Open pit coal mine slope multi-source monitoring method and device

Abstract

The embodiment of the invention provides an open pit coal mine slope multi-source monitoring method and device. The open pit coal mine slope multi-source monitoring method comprises the steps that slope geological data information is collected in an on-site survey or drilling sampling mode; determining a monitoring point based on the side slope geological data information; the method comprises the following steps: respectively acquiring earth surface displacement data, underground water level data, rock-soil physical parameter data and micro-seismic activity data of a slope through monitoring equipment; performing feature extraction on the surface displacement data, the underground water level data, the rock-soil physical parameter data and the micro-seismic activity data of the slope to obtain surface displacement features, underground water level features, rock-soil physical parameter features and micro-seismic activity features respectively; and inputting the surface displacement characteristics, the underground water level characteristics, the rock-soil physical parameter characteristics and the micro-seismic activity characteristics into a pre-trained slope early warning model, and predicting to obtain the stability condition of the slope. And the stable state of the slope can be comprehensively reflected. And prediction is performed in combination with multi-source data features, so that the scientificity and accuracy of a prediction result are ensured.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of open-pit coal mine slope safety monitoring, and in particular to an open-pit coal mine slope multi-source monitoring method and device. Background Art

[0002] With the continuous exploitation of coal resources, the safety issues of open-pit coal mine slopes have become increasingly prominent. Traditional slope monitoring methods mainly rely on single technical means, such as surface displacement monitoring and groundwater level monitoring. These methods have problems such as single monitoring data and poor timeliness, and cannot fully and accurately reflect the stability of the slope.

[0003] Therefore, it is particularly important to develop a method that can comprehensively utilize multiple monitoring technologies to achieve efficient and accurate monitoring of the dynamic changes of open-pit coal mine slopes. Summary of the invention

[0004] The embodiments of the present invention aim to solve at least one of the technical problems existing in the prior art, and provide a method and device for multi-source monitoring of slopes in an open-pit coal mine.

[0005] In a first aspect, an embodiment of the present invention provides a multi-source monitoring method for an open-pit coal mine slope, the method comprising:

[0006] Collect slope geological information through on-site survey or drilling sampling;

[0007] Based on the slope geological information, surface displacement monitoring points, groundwater level monitoring points, geotechnical physical parameter monitoring points and microseismic activity monitoring points are determined respectively;

[0008] The surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope are obtained respectively by using the surface displacement monitoring equipment, groundwater level monitoring equipment, geotechnical physical parameter monitoring equipment and microseismic activity monitoring equipment installed at each monitoring point;

[0009] Extracting features from the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope to obtain surface displacement features, groundwater level features, geotechnical physical parameter features, and microseismic activity features, respectively;

[0010] The surface displacement characteristics, groundwater level characteristics, geotechnical physical parameter characteristics and microseismic activity characteristics are input into a pre-trained slope early warning model to predict the stability of the slope.

[0011] In some possible embodiments, before extracting features from the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope to obtain surface displacement features, groundwater level features, geotechnical physical parameter features, and microseismic activity features, respectively, the method further includes:

[0012] Respectively identifying and eliminating abnormal data in the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope;

[0013] Using an interpolation method to interpolate the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope after removing abnormal data to fill in missing values;

[0014] The interpolated surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope are standardized and aligned in time and space respectively.

[0015] In some possible embodiments, the feature extraction of the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope to obtain surface displacement features, groundwater level features, geotechnical physical parameter features and microseismic activity features respectively includes:

[0016] Extracting features from the surface displacement data of the slope to obtain features of displacement rate, maximum displacement, and displacement direction;

[0017] Extracting features of the groundwater level data of the slope to obtain water level change rate, maximum water level, and minimum water level features;

[0018] Extracting features of geotechnical physical parameter data of the slope to obtain soil moisture, temperature, pore pressure, and shear strength features;

[0019] Feature extraction is performed on the microseismic activity data of the slope to obtain the frequency, intensity and source location characteristics of the microseismic events.

[0020] In some possible embodiments, the slope warning model adopts a convolutional neural network model.

