or slope in the mining area and use it as a sample to provide a basis for filtering processing for subsequent processing of geological seismic waves.

[0028] Step S220: performing FFT transformation on the background noise waveform data, collecting statistics on the amplitude data corresponding to each characteristic frequency band, and determining a first amplitude range according to the occurrence frequency of the amplitude data.

[0029] Since there are differences in the amplitudes corresponding to the frequency components in the multiple background noise waveform data collected through step S210, the amplitudes corresponding to the frequency components of the pre-sampling data obtained by all marked seismic sensors after FFT transformation can be statistically analyzed, and the intervals where the highest amplitude and the lowest amplitude are located can be taken out for interception to obtain the first amplitude range. In a specific example, the closed interval consisting of the highest amplitude and the lowest amplitude can be taken as the first amplitude range.

[0030] Step S230 : performing interval sampling on the unmarked preset vibration sensors according to the pre-sampling time to obtain a plurality of background noise correction waveform data corresponding to a portion of the pre-sampling time.

[0031] Step S240: performing FFT transformation on the background noise correction waveform data, calculating the correction amplitude data corresponding to each correction characteristic frequency band, and determining the correction amplitude range according to the correction amplitude data; Step S260: finding the intersection of the first amplitude range and the corrected amplitude range to obtain a corrected amplitude range, and establishing a correspondence between the corrected amplitude range and the characteristic frequency to obtain background noise characteristics.

[0032] Step S300: extracting blasting vibration waveform data based on blasting time information, and continuously monitoring post-blasting vibration data after the blasting is completed.

[0033] In one embodiment, the specific steps of step S300 include: Step S310: obtaining the location of the detonation point according to the blasting plan, and obtaining the vibration sensor closest to the detonation point as a reference sensor for obtaining a reference blasting signal according to the location of the detonation point; Step S320: obtaining the geological seismic wave acquired by the reference sensor after the first blast as the reference original waveform; Step S330: performing FFT transformation on the reference original waveform, and digitally filtering the transformed reference original waveform according to background noise characteristics; Step S340: The frequency components obtained after digital filtering are used as blasting vibration waveform data.

[0034] Step S400: extracting vibration features from the post-blasting vibration data, comparing the vibration features with background noise features, and determining whether there are abnormal feature components.

[0035] In one embodiment, the specific steps of step S400 include: Step S410: reading post-blasting vibration data continuously collected by a preset vibration sensor after the blasting is completed, and performing FFT transformation on the post-blasting vibration data to obtain vibration characteristics; Step S420: filtering the post-blasting vibration data using the frequency characteristics and the corresponding corrected amplitude range contained in the background noise characteristics; Step S430: determining whether blasting is completed when post-blasting vibration data is obtained; Step S440: If not, the waveform after the primary filtering is subjected to secondary filtering according to the blasting vibration waveform data.

[0036] Step S450: determining whether the waveform after secondary filtering still contains abnormal waveform components; Step S460: If yes, it means that there are abnormal characteristic components in the vibration characteristics; Step S470: If not, it means that there is no abnormal characteristic component in the vibration characteristics.

[0037] Step S500: If yes, obtain GNSS distance measurement data and determine whether the change value of the GNSS distance measurement data exceeds a preset range.

[0038] In one embodiment, the specific steps of step S500 include: Step S510: reading the change value of the GNSS ranging data obtained at each sampling point; Step S520: Determine whether the accumulated displacement of the change value exceeds a preset warning range.

[0039] Step S600: If yes, output warning information.

[0040] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0041] Based on the same inventive concept, the embodiments of the present application also provide a coal mine geological disaster monitoring and early warning system for implementing the above-mentioned coal mine geological disaster monitoring and early warning method. The implementation solution provided by this device is similar to the implementation solution described in the above-mentioned method. Therefore, the specific limitations in one or more coal mine geological disaster monitoring and early warning system embodiments provided below can be referred to the limitations of the coal mine geological disaster monitoring and early warning method above, and will not be repeated here.

[0042] In one embodiment, a coal mine geological disaster monitoring and early warning system is provided. The system can be a terminal, and its internal structure diagram can be as follows: Figure 4 As shown. The computer device includes a processor, memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal via wired or wireless communication. The wireless communication can be achieved via Wi-Fi, a mobile cellular network, NFC (near-field communication), or other technologies. The computer program is executed by the processor to implement a method for monitoring and early warning of coal mine geological disasters. The display screen of the computer device can be a liquid crystal display or an electronic ink display. The input device of the computer device can be a touch layer covering the display screen, keys, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse.

[0043] Each module in the above-mentioned coal mine geological disaster monitoring and early warning system can be implemented in whole or in part through software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor of the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each of the above modules.

[0044] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0045] In one embodiment, a coal mine geological disaster monitoring and early warning system is provided, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: Step S100: obtaining a blasting plan, extracting blasting time information from the blasting plan, and setting a pre-sampling time according to the blasting time information; Step S200: acquiring and storing background noise waveform data according to the pre-sampling time, and acquiring background noise characteristics according to the background noise waveform; Step S300: extracting blasting vibration waveform data based on blasting time information, and continuously monitoring post-blasting vibration data after the blasting is completed; Step S400: extracting vibration features from the post-blasting vibration data, comparing the vibration features with background noise features, and determining whether there are abnormal feature components; Step S500: If yes, obtain GNSS distance measurement data and determine whether the change value of the GNSS distance measurement data exceeds a preset range; Step S600: If yes, output warning information.

