Mine Safety Monitoring Method, System, Equipment and Medium Based on 5G Big Data

Abstract

This application relates to the technical field of data monitoring, and particularly to a mine safety monitoring method, system, device and medium based on 5G big data. The method includes obtaining safety monitoring data and historical monitoring information at different positions in a preset area of the mine based on a 5G communication network, performing data cleaning and integration processing on the safety monitoring data to obtain processed safety monitoring data, performing abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain current abnormal information and safety warning information within a preset time period, and controlling the display of the current abnormal information and safety warning information. This application improves the data transmission efficiency and ensures the safety of mining personnel.

Description

Technical Field

[0001] This application relates to the technical field of data monitoring, and in particular to a mine safety monitoring method, system, device and medium based on 5G big data. Background Art

[0002] With the deepening of mine exploitation, mine safety issues have become increasingly prominent. At present, although there are some mine safety monitoring systems, most of them are based on traditional wired transmission methods, which are complex in wiring, difficult to maintain, and have low data transmission efficiency, and cannot meet the needs of real-time monitoring. Summary of the Invention

[0003] In order to solve at least one of the above technical problems, this application provides a mine safety monitoring method, system, device and medium based on 5G big data.

[0004] In a first aspect, this application provides a mine safety monitoring method based on 5G big data, adopting the following technical solutions:

[0005] Based on the 5G communication network, obtain the safety monitoring data and historical monitoring information at different positions within the preset area of the mine;

[0006] Perform data cleaning and integration processing on the safety monitoring data to obtain the processed safety monitoring data;

[0007] Perform abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormal information and the safety warning information within a preset time period;

[0008] Control to display the current abnormal information and the safety warning information.

[0009] In a possible implementation manner, the performing abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormal information and the safety warning information within a preset time period includes:

[0010] Analyze the historical monitoring information to obtain the monitoring data at different mine positions and different times in the historical monitoring information and the data change sequences at different mine positions within different unit times;

[0011] Correlate the monitoring data and the data change sequences according to the mine positions to obtain the first correlation data;

[0012] Based on the monitoring data and the data change sequences, correlate the data corresponding to the adjacent mine positions of each mine position with the first correlation data to obtain the second correlation data;

[0013] Determine the monitoring parameter characteristics and the time series length based on the second associated data, and predict the historical monitoring information according to the monitoring parameter characteristics and the time series length to obtain a parameter data sequence in which different monitoring parameter characteristics change over time;

[0014] Determine the time node information and the monitoring location information when the safety monitoring data is acquired, and determine the target data sequence corresponding thereto in the parameter data sequence according to the time node information and the monitoring location information;

[0015] Judge whether there is preset abnormal range data in the target data sequence. If so, perform early warning processing on the sequence nodes with preset abnormal range data in the target data sequence based on the abnormal early warning standard information to obtain safety early warning information.

[0016] In a possible implementation manner, before obtaining the safety monitoring data and the historical monitoring information at different positions in the preset area of the mine based on the 5G communication network, it further includes:

[0017] Obtain reflector information and signal strength data, where the reflector information is the angle information and the reflection surface information corresponding to a signal reflector pre-installed at a specified position, and the signal strength data is the signal strength data of the 5G communication network;

[0018] Analyze the signal strength data to identify signal abnormal positions where there are signal blind spots or weak signal areas inside the mine;

[0019] Determine an adjustment instruction based on the signal abnormal position and the reflector information, and control and adjust the angle parameter and the reflection surface parameter in the signal reflector.

[0020] In a possible implementation manner, before obtaining the reflector information and the signal strength data, it further includes:

[0021] Obtain the monitoring status data of the signal reflector, where the monitoring status data includes real-time monitoring data and historical monitoring data;

[0022] Predict the signal reflector based on the monitoring status data to determine the suspicious fault points existing in the signal reflector;

[0023] Generate fault maintenance information based on the suspicious fault points and send the fault maintenance information to the terminal device of the maintenance personnel.