[0021] In a second aspect, an embodiment of the present invention provides a multi-source monitoring device for an open-pit coal mine slope, the device comprising:

[0022] A collection module is used to collect slope geological information through on-site exploration or drilling sampling;

[0023] A determination module, for determining surface displacement monitoring points, groundwater level monitoring points, geotechnical physical parameter monitoring points and microseismic activity monitoring points respectively based on the slope geological information;

[0024] An acquisition module, used to respectively acquire surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope through surface displacement monitoring equipment, groundwater level monitoring equipment, geotechnical physical parameter monitoring equipment and microseismic activity monitoring equipment set at each monitoring point;

[0025] An extraction module is used to extract features from the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope, and obtain surface displacement features, groundwater level features, geotechnical physical parameter features and microseismic activity features respectively;

[0026] The prediction module is used to input the surface displacement characteristics, groundwater level characteristics, geotechnical physical parameter characteristics and microseismic activity characteristics into a pre-trained slope early warning model to predict the stability of the slope.

[0027] In some possible embodiments, the device further includes a processing module, configured to:

[0028] Respectively identifying and eliminating abnormal data in the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope;

[0029] Using an interpolation method to interpolate the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope after removing abnormal data to fill in missing values;

[0030] The interpolated surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope are standardized and aligned in time and space respectively.

[0031] In some possible embodiments, the extraction module is further configured to:

[0032] Extracting features from the surface displacement data of the slope to obtain features of displacement rate, maximum displacement, and displacement direction;

[0033] Extracting features of the groundwater level data of the slope to obtain water level change rate, maximum water level, and minimum water level features;

[0034] Extracting features of geotechnical physical parameter data of the slope to obtain soil moisture, temperature, pore pressure, and shear strength features;

[0035] Feature extraction is performed on the microseismic activity data of the slope to obtain the frequency, intensity and source location characteristics of the microseismic events.

[0036] In some possible embodiments, the slope warning model adopts a convolutional neural network model.

[0037] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0038] one or more processors;

[0039] A storage unit is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors can implement the method described above.

[0040] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, can implement the method described above.

[0041] In a fifth aspect, an embodiment of the present invention provides a computer program product, including a computer program, which, when executed by a processor, can implement the method described above.

[0042] The multi-source monitoring method and device for open-pit coal mine slopes of the embodiment of the present invention integrates various monitoring data such as surface displacement, groundwater level, geotechnical physical parameters and microseismic activity, and can comprehensively reflect the stability of the slope. Analysis is performed from multiple angles such as geological structure, topography, and geotechnical characteristics to ensure the comprehensiveness and accuracy of the monitoring results. By extracting features from multi-source data and identifying key geological and environmental parameters, the scientificity and reliability of data analysis are improved. A pre-trained slope early warning model is used to make predictions in combination with multi-source data features to ensure the scientificity and accuracy of the prediction results. Based on real-time data and early warning models, early warnings can be issued in a timely manner to remind relevant personnel to take countermeasures and reduce the risk of geological disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a flow chart of a multi-source monitoring method for open-pit coal mine slope according to an embodiment of the present invention;

[0045] Figure 2 It is a schematic diagram of the structure of a multi-source monitoring device for an open-pit coal mine slope according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of protection of the present invention.

[0047] Unless otherwise specified, the technical terms or scientific terms used in the embodiments of the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. "Including" or "comprising" used in the embodiments of the present invention neither limit the shapes, numbers, steps, actions, operations, components, originals and / or their groups mentioned, nor exclude the appearance or addition of one or more other different shapes, numbers, steps, actions, operations, components, originals and / or their groups, or the addition of these. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number and order of the indicated technical features. Thus, the features defined as "first" and "second" can explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0048] Unless otherwise specifically stated, the relative arrangement of the components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention. At the same time, it should be understood that for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship, and the techniques, methods and devices known to ordinary technicians in the relevant fields may not be discussed in detail, but where appropriate, the techniques, methods and devices shown should be considered as part of the authorized specification. In all examples shown and discussed here, any specific other examples may have different values. It should be noted that similar symbols and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0049] In the description of the embodiments of the present invention, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In the embodiments of the present invention, the schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in the embodiments of the present invention and the features of the different embodiments or examples, without contradiction.

[0050] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described here.

[0051] like Figure 1 As shown, the embodiment of the present invention relates to a multi-source monitoring method for an open-pit coal mine slope, the method comprising the following steps S101 to S105:

[0052] Step S101: Collect slope geological information by on-site survey or drilling sampling.

