A method and system for monitoring and early warning of geological disasters in coal mines

Abstract

This application relates to a method and system for monitoring and early warning of geological disasters in coal mines. It pertains to the field of intelligent mining technology and includes: acquiring a blasting plan; extracting blasting time information from the blasting plan; and setting a pre-sampling time based on the blasting time information; acquiring and storing background noise waveform data based on the pre-sampling time, and obtaining background noise features based on the background noise waveform; extracting blasting vibration waveform data based on the blasting time information, and continuously monitoring post-blasting vibration data after blasting; extracting vibration features from the post-blasting vibration data, comparing the vibration features with background noise features, and determining whether there are any abnormal feature components; performing pre-collection before blasting to acquire background noise waveform data including data generated by equipment and personnel operating within the mining area, and using 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.

Description

Technical Field

[0001] This 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 Technology

[0002] Mine geological hazards are a significant safety risk that cannot be ignored during mining development. Their occurrence is often related to a variety of factors, including the geological structure, topography, and human activities of the mining area. These hazards not only threaten the lives of miners but can also cause severe damage to the surrounding environment, leading to substantial economic losses. Therefore, accurately predicting mine geological hazard risks is of great importance for ensuring safe mine production and protecting the surrounding environment.

[0003] An existing invention patent with publication number CN120375553A discloses a geological disaster monitoring and early warning system and method for mining areas. The early warning system operates in various nodes of a geological disaster monitoring network, which includes mining area nodes, mining supervision area nodes, and mining 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. This network-based approach connects mining enterprises, mining supervision departments, and mining data early warning departments, enabling effective data updates and interactions among the three parties, significantly improving the accuracy and timeliness of early warnings for geological disasters in mining areas.

[0004] However, blasting is still required to remove obstacles during mining operations. The high-frequency geological shock waves generated after blasting will affect the system for a period of time. The vibration data packets collected by the system contain various low-frequency and high-frequency noises, which seriously affect the accuracy of the system's prediction of geological disasters such as landslides and collapses. Summary of the Invention

[0005] Therefore, 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, addressing the aforementioned technical problems.

[0006] Firstly, this application provides a method for monitoring and early warning of geological disasters in coal mines, the method comprising:

[0007] Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information;

[0008] Background noise waveform data is acquired and stored based on the pre-sampling time, and background noise features are obtained based on the background noise waveform.

[0009] Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting;

[0010] Extract vibration features from post-blast vibration data, compare vibration features with background noise features, and determine whether there are any abnormal feature components.

[0011] If so, acquire GNSS ranging data and determine whether the change in GNSS ranging data exceeds the preset warning range;

[0012] If so, output an alarm message.

[0013] In one embodiment, the specific steps of obtaining the blasting plan, extracting the blasting time information from the blasting plan, and setting the pre-sampling time based on the blasting time information include:

[0014] Obtain the coordinates of the detonation point in the demolition plan, as well as the planned detonation time interval;

[0015] Pre-set vibration sensors within a preset range around the detonation point coordinates are marked, and several sampling time points are set before the start time of the planned detonation time interval, which are used as the pre-sampling time.

[0016] In one embodiment, the specific steps of acquiring and storing background noise waveform data based on the pre-sampling time, and obtaining background noise features based on the background noise waveform, include:

[0017] The marked preset vibration sensor is sampled according to the pre-sampling time to obtain several background noise waveform data corresponding to the pre-sampling time;

[0018] 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 based on the frequency of occurrence of the amplitude data.

[0019] In one embodiment, the unmarked preset vibration sensor is sampled at intervals according to the pre-sampling time to obtain a number of background noise correction waveform data corresponding to a portion of the pre-sampling time;

[0020] Perform FFT transformation on the background noise correction waveform data, statistically analyze the correction amplitude data corresponding to each correction characteristic frequency band, and determine the correction amplitude range based on the correction amplitude data;

[0021] Find the intersection of the first amplitude range and the corrected amplitude range to obtain the corrected amplitude range, and establish a correspondence between the corrected amplitude range and the characteristic frequency to obtain the background noise characteristics.