[0024] In a possible implementation manner, predicting the signal reflector based on the monitoring status data to determine the suspicious fault points existing in the signal reflector includes:

[0025] Determine the reflection coefficient and key operating parameters of the reflector based on the historical monitoring data in the monitored status data;

[0026] Perform data processing on the reflection coefficient and key operating parameters to obtain the processed reflection coefficient and key operating parameters;

[0027] Extract features from the processed reflection coefficient and key operating parameters to extract fault features related to the failure of the signal reflector;

[0028] Create a prediction model and train the prediction model based on the fault features to obtain the trained prediction model;

[0029] Input the real-time monitoring data into the prediction model for prediction to determine the suspicious fault points of the signal reflector.

[0030] In a possible implementation manner, after controlling the display of the current abnormal information and safety warning information, it further includes:

[0031] Obtain mine image information and construct a three-dimensional mine environment based on the features in the mine image information;

[0032] Retrieve the personnel information responsible for maintaining different areas in the mine respectively and connect the personnel information to the three-dimensional mine environment;

[0033] Connect the current abnormal information and the safety warning information to the three-dimensional mine environment, and dynamically select the maintenance personnel responsible for the current abnormal information and the safety warning information according to the activity situation and resource allocation situation of the personnel information in the three-dimensional mine environment, and grant the maintenance personnel the right to view the current abnormal information and the safety warning information.

[0034] In a second aspect, the present application provides a mine safety monitoring system based on 5G big data, adopting the following technical solutions:

[0035] A mine safety monitoring system based on 5G big data includes:

[0036] An information acquisition module for acquiring safety monitoring data and historical monitoring information at different positions in a preset area of the mine based on a 5G communication network;

[0037] A data processing module for performing data cleaning and integration processing on the safety monitoring data to obtain the processed safety monitoring data;

[0038] An anomaly analysis module for performing anomaly warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current anomaly information and safety warning information within a preset time period;

[0039] A control display module for controlling the display of the current abnormal information and safety warning information.

[0040] In a possible implementation manner, when the abnormal analysis module performs abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormal information and the safety warning information within a preset time period, it is specifically used for:

[0041] Analyze the historical monitoring information to obtain the monitoring data of different mine locations at different times and the data change sequences of different mine locations within different unit times in the historical monitoring information;

[0042] Correlate the monitoring data and the data change sequences according to the mine locations to obtain first correlation data;

[0043] Based on the monitoring data and the data change sequences, correlate the data corresponding to the adjacent mine locations of each mine location with the first correlation data to obtain second correlation data;

[0044] Determine the monitoring parameter characteristics and the time series length based on the second correlation data, and predict the historical monitoring information according to the monitoring parameter characteristics and the time series length to obtain a parameter data sequence in which different monitoring parameter characteristics change over time;

[0045] Determine the time node information and the monitoring location information when the safety monitoring data is acquired, and determine the target data sequence corresponding thereto in the parameter data sequence according to the time node information and the monitoring location information;

[0046] Judge whether there is preset abnormal range data in the target data sequence. If so, perform warning processing on the sequence nodes with preset abnormal range data in the target data sequence based on the abnormal warning standard information to obtain safety warning information.

[0047] In another possible implementation manner, the system further includes: a data acquisition module, a data analysis module, and a device control module, where

[0048] The data acquisition module is used to acquire reflector information and signal strength data. The reflector information is the angle information and the reflection surface information corresponding to a signal reflector pre-installed at a specified position, and the signal strength data is the signal strength data of a 5G communication network;

[0049] The data analysis module is used to analyze the signal strength data to identify signal abnormal positions where there are signal blind areas or signal weak areas inside the mine;

[0050] The device control module is used to determine an adjustment instruction based on the signal abnormal position and the reflector information, and control and adjust the angle parameter and the reflecting surface parameter in the signal reflector.

[0051] In another possible implementation manner, the system further includes: a status acquisition module, a fault prediction module, and a fault information determination module, where,

[0052] The status acquisition module is used to acquire the monitoring status data of the signal reflector, and the monitoring status data includes real-time monitoring data and historical monitoring data;

[0053] The fault prediction module is used to predict the signal reflector based on the monitoring status data and determine the suspicious fault points existing in the signal reflector;

[0054] The fault information determination module is used to generate fault maintenance information based on the suspicious fault points and send the fault maintenance information to the terminal device of the maintenance personnel.