[0046] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: Step S100: obtaining a blasting plan, extracting blasting time information in the blasting plan, and setting a pre-sampling time according to the blasting time information; Step S200: acquiring and storing background noise waveform data according to the pre-sampling time, and acquiring background noise characteristics according to the background noise waveform; Step S300: extracting blasting vibration waveform data based on blasting time information, and continuously monitoring post-blasting vibration data after the blasting is completed; Step S400: extracting vibration features from the post-blasting vibration data, comparing the vibration features with background noise features, and determining whether there are abnormal feature components; Step S500: If yes, obtain GNSS distance measurement data and determine whether the change value of the GNSS distance measurement data exceeds a preset range; Step S600: If yes, output warning information.

[0047] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps: Step S100: obtaining a blasting plan, extracting blasting time information in the blasting plan, and setting a pre-sampling time according to the blasting time information; Step S200: acquiring and storing background noise waveform data according to the pre-sampling time, and acquiring background noise characteristics according to the background noise waveform; Step S300: extracting blasting vibration waveform data based on blasting time information, and continuously monitoring post-blasting vibration data after the blasting is completed; Step S400: extracting vibration features from the post-blasting vibration data, comparing the vibration features with background noise features, and determining whether there are abnormal feature components; Step S500: If yes, obtain GNSS distance measurement data and determine whether the change value of the GNSS distance measurement data exceeds a preset range; Step S600: If yes, output warning information.

[0048] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0049] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0050] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A coal mine geological disaster monitoring and early warning method, characterized in that: The method comprises: Obtain the blasting plan, extract the blasting time information in the blasting plan, and set the pre-sampling time according to the blasting time information; Acquire and store background noise waveform data according to the pre-sampling time, and acquire background noise characteristics according to the background noise waveform; Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after the blasting is completed; Extract vibration features from post-blasting vibration data, compare the vibration features with background noise features, and determine whether there are abnormal characteristic components; If yes, obtain GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset range; If so, an alarm message is output.

2. A coal mine geological disaster monitoring and early warning method according to claim 1, characterized in that: The specific steps of obtaining the blasting plan, extracting the blasting time information in the blasting plan, and setting the pre-sampling time according to the blasting time information include: Obtaining the coordinates of the detonation point and the planned detonation time interval in the blasting plan; The preset vibration sensors within the preset range around the detonation point position coordinates are marked, and several sampling time points are set before the starting time point of the planned detonation time interval and used as pre-sampling time.

3. A coal mine geological disaster monitoring and early warning method according to claim 2, characterized in that: The specific steps of acquiring and storing background noise waveform data according to the pre-sampling time, and acquiring background noise characteristics according to the background noise waveform include: Sampling the preset vibration sensor marked with the pre-sampling time according to the pre-sampling time to obtain a plurality of background noise waveform data corresponding to the pre-sampling time; Perform FFT transformation on the background noise waveform data, collect statistics on amplitude data corresponding to each characteristic frequency band, and determine a first amplitude range according to the occurrence frequency of the amplitude data.

4. A coal mine geological disaster monitoring and early warning method according to claim 3, characterized in that: performing interval sampling on the unmarked preset vibration sensor according to the pre-sampling time to obtain a plurality of background noise correction waveform data corresponding to part of the pre-sampling time; Performing FFT transformation on the background noise correction waveform data, counting the correction amplitude data corresponding to each correction characteristic frequency band, and determining the correction amplitude range according to the correction amplitude data; The first amplitude range and the corrected amplitude range are intersected to obtain a corrected amplitude range, and a corresponding relationship is established between the corrected amplitude range and the characteristic frequency to obtain the background noise feature.

5. A coal mine geological disaster monitoring and early warning method according to claim 4, characterized in that: The specific steps of extracting blasting vibration waveform data based on blasting time information and continuously monitoring post-blasting vibration data after blasting are as follows: Acquiring a detonation point location according to the blasting plan, and acquiring the vibration sensor closest to the detonation point as a reference sensor for acquiring a reference blasting signal based on the detonation point location; Obtaining the geological seismic wave obtained by the reference sensor after the first blast as a reference original waveform; Performing an FFT transformation on the reference original waveform, and digitally filtering the transformed reference original waveform according to the background noise characteristics; The frequency components obtained after digital filtering are used as blasting vibration waveform data.

6. A coal mine geological disaster monitoring and early warning method according to claim 5, characterized in that: The specific steps of extracting vibration features from post-blasting vibration data, comparing the vibration features with background noise features, and determining whether abnormal feature components exist include: Reading post-blasting vibration data continuously collected by the preset vibration sensor after the blasting is completed, and performing FFT transformation on the post-blasting vibration data to obtain vibration characteristics; Filtering the post-blasting vibration data using the frequency characteristics and the corresponding corrected amplitude range contained in the background noise characteristics; determining whether blasting is completed when the post-blasting vibration data is obtained; If not, the waveform after the primary filtering is subjected to secondary filtering according to the blasting vibration waveform data; Determine whether the waveform after secondary filtering still contains abnormal waveform components; If so, it means that there are abnormal characteristic components in the vibration characteristics; If not, it means that there is no abnormal characteristic component in the vibration characteristics.

7. A coal mine geological disaster monitoring and early warning method according to claim 6, characterized in that: The specific steps of obtaining GNSS ranging data and determining whether the change value of the GNSS ranging data exceeds a preset range include: Read the change value of the GNSS ranging data obtained at each sampling point; Determine whether the cumulative displacement of the change value exceeds a preset warning range.

8. A coal mine geological disaster monitoring and early warning system, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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