[0022] In one embodiment, the specific steps for extracting blasting vibration waveform data based on blasting time information and continuously monitoring post-blasting vibration data after blasting include:

[0023] The location of the detonation point is obtained according to the blasting plan, and the vibration sensor closest to the detonation point is selected as the reference sensor for obtaining the reference blasting signal.

[0024] The geological seismic waves acquired by the reference sensor after the first blast were used as the reference raw waveform;

[0025] The original reference waveform is subjected to FFT transformation, and the transformed original reference waveform is digitally filtered according to the background noise characteristics.

[0026] The frequency components obtained after digital filtering are used as blasting vibration waveform data.

[0027] In one embodiment, the specific steps for extracting vibration features from post-blast vibration data, comparing the vibration features with background noise features, and determining whether there are any abnormal feature components include:

[0028] Read the post-blast vibration data continuously collected by the preset vibration sensor after the blasting is completed, and perform FFT transformation on the post-blast vibration data to obtain vibration characteristics;

[0029] The frequency features contained in the background noise characteristics and the corresponding corrected amplitude range are used to filter the post-blast vibration data.

[0030] Determine whether the blasting has ended when the post-blasting vibration data is obtained;

[0031] If not, then the waveform after the first filtering is filtered a second time based on the blasting vibration waveform data;

[0032] Determine whether the waveform after secondary filtering still contains abnormal waveform components;

[0033] If so, it indicates that there are abnormal characteristic components in the vibration characteristics;

[0034] If not, it means that there are no abnormal feature components in the vibration characteristics.

[0035] In one embodiment, the specific steps for acquiring GNSS ranging data and determining whether the change in the GNSS ranging data exceeds a preset warning range include:

[0036] Read the change value of the GNSS ranging data obtained at each sampling point;

[0037] Determine whether the cumulative displacement of the changed value exceeds the preset warning range.

[0038] Secondly, this application also provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0039] Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information;

[0040] Background noise waveform data is acquired and stored based on the pre-sampling time, and background noise features are obtained based on the background noise waveform.

[0041] Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting;

[0042] Extract vibration features from post-blast vibration data, compare vibration features with background noise features, and determine whether there are any abnormal feature components.

[0043] If so, acquire GNSS ranging data and determine whether the change in GNSS ranging data exceeds the preset warning range;

[0044] If so, output an alarm message.

[0045] Thirdly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0046] Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information;

[0047] Background noise waveform data is acquired and stored based on the pre-sampling time, and background noise features are obtained based on the background noise waveform.

[0048] Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting;

[0049] Extract vibration features from post-blast vibration data, compare vibration features with background noise features, and determine whether there are any abnormal feature components.

[0050] If so, acquire GNSS ranging data and determine whether the change in GNSS ranging data exceeds the preset warning range;

[0051] If so, output an alarm message.

[0052] Fourthly, this application also provides a computer program product comprising a computer program that, when executed by a processor, performs the following steps:

[0053] Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information;

[0054] Background noise waveform data is acquired and stored based on the pre-sampling time, and background noise features are obtained based on the background noise waveform.

[0055] Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting;

[0056] Extract vibration features from post-blast vibration data, compare vibration features with background noise features, and determine whether there are any abnormal feature components.

[0057] If so, acquire GNSS ranging data and determine whether the change in GNSS ranging data exceeds the preset warning range;

[0058] If so, output an alarm message.

[0059] The aforementioned coal mine geological disaster monitoring and early warning methods, devices, computer equipment, storage media, and computer program products acquire background noise waveform data generated by equipment and personnel during operations within the mining area before blasting. The components of each frequency in the background noise waveform data are used as reference samples for geological seismic wave filtering, thereby obtaining more accurate geological seismic wave signals and post-blasting vibration signals. This allows for the determination of whether there are any abnormalities in the post-blasting vibration signals. If so, GNSS ranging is activated to measure whether abnormal displacement has occurred on the ground surface. If so, an alarm is output, thus achieving early warning of secondary geological disasters after mine blasting. Attached Figure Description

[0060] Figure 1 This is an application environment diagram of the coal mine geological disaster monitoring and early warning method in one embodiment;