[0055] In another possible implementation manner, when the fault prediction module predicts the signal reflector based on the monitoring status data and determines the suspicious fault points existing in the signal reflector, it specifically is used for:

[0056] Determine the reflection coefficient and the key operation parameters of the reflection signaler based on the historical monitoring data in the monitoring status data;

[0057] Perform data processing on the reflection coefficient and the key operation parameters to obtain the processed reflection coefficient and key operation parameters;

[0058] Extract features from the processed reflection coefficient and key operation parameters, and extract the fault features related to the signal reflector fault;

[0059] Create a prediction model, and train the prediction model according to the fault features to obtain a trained prediction model;

[0060] Input the real-time monitoring data into the prediction model for prediction, and determine the suspicious fault points existing in the signal reflector.

[0061] In another possible implementation manner, the system further includes: a three-dimensional construction module, a personnel access module, and a dynamic adjustment module, where,

[0062] The three-dimensional construction module is used to acquire the mine image information and construct a three-dimensional mine environment based on the features in the mine image information;

[0063] The personnel access module is used to retrieve the personnel information of the personnel responsible for maintaining different areas in the mine respectively, and access the personnel information to the three-dimensional environment of the mine;

[0064] The dynamic adjustment module is used to access the current abnormal information and the safety warning information to the three-dimensional environment of the mine. According to the activity situation and resource allocation situation of the personnel information in the three-dimensional environment of the mine, it dynamically selects the maintenance personnel responsible for the current abnormal information and the safety warning information, and authorizes the maintenance personnel to view the current abnormal information and the safety warning information.

[0065] Thirdly, the present application provides an electronic device, adopting the following technical solution:

[0066] At least one processor;

[0067] A memory;

[0068] At least one application program, wherein at least one application program is stored in the memory and is configured to be executed by at least one processor. The at least one application program is configured to: execute a mine safety monitoring method based on 5G big data as described in any item of the first aspect.

[0069] Fourthly, the present application provides a computer-readable storage medium, adopting the following technical solution:

[0070] A computer-readable storage medium, on which a computer program is stored. When the computer program is executed in a computer, the computer is made to execute the mine safety monitoring method based on 5G big data as described in any item of the first aspect.

[0071] In summary, the present application includes at least one of the following beneficial technical effects:

[0072] During the process of mine exploitation, to ensure the safety of the exploitation personnel, the present application, based on the 5G communication network, obtains the safety monitoring data and historical monitoring information at different positions in the preset area of the mine, then performs data cleaning and integration processing on the safety monitoring data to obtain the processed safety monitoring data, and then performs abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormal information and the safety warning information within the preset time period, and then controls the display of the current abnormal information and the safety warning information, thereby improving the data transmission efficiency and ensuring the safety of the exploitation personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 It is a schematic flowchart of a mine safety monitoring method based on 5G big data provided by an embodiment of the present application.

[0074] Figure 2Schematic diagram of a mine safety monitoring system based on 5G big data provided by an embodiment of the present application.

[0075] Figure 3 Schematic diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0076] The following will further describe the present application in detail Figures 1 - 3 in conjunction with the accompanying drawings.

[0077] This specific embodiment is only an interpretation of the present application and does not limit the present application. After reading this specification, those skilled in the art can make modifications to this embodiment without creative contributions as needed, but as long as they are within the scope of the present application, they are protected by the patent law.

[0078] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without making creative efforts fall within the scope of protection of the present application.

[0079] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. These three situations. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, unless otherwise specified.

[0080] The following will further describe the embodiments of the present application in detail in conjunction with the accompanying drawings of the specification.

[0081] An embodiment of the present application provides a method for a mine safety monitoring method based on 5G big data, which is executed by an electronic device. The electronic device can be a server or a terminal device. Among them, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected through wired or wireless communication methods. This embodiment of the present application does not make any restrictions here, such as Figure 1 As shown, the method includes:

[0082] Step S10: Based on the 5G communication network, obtain safety monitoring data and historical monitoring information at different positions in a preset area of the mine.