[0053] Specifically, in this step, collect existing geological maps, topographic maps, geological reports and other relevant information. Prepare necessary exploration tools and equipment, such as geological hammers, compasses, topographic survey instruments, cameras, etc. Design a reasonable exploration route based on the topography and geological characteristics of the slope to ensure that the key areas of the slope are covered. Mark areas that need to be focused on on the map, such as areas with complex geological structures, steep terrain, and areas with cracks or obvious signs of deformation. Record the topographic and geomorphological characteristics of the slope, such as slope, slope direction, and terrain undulations. Observe and record the geological structure of the slope, such as rock layer distribution, faults, and fissures. Observe the color, texture, structure and other characteristics of the rock and soil, and preliminarily judge its physical and chemical properties. Record the location, length, width, direction and other information of existing cracks on the slope, as well as any signs of deformation.

[0054] Furthermore, during the survey, standardized recording forms can be used to record various information observed during the survey, and GPS equipment can be used to record the coordinates of important geological features, etc.

[0055] Step S102: Based on the slope geological information, surface displacement monitoring points, groundwater level monitoring points, geotechnical physical parameter monitoring points and microseismic activity monitoring points are determined respectively.

[0056] Specifically, in this step, for surface displacement monitoring points, key positions at the top, middle and bottom of the slope are selected, especially areas prone to landslides; and monitoring points are set near geological structures such as faults, fissures, and weak interlayers; monitoring points are set in areas with large slopes and steep terrain; and monitoring points are set in areas with existing cracks or obvious signs of deformation.

[0057] For groundwater level monitoring points, monitoring points can be set up in the following locations: areas with high groundwater levels and active groundwater flow, near groundwater channels such as faults and fissures, at the junction of highly permeable rock layers (such as sandstone and conglomerate) and impermeable layers (such as clay), and in low-lying areas prone to water accumulation.

[0058] For geotechnical physical parameter monitoring points, monitoring points can be set up in the following locations: areas where geotechnical physical properties (such as density, porosity, water content, compressive strength) change significantly; the junction of different geological units (such as different rock layers, different sedimentary environments); areas where there are obvious cracks or deformation signs; areas where groundwater level changes significantly affect geotechnical physical properties, etc.

[0059] For microseismic activity monitoring points, monitoring points can be set up in the following locations: near geological structures such as faults, fissures, and weak interlayers; in areas where stress is concentrated and microseismic activity is prone to occur; in areas where cracks or obvious signs of deformation already exist; in areas where microseismic activity or geological disasters have occurred in history, etc.

[0060] After determining the monitoring points, it is necessary to select appropriate equipment for installation, such as selecting appropriate surface displacement monitoring equipment, such as GPS positioning system, total station, etc. Select appropriate groundwater level monitoring equipment, such as groundwater level meter, automatic recorder, etc. Select appropriate geotechnical physical parameter monitoring equipment, such as soil moisture sensor, temperature sensor, pore pressure sensor, etc. Select appropriate microseismic activity monitoring equipment, such as seismograph, microseismic sensor, etc.

[0061] Step S103, obtaining the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope respectively by means of surface displacement monitoring equipment, groundwater level monitoring equipment, geotechnical physical parameter monitoring equipment and microseismic activity monitoring equipment set at each monitoring point.

[0062] Specifically, in this step, after obtaining each data, it is necessary to perform some preprocessing on each data, such as identifying and removing abnormal data in the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope. The surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope after removing the abnormal data are interpolated using the interpolation method to fill in the missing values. The surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope after interpolation are standardized, and aligned in time and space, etc.

[0063] Step S104: extracting features from the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope to obtain surface displacement features, groundwater level features, geotechnical physical parameter features and microseismic activity features, respectively.

[0064] Specifically, in this step, feature extraction is performed on the surface displacement data of the slope to obtain displacement rate, maximum displacement, and displacement direction characteristics; feature extraction is performed on the groundwater level data of the slope to obtain water level change rate, highest water level, and lowest water level characteristics; feature extraction is performed on the geotechnical physical parameter data of the slope to obtain soil moisture, temperature, pore pressure, and shear strength characteristics; feature extraction is performed on the microseismic activity data of the slope to obtain frequency, intensity, and source location characteristics of microseismic events.

[0065] Step S105: input the surface displacement characteristics, groundwater level characteristics, geotechnical physical parameter characteristics and microseismic activity characteristics into a pre-trained slope early warning model to predict the stability of the slope.