[0061] Figure 2 This is a flowchart illustrating a method for monitoring and early warning of geological disasters in coal mines in one embodiment;

[0062] Figure 3 This is a schematic diagram of the specific process of step S200 in one embodiment;

[0063] Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0065] The coal mine geological disaster monitoring and early warning method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located 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 include vibration sensors, GNSS radar, etc., installed in coal mines. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0066] In one embodiment, such as Figure 2 As shown, a method for monitoring and early warning of geological disasters in coal mines is provided, and this method is applied to... Figure 1 Taking server 104 as an example, the following steps are included:

[0067] Step S100: Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information.

[0068] Specifically, the steps in step S100 include:

[0069] Step S110: Obtain the coordinates of the detonation point in the blasting plan, as well as the planned detonation time interval.

[0070] The blasting plan is a set of information manually entered by the operator to indicate the next mining blasting operation. It includes the location coordinates of the blasting point, the planned detonation time interval, and the data on the blasting point location or number of blasts. The planned detonation time interval is used to indicate the time segment in which the blasting task will be carried out. Since the specific time of blasting is affected by many factors on site, a time interval that includes the specific time of blasting can be set when entering the blasting plan, so as to indicate the time of blasting task execution.

[0071] Step S120: Mark the preset vibration sensors within a preset range around the detonation point location coordinates, and set several sampling time points before the start time point of the planned detonation time interval, which will be used as the pre-sampling time.

[0072] The sampling point time is used to control the time for the preset vibration sensors to acquire ground vibration data within the mining area. The preset vibration sensors within the mining area are marked according to their coordinates relative to the detonation point. The preset range is a pre-input or pre-set constant representing distance. In a specific example, the preset range is a circular area with the detonation point's coordinates as the center and the constant representing distance as the radius. When the blasting point is not unique, the preset range is a continuous area formed by connecting multiple of the aforementioned circular areas. Vibration sensors within the preset range are marked, while those outside the preset range are not marked. Different sampling strategies are also adopted during subsequent sampling.

[0073] Step S200: Obtain and store background noise waveform data based on the pre-sampling time, and obtain background noise features based on the background noise waveform.

[0074] Specifically, the specific steps of step S200 are as follows: Figure 3 As shown, it includes:

[0075] Step S210: The pre-marked vibration sensor is sampled according to the pre-sampling time to obtain several background noise waveform data corresponding to the pre-sampling time.

[0076] In one 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 AM, then the pre-sampling time is set at 10:10 AM as the first sampling time, and a pre-sampling time is set every minute, with the last pre-sampling at 10:24 AM. The duration of each sampling is set to 10 seconds, that is, sampling begins 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, due to the complex ground environment in the mining area, in addition to normal low-frequency geological seismic waves, there are also weak geological seismic waves generated by mining equipment and construction personnel. When collecting relevant data, these low-frequency geological seismic waves will affect the collection of high-frequency geological seismic waves. Therefore, in this embodiment, a pre-sampling step is adopted to collect the background noise of the ground or slope in the mining area through multiple pre-sampling before blasting and use it as a sample to provide a basis for filtering the geological seismic waves in subsequent processing.

[0077] Step S220: 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 based on the frequency of occurrence of the amplitude data.

[0078] Since the amplitudes of each frequency component in the multiple background noise waveform data acquired in step S210 are different, the amplitudes of each frequency component after FFT transformation of the pre-sampled data obtained by all marked seismic sensors can be statistically analyzed, and the interval containing the highest and lowest amplitudes can be extracted to obtain the first amplitude range. In a specific example, the closed interval formed by the highest and lowest amplitudes can be taken as the first amplitude range.

[0079] Step S230: The unmarked preset vibration sensor is sampled at intervals according to the pre-sampling time to obtain a number of background noise correction waveform data corresponding to a portion of the pre-sampling time.

[0080] Step S240: 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;

[0081] Step S250: Find the intersection of the first amplitude range and the corrected amplitude range to obtain the corrected amplitude range, and establish a correspondence between the corrected amplitude range and the characteristic frequency to obtain the background noise feature.