[0083] For the embodiments of this application, the 5G communication network represents the fifth-generation mobile communication network, which provides characteristics such as high data rate, low latency, and large connection, and is applicable to various application scenarios that require high data transmission speed and low latency; the preset area in the mine refers to a specific monitoring range demarcated in the mine, which may contain multiple monitoring points to ensure comprehensive coverage; the safety monitoring data is used to represent the safety-related data of the mine monitored in real time, such as environmental parameters such as gas concentration, temperature, and humidity; the historical monitoring information refers to the records of safety monitoring data collected over a past period of time.

[0084] Specifically, based on the high transmission rate and low latency characteristics of the 5G communication network, the system can collect safety monitoring data from different locations within the preset area of the mine in real time. These data include, but are not limited to, key indicators such as air quality, groundwater level, and soil stability. At the same time, the system will also obtain historical monitoring information for comparison and analysis with the current data, so as to detect abnormal situations in time and take corresponding measures.

[0085] In the embodiments of this application, by arranging multiple sensor nodes within the preset area of the mine, these nodes upload the monitoring data to the electronic device in real time through the 5G communication network. The electronic device is responsible for receiving, storing, and processing these data, and at the same time provides a query function for historical monitoring information. In addition, drones or intelligent inspection robots can be used to carry sensors to conduct mobile monitoring within the preset area of the mine. These mobile devices transmit the real-time collected data back to the electronic device through the 5G communication network, and the electronic device then analyzes these data and compares them with the historical data to evaluate the safety status of the mine.

[0086] Step S11: Perform data cleaning and integration processing on the safety monitoring data to obtain the processed safety monitoring data.

[0087] For the embodiments of this application, the data cleaning and integration processing includes removing duplicate, invalid, and incorrect data, filling in missing values, and normalizing or standardizing the data, etc., with the aim of improving the data quality and usability.

[0088] Specifically, the data cleaning and integration processing is a key data preprocessing step, aiming to remove noise, outliers, and duplicate data from the original safety monitoring data, and at the same time fill in or process missing values to ensure the accuracy and integrity of the data, thereby improving the data quality and reliability.

[0089] Step S12: Perform abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormal information and the safety warning information within the preset time period.

[0090] For the embodiments of this application, anomaly warning analysis refers to the process of identifying data changes that deviate from the normal pattern or expected range by comparing the currently processed safety monitoring data with historical monitoring information, and then issuing a warning; the current anomaly information represents the data or events detected in real-time analysis that do not conform to the normal pattern; the safety warning information within a preset time period refers to the potential or impending safety risk warning obtained based on the comparison and analysis of historical data and current data within a specific time range.

[0091] Specifically, the system will establish a normal data behavior pattern or range based on historical monitoring information. When the processed safety monitoring data is input, the system will compare it with the historical data to check if there is any data that exceeds the normal range or is inconsistent with the historical pattern. If an anomaly is found, the system will generate the current anomaly information, and based on these anomalies and historical trends, predict the possible safety risks within the preset time period, thereby generating safety warning information.

[0092] Specifically, analyze the historical monitoring information to obtain the monitoring data of different mine locations at different times and the data change sequences of different mine locations within different unit times. Associate the monitoring data and data change sequences according to the mine location to obtain the first associated data. Based on the monitoring data and data change sequences, associate the data corresponding to adjacent mine locations of each mine location with the first associated data to obtain the second associated data. Determine the monitoring parameter characteristics and the time series length based on the second associated data, and predict the historical monitoring information according to the monitoring parameter characteristics and the time series length to obtain the parameter data sequence in which different monitoring parameter characteristics change over time. Determine the time node information and monitoring location information when the safety monitoring data is obtained, and determine the target data sequence corresponding to them in the parameter data sequence according to the time node information and monitoring location information. Judge whether there is data within the preset abnormal range in the target data sequence. If so, perform warning processing on the sequence nodes with data within the preset abnormal range in the target data sequence based on the anomaly warning standard information to obtain the safety warning information.

[0093] Step S13: Control to display the current anomaly information and the safety warning information.