[0066] Specifically, in this step, the slope warning model adopts a convolutional neural network model. Based on the trained model, the real-time monitoring data is analyzed online to identify data points that deviate from the normal range, that is, potential abnormalities. According to the abnormal detection results and slope safety standards, the warning threshold is set. When the monitoring data reaches or exceeds these thresholds, the system automatically triggers an alarm. Once the alarm is triggered, the system should immediately notify relevant personnel through multiple channels such as text messages and emails so that timely countermeasures can be taken, etc.

[0067] The multi-source monitoring method for open-pit coal mine slopes of the embodiment of the present invention integrates various monitoring data such as surface displacement, groundwater level, geotechnical physical parameters and microseismic activity, and can comprehensively reflect the stability of the slope. Analysis is performed from multiple angles such as geological structure, topography, and geotechnical characteristics to ensure the comprehensiveness and accuracy of the monitoring results. By extracting features from multi-source data and identifying key geological and environmental parameters, the scientificity and reliability of data analysis are improved. A pre-trained slope early warning model is used to make predictions in combination with multi-source data features to ensure the scientificity and accuracy of the prediction results. Based on real-time data and early warning models, early warnings can be issued in a timely manner to remind relevant personnel to take countermeasures and reduce the risk of geological disasters.

[0068] Based on the same inventive concept, an embodiment of the present invention provides an open-pit coal mine slope multi-source monitoring device, which can be applied to the method described above. For details, please refer to the relevant records in the above text and will not be repeated here.

[0069] like Figure 2 As shown, the device includes: a collection module 201, a determination module 202, an acquisition module 203, an extraction module 204 and a prediction module 205. The collection module 201 is used to collect slope geological information by field survey or drilling sampling. The determination module 202 is used to determine the surface displacement monitoring points, groundwater level monitoring points, geotechnical physical parameter monitoring points and microseismic activity monitoring points based on the slope geological information. The acquisition module 203 is used to obtain the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope by setting the surface displacement monitoring equipment, groundwater level monitoring equipment, geotechnical physical parameter monitoring equipment and microseismic activity monitoring equipment of each monitoring point. The extraction module 204 is used to extract the features of the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope, and obtain the surface displacement features, groundwater level features, geotechnical physical parameter features and microseismic activity features respectively. The prediction module 205 is used to input the surface displacement characteristics, groundwater level characteristics, geotechnical physical parameter characteristics and microseismic activity characteristics into the pre-trained slope early warning model to predict the stability of the slope.

[0070] The multi-source monitoring device for the slope of an open-pit coal mine of the embodiment of the present invention integrates a variety of monitoring data such as surface displacement, groundwater level, geotechnical physical parameters and microseismic activity, and can comprehensively reflect the stability of the slope. Analysis is performed from multiple angles such as geological structure, topography, and geotechnical characteristics to ensure the comprehensiveness and accuracy of the monitoring results. By extracting features from multi-source data and identifying key geological and environmental parameters, the scientificity and reliability of data analysis are improved. A pre-trained slope early warning model is used to make predictions in combination with the features of multi-source data to ensure the scientificity and accuracy of the prediction results. Based on real-time data and early warning models, early warnings can be issued in a timely manner to remind relevant personnel to take countermeasures and reduce the risk of geological disasters.

[0071] In some possible embodiments, Figure 2 As shown, the device further includes a processing module 206, which is used to:

[0072] Respectively identifying and eliminating abnormal data in the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope;

[0073] Using an interpolation method to interpolate the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope after removing abnormal data to fill in missing values;

[0074] The interpolated surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope are standardized and aligned in time and space respectively.

[0075] In some possible embodiments, Figure 2 As shown, the extraction module 204 is further used for:

[0076] The surface displacement data of the slope is feature extracted to obtain the displacement rate, maximum displacement, and displacement direction features. The groundwater level data of the slope is feature extracted to obtain the water level change rate, maximum water level, and minimum water level features. The geotechnical physical parameter data of the slope is feature extracted to obtain the soil moisture, temperature, pore pressure, and shear strength features. The microseismic activity data of the slope is feature extracted to obtain the frequency, intensity, and source location features of the microseismic events.

[0077] In some possible embodiments, the slope warning model adopts a convolutional neural network model.

[0078] Based on the same inventive concept, an embodiment of the present invention provides an electronic device, including:

[0079] one or more processors;

[0080] A storage unit is used to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors can implement the method described above.

[0081] Based on the same inventive concept, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method described above can be implemented.

[0082] The computer-readable medium may be included in the apparatus, device, or system of the present invention, or may exist independently.