[0082] Step S300: Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting.

[0083] In one embodiment, step S300 specifically includes the following steps:

[0084] Step S310: Obtain the location of the detonation point according to the blasting plan, and obtain the vibration sensor closest to the detonation point as the reference sensor for obtaining the reference blasting signal.

[0085] Step S320: Obtain the geological seismic wave acquired by the reference sensor after the first blast as the reference raw waveform;

[0086] Step S330: Perform FFT transformation on the original reference waveform, and perform digital filtering on the transformed original reference waveform based on the background noise characteristics;

[0087] Step S340: Use the frequency components obtained after digital filtering as the blasting vibration waveform data.

[0088] Step S400: Extract vibration features from the post-blasting vibration data, compare the vibration features with the background noise features, and determine whether there are any abnormal feature components.

[0089] In one embodiment, step S400 specifically includes the following steps:

[0090] Step S410: Read the post-blast vibration data continuously collected by the preset vibration sensor after the blasting is completed, and perform FFT transformation on the post-blast vibration data to obtain vibration characteristics;

[0091] Step S420: Filter the post-blasting vibration data once using the frequency features contained in the background noise features and the corresponding corrected amplitude range;

[0092] Step S430: Determine whether the blasting has ended when the post-blasting vibration data is obtained;

[0093] Step S440: If not, perform a second filtering on the waveform after the first filtering based on the blasting vibration waveform data.

[0094] Step S450: Determine whether the waveform after secondary filtering still contains abnormal waveform components;

[0095] Step S460: If yes, it indicates that there are abnormal feature components in the vibration characteristics;

[0096] Step S470: If not, it means that there are no abnormal feature components in the vibration characteristics.

[0097] Step S500: If yes, acquire GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset warning range.

[0098] In one embodiment, step S500 specifically includes the following steps:

[0099] Step S510: Read the change value of the GNSS ranging data obtained at each sampling point;

[0100] Step S520: Determine whether the cumulative displacement of the change value exceeds the preset warning range.

[0101] Step S600: If yes, output alarm information.

[0102] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0103] Based on the same inventive concept, this application also provides a coal mine geological disaster monitoring and early warning system for implementing the coal mine geological disaster monitoring and early warning method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more coal mine geological disaster monitoring and early warning system embodiments provided below can be found in the limitations of the coal mine geological disaster monitoring and early warning method described above, and will not be repeated here.

[0104] In one embodiment, a coal mine geological disaster monitoring and early warning system is provided. This 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, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, 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 geological disasters in coal mines. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0105] Each module in the aforementioned coal mine geological disaster monitoring and early warning system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0106] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0107] 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 the processor executes the computer program to perform the following steps:

[0108] Step S100: Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information;

[0109] Step S200: Obtain and store background noise waveform data based on the pre-sampling time, and obtain background noise features based on the background noise waveform;

[0110] Step S300: Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting;

[0111] Step S400: Extract vibration features from the post-blasting vibration data, compare the vibration features with the background noise features, and determine whether there are any abnormal feature components.

[0112] Step S500: If yes, then acquire GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset warning range;

[0113] Step S600: If yes, output alarm information.

[0114] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0115] Step S100: Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information;

[0116] Step S200: Obtain and store background noise waveform data based on the pre-sampling time, and obtain background noise features based on the background noise waveform;

[0117] Step S300: Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting;

[0118] Step S400: Extract vibration features from the post-blasting vibration data, compare the vibration features with the background noise features, and determine whether there are any abnormal feature components.

[0119] Step S500: If yes, then acquire GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset warning range;

[0120] Step S600: If yes, output alarm information.

[0121] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0122] Step S100: Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information;

[0123] Step S200: Obtain and store background noise waveform data based on the pre-sampling time, and obtain background noise features based on the background noise waveform;

[0124] Step S300: Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting;

[0125] Step S400: Extract vibration features from the post-blasting vibration data, compare the vibration features with the background noise features, and determine whether there are any abnormal feature components.

[0126] Step S500: If yes, then acquire GNSS ranging data and determine whether the change value of the GNSS ranging data exceeds the preset warning range;

[0127] Step S600: If yes, output alarm information.