[0094] In the embodiment of the present application, during the process of mine exploitation, to ensure the safety of the exploitation personnel, the present application obtains safety monitoring data and historical monitoring information at different positions in a preset area of the mine based on a 5G communication network, then performs data cleaning and integration processing on the safety monitoring data to obtain the processed safety monitoring data, and then performs abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormal information and safety warning information within a preset time period, and then controls the display of the current abnormal information and safety warning information, thereby improving the data transmission efficiency and ensuring the safety of the exploitation personnel.

[0095] Further, in the embodiment of the present application, before obtaining the safety monitoring data and historical monitoring information at different positions in a preset area of the mine based on a 5G communication network, it further includes: obtaining reflector information and signal strength data, where the reflector information is the angle information and reflection surface information corresponding to a signal reflector pre-installed at a specified position, and the signal strength data is the signal strength data of the 5G communication network, analyzing the signal strength data to identify signal abnormal positions with signal blind spots or weak signal areas inside the mine, and determining an adjustment instruction based on the signal abnormal positions and the reflector information, and controlling the adjustment of the angle parameter and reflection surface parameter in the signal reflector.

[0096] Further, in the embodiment of the present application, before obtaining the reflector information and signal strength data, it further includes: obtaining the monitoring status data of the signal reflector, where the monitoring status data includes real-time monitoring data and historical monitoring data, predicting the signal reflector based on the monitoring status data to determine the suspected fault points existing in the signal reflector, generating fault maintenance information based on the suspected fault points, and sending the fault maintenance information to the terminal device of the maintenance personnel.

[0097] Further, in the embodiment of the present application, predicting the signal reflector based on the monitoring status data to determine the suspected fault points existing in the signal reflector includes: determining the reflection coefficient and key operation parameters of the reflector based on the historical monitoring data in the monitoring status data, performing data processing on the reflection coefficient and key operation parameters to obtain the processed reflection coefficient and key operation parameters, extracting fault features related to the failure of the signal reflector from the processed reflection coefficient and key operation parameters, creating a prediction model, training the prediction model according to the fault features to obtain the trained prediction model, and inputting the real-time monitoring data into the prediction model for prediction to determine the suspected fault points existing in the signal reflector.

[0098] Further, in the embodiment of the present application, after controlling the display of the current abnormal information and the safety warning information, the following steps are also included: obtaining mine image information, constructing a three-dimensional mine environment based on the features in the mine image information, separately retrieving the personnel information of the personnel responsible for maintaining different areas in the mine, connecting the personnel information to the three-dimensional mine environment, connecting the current abnormal information and the safety warning information to the three-dimensional mine environment, dynamically selecting the maintenance personnel responsible for the current abnormal information and the safety warning information according to the activity situation and resource allocation situation of the personnel information in the three-dimensional mine environment, and granting the maintenance personnel the right to view the current abnormal information and the safety warning information.

[0099] Next, an introduction to a mine safety monitoring system based on 5G big data provided by the embodiment of the present application is given. The mine safety monitoring system based on 5G big data described below can be mutually corresponding and referenced with the mine safety monitoring method based on 5G big data described above. Please refer to Figure 2 , Figure 2 FIG. 20 is a schematic structural diagram of a mine safety monitoring system 20 based on 5G big data provided by the embodiment of the present application, including:

[0100] An information acquisition module 21, configured to acquire safety monitoring data and historical monitoring information at different positions within a preset area of the mine based on a 5G communication network;

[0101] A data processing module 22, configured to perform data cleaning and integration processing on the safety monitoring data to obtain processed safety monitoring data;

[0102] An abnormal analysis module 23, configured to perform abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormal information and the safety warning information within a preset time period;

[0103] A control display module 24, configured to control the display of the current abnormal information and the safety warning information.