[0083] Among them, computer-readable storage media can be any tangible media that contains or stores a program, which can be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment. More specific examples include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, an optical fiber, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0084] The computer-readable storage medium may also include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code, specific examples of which include but are not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0085] Based on the same inventive concept, an embodiment of the present invention provides a computer program product, including a computer program, which can implement the method described above when executed by a processor.

[0086] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A multi-source monitoring method for open-pit coal mine slopes, characterized in that: The method comprises: Collect slope geological information through on-site survey or drilling sampling; Based on the slope geological information, surface displacement monitoring points, groundwater level monitoring points, geotechnical physical parameter monitoring points and microseismic activity monitoring points are determined respectively; The surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope are obtained respectively by using the surface displacement monitoring equipment, groundwater level monitoring equipment, geotechnical physical parameter monitoring equipment and microseismic activity monitoring equipment installed at each monitoring point; Extracting features from the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope to obtain surface displacement features, groundwater level features, geotechnical physical parameter features, and microseismic activity features, respectively; The surface displacement characteristics, groundwater level characteristics, geotechnical physical parameter characteristics and microseismic activity characteristics are input into a pre-trained slope early warning model to predict the stability of the slope.

2. The method according to claim 1, characterized in that: Before extracting features from the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope to obtain surface displacement features, groundwater level features, geotechnical physical parameter features, and microseismic activity features, the method further includes: Respectively identifying and eliminating abnormal data in the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope; Using an interpolation method to interpolate the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope after removing abnormal data to fill in missing values; The interpolated surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope are standardized and aligned in time and space respectively.

3. The method according to claim 1, characterized in that The feature extraction of the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope is performed to obtain surface displacement features, groundwater level features, geotechnical physical parameter features and microseismic activity features, respectively, including: Extracting features from the surface displacement data of the slope to obtain features of displacement rate, maximum displacement, and displacement direction; Extracting features of the groundwater level data of the slope to obtain water level change rate, maximum water level, and minimum water level features; Extracting features of geotechnical physical parameter data of the slope to obtain soil moisture, temperature, pore pressure, and shear strength features; Feature extraction is performed on the microseismic activity data of the slope to obtain the frequency, intensity and source location characteristics of the microseismic events.

4. The method according to any one of claims 1 to 3, characterized in that: The slope warning model adopts a convolutional neural network model.

5. A multi-source monitoring device for open-pit coal mine slopes, characterized in that: The device comprises: A collection module is used to collect slope geological information through on-site exploration or drilling sampling; A determination module, for determining surface displacement monitoring points, groundwater level monitoring points, geotechnical physical parameter monitoring points and microseismic activity monitoring points respectively based on the slope geological information; An acquisition module, used to respectively acquire surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope through surface displacement monitoring equipment, groundwater level monitoring equipment, geotechnical physical parameter monitoring equipment and microseismic activity monitoring equipment set at each monitoring point; An extraction module is used to extract features from the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope, and obtain surface displacement features, groundwater level features, geotechnical physical parameter features and microseismic activity features respectively; The prediction module is used to input the surface displacement characteristics, groundwater level characteristics, geotechnical physical parameter characteristics and microseismic activity characteristics into a pre-trained slope early warning model to predict the stability of the slope.

6. The device according to claim 5, characterized in that The device also includes a processing module, configured to: Respectively identifying and eliminating abnormal data in the surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope; Using an interpolation method to interpolate the surface displacement data, groundwater level data, geotechnical physical parameter data, and microseismic activity data of the slope after removing abnormal data to fill in missing values; The interpolated surface displacement data, groundwater level data, geotechnical physical parameter data and microseismic activity data of the slope are standardized and aligned in time and space respectively.

7. The device according to claim 5, characterized in that The extraction module is further specifically used for: Extracting features from the surface displacement data of the slope to obtain features of displacement rate, maximum displacement, and displacement direction; Extracting features of the groundwater level data of the slope to obtain water level change rate, maximum water level, and minimum water level features; Extracting features of geotechnical physical parameter data of the slope to obtain soil moisture, temperature, pore pressure, and shear strength features; Feature extraction is performed on the microseismic activity data of the slope to obtain the frequency, intensity and source location characteristics of the microseismic events.

8. The device according to any one of claims 5 to 7, characterized in that The slope warning model adopts a convolutional neural network model.

9. An electronic device, characterized in that: include: one or more processors; A storage unit, used to store one or more programs, which, when executed by the one or more processors, enable the one or more processors to implement the method according to any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 can be implemented.

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