[0128] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, 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 many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0129] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0130] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for monitoring and early warning of geological disasters in coal mines, characterized in that, The method includes: Obtain the blasting plan, extract the blasting time information from the blasting plan, and set the pre-sampling time based on the blasting time information; Background noise waveform data is acquired and stored based on the pre-sampling time, and background noise features are obtained based on the background noise waveform. Extract blasting vibration waveform data based on blasting time information, and continuously monitor post-blasting vibration data after blasting; Extract vibration features from post-blast vibration data, compare vibration features with background noise features, and determine whether there are any abnormal feature components. If so, acquire GNSS ranging data and determine whether the change in GNSS ranging data exceeds the preset warning range; If so, output an alarm message; The specific steps of obtaining the blasting plan, extracting the blasting time information from the blasting plan, and setting the pre-sampling time based on the blasting time information include: Obtain the coordinates of the detonation point in the blasting plan, as well as the planned detonation time interval; Preset vibration sensors within a preset range around the coordinates of the detonation point are marked, and several sampling time points are set before the start time of the planned detonation time interval, which are used as the pre-sampling time. The specific steps of acquiring and storing background noise waveform data based on the pre-sampling time, and obtaining background noise features based on the background noise waveform, include: The preset vibration sensor marked with the pre-sampling time is sampled according to the pre-sampling time to obtain a number of background noise waveform data corresponding to the pre-sampling time; Perform an FFT transformation on the background noise waveform data, count the amplitude data corresponding to each characteristic frequency band, and determine the first amplitude range based on the frequency of occurrence of the amplitude data. The unmarked preset vibration sensor is sampled at intervals according to the pre-sampling time to obtain a number of background noise correction waveform data corresponding to a portion of the pre-sampling time; Perform an FFT transform on the background noise correction waveform data, statistically analyze the correction amplitude data corresponding to each correction feature frequency band, and determine the correction amplitude range based on the correction amplitude data. The intersection of the first amplitude range and the corrected amplitude range is used to obtain the corrected amplitude range. The corrected amplitude range is then correlated with the characteristic frequency to obtain the background noise feature.

2. The method for monitoring and early warning of geological disasters in coal mines according to claim 1, characterized in that, The specific steps for extracting blasting vibration waveform data based on blasting time information and continuously monitoring post-blasting vibration data after blasting include: The location of the detonation point is obtained according to the blasting plan, and the vibration sensor closest to the detonation point is obtained as the reference sensor for obtaining the reference blasting signal. The geological seismic waves acquired by the reference sensor after the first blast were used as the reference original waveform; The original reference waveform is subjected to FFT transformation, and the transformed original reference waveform is digitally filtered according to the background noise characteristics. The frequency components obtained after digital filtering are used as blasting vibration waveform data.

3. The method for monitoring and early warning of geological disasters in coal mines according to claim 2, characterized in that, The specific steps for extracting vibration features from post-blast vibration data, comparing vibration features with background noise features, and determining whether there are abnormal feature components include: Read the post-blast vibration data continuously collected by the preset vibration sensor after the blasting is completed, and perform FFT transformation on the post-blast vibration data to obtain vibration characteristics; The frequency features contained in the background noise characteristics and the corresponding corrected amplitude range are used to filter the post-blast vibration data once. Determine whether the blasting has ended when the post-blasting vibration data is obtained; If not, then the waveform after the first filtering is filtered a second time based on the blasting vibration waveform data; Determine whether the waveform after secondary filtering still contains abnormal waveform components; If so, it indicates that there are abnormal characteristic components in the vibration characteristics; If not, it means that there are no abnormal feature components in the vibration characteristics.

4. The method for monitoring and early warning of geological disasters in coal mines according to claim 3, characterized in that, The specific steps for acquiring GNSS ranging data and determining whether the change in GNSS ranging data exceeds the preset warning range include: Read the change value of the GNSS ranging data obtained at each sampling point; Determine whether the cumulative displacement of the changed value exceeds the preset warning range.

5. 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, it implements the steps of the method according to any one of claims 1 to 4.

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