[0104] In a possible implementation manner in the embodiment of the present application, when the abnormal analysis module 23 performs abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormal information and the safety warning information within a preset time period, it is specifically configured to:

[0105] Analyze the historical monitoring information to obtain the monitoring data of different mine positions at different times and the data change sequences of different mine positions within different unit times in the historical monitoring information;

[0106] Correlate the monitoring data and the data change sequences according to the mine positions to obtain first correlation data;

[0107] Based on the monitoring data and the data change sequence, associate the data corresponding to the adjacent mine positions of each mine position with the first associated data to obtain the second associated data;

[0108] Based on the second associated data, determine the monitoring parameter characteristics and the time series length, and predict the historical monitoring information according to the monitoring parameter characteristics and the time series length to obtain a parameter data sequence in which different monitoring parameter characteristics change over time;

[0109] Determine the time node information and the monitoring position information when the safety monitoring data is obtained, and determine the corresponding target data sequence in the parameter data sequence according to the time node information and the monitoring position information;

[0110] Judge whether there is preset abnormal range data in the target data sequence. If so, based on the abnormal warning standard information, perform warning processing on the sequence nodes with preset abnormal range data in the target data sequence to obtain safety warning information.

[0111] In another possible implementation manner in the embodiments of the present application, the system 20 further includes: a data acquisition module, a data analysis module, and a device regulation module, where,

[0112] The data acquisition module is used to acquire reflector information and signal strength data. The reflector information is the angle information and the reflection surface information corresponding to a signal reflector pre-installed at a specified position, and the signal strength data is the signal strength data of the 5G communication network;

[0113] The data analysis module is used to analyze the signal strength data and identify the signal abnormal positions where there are signal blind areas or signal weak areas inside the mine;

[0114] The device regulation module is used to determine an adjustment instruction based on the signal abnormal position and the reflector information, and control and adjust the angle parameter and the reflection surface parameter in the signal reflector.

[0115] In another possible implementation manner in the embodiments of the present application, the system 20 further includes: a status acquisition module, a fault prediction module, and a fault information determination module, where,

[0116] The status acquisition module is used to acquire the monitoring status data of the signal reflector. The monitoring status data includes real-time monitoring data and historical monitoring data;

[0117] The fault prediction module is used to predict the signal reflector based on the monitoring status data and determine the suspicious fault points existing in the signal reflector;

[0118] The fault information determination module is used to generate fault maintenance information based on the suspicious fault points and send the fault maintenance information to the terminal device of the maintenance personnel.

[0119] In another possible implementation manner in the embodiments of the present application, when the fault prediction module predicts the signal reflector based on the monitored status data and determines the suspicious fault points existing in the signal reflector, it is specifically used for:

[0120] Determine the reflection coefficient and key operation parameters of the reflector based on the historical monitoring data in the monitored status data;

[0121] Perform data processing on the reflection coefficient and key operation parameters to obtain the processed reflection coefficient and key operation parameters;

[0122] Extract fault features related to the signal reflector fault by performing feature extraction on the processed reflection coefficient and key operation parameters;

[0123] Create a prediction model and train the prediction model according to the fault features to obtain a trained prediction model;

[0124] Input the real-time monitoring data into the prediction model for prediction to determine the suspicious fault points existing in the signal reflector.

[0125] In another possible implementation manner in the embodiments of the present application, the system 20 further includes: a three-dimensional construction module, a personnel access module, and a dynamic adjustment module, where

[0126] The three-dimensional construction module is used to obtain mine image information and construct a three-dimensional mine environment based on the features in the mine image information;

[0127] The personnel access module is used to retrieve the personnel information responsible for maintaining different areas in the mine respectively and access the personnel information into the three-dimensional mine environment;

[0128] The dynamic adjustment module is used to access the current abnormal information and safety warning information into the three-dimensional mine environment, dynamically select the maintenance personnel responsible for the current abnormal information and safety warning information according to the activity situation of the personnel information and the resource allocation situation in the three-dimensional mine environment, and grant the maintenance personnel the right to view the current abnormal information and safety warning information.

[0129] Next, an electronic device provided in the embodiments of the present application will be introduced. The electronic device described below can be mutually corresponding and referred to with the mine safety monitoring method based on 5G big data described above.

[0130] The embodiments of the present application provide an electronic device, as Figure 3 shown, Figure 3 is a schematic structural diagram of an electronic device provided in the embodiments of the present application, Figure 3The electronic device 300 shown includes: a processor 301 and a memory 303. Among them, the processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may further include a transceiver 304. It should be noted that in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation to the embodiments of the present application.

[0131] The processor 301 may be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logic blocks, modules, and circuits described in connection with the disclosed content of the embodiments of the present application. The processor 301 may also be a combination that implements computing functions, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0132] The bus 302 may include a path for transmitting information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0133] The memory 303 can be a ROM (ReadOnlyMemory), or other types of static storage devices that can store static information and instructions, a RAM (RandomAccessMemory), or other types of dynamic storage devices that can store information and instructions. It can also be an EEPROM (ElectricallyErasableProgrammableReadOnlyMemory), a CD-ROM (CompactDiscReadOnlyMemory), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0134] The memory 303 is used to store the application program code for implementing the solution of the embodiment of the present application and is controlled by the processor 301 for execution. The processor 301 is used to execute the application program code stored in the memory 303 to implement the content shown in the foregoing method embodiment.

[0135] Among them, the electronic device includes but is not limited to: mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The illustrated electronic device is only an example and should not impose any limitations on the functions and usage scope of the embodiment of the present application.

[0136] Next, a computer-readable storage medium provided by the embodiment of the present application will be introduced. The computer-readable storage medium described below can be correspondingly referred to the method described above.

[0137] The embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned mine safety monitoring method based on 5G big data are implemented.

[0138] Since the embodiment of the computer-readable storage medium part corresponds to the embodiment of the method part, please refer to the description of the embodiment of the method part for the embodiment of the computer-readable storage medium part.

[0139] It should be understood that although the steps in the flowchart of the accompanying drawings are shown sequentially in the direction of the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear indication in this document, there is no strict order restriction for the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0140] The above are only some embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A mine safety monitoring method based on 5G big data, characterized in that: include: Based on the 5G communication network, obtain safety monitoring data and historical monitoring information at different locations in the preset area of ​​the mine; Performing data cleaning and integration processing on the safety monitoring data to obtain processed safety monitoring data; Performing abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain current abnormal information and safety warning information within a preset time period; The performing abnormal warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain current abnormal information and safety warning information within a preset time period includes: Analyze the historical monitoring information to obtain monitoring data of different mine locations at different times in the historical monitoring information and data change sequences of different mine locations at different unit times; Associating the monitoring data and the data change sequence according to the mine location to obtain first associated data; Based on the monitoring data and the data change sequence, associating the data corresponding to the adjacent mine locations of each mine location with the first associated data to obtain second associated data; Determine monitoring parameter characteristics and time series length based on the second associated data, and predict the historical monitoring information according to the monitoring parameter characteristics and time series length to obtain parameter data sequences in which different monitoring parameter characteristics change over time; Determine the time node information and monitoring location information when the safety monitoring data is acquired, and determine the target data sequence corresponding to the parameter data sequence according to the time node information and monitoring location information; Determine whether there is a preset abnormal range of data in the target data sequence, and if so, perform warning processing on the sequence nodes in the target data sequence that have the preset abnormal range of data based on the abnormal warning standard information to obtain safety warning information; Control and display the current abnormal information and safety warning information.

2. According to a method for mine safety monitoring based on 5G big data according to claim 1, it is characterized in that: The method of obtaining safety monitoring data and historical monitoring information at different locations within a preset area of ​​a mine based on a 5G communication network also includes: Obtain reflector information and signal strength data, wherein the reflector information is angle information and reflecting surface information corresponding to a signal reflector pre-installed at a specified location, and the signal strength data is signal strength data of a 5G communication network; Analyze the signal strength data to identify signal abnormality locations in the mine where there are signal blind spots or signal weak spots; An adjustment instruction is determined based on the signal abnormality position and the reflector information to control and adjust the angle parameters and the reflection surface parameters in the signal reflector.

3. A mine safety monitoring method based on 5G big data according to claim 2, characterized in that: The obtaining of reflector information and signal strength data also includes: Acquiring monitoring status data of the signal reflector, wherein the monitoring status data includes real-time monitoring data and historical monitoring data; Predicting the signal reflector based on the monitoring status data to determine a suspected fault point of the signal reflector; Fault maintenance information is generated based on the suspected fault point, and the fault maintenance information is sent to a terminal device of a maintenance personnel.

4. A mine safety monitoring method based on 5G big data according to claim 3, characterized in that: The predicting the signal reflector based on the monitoring status data to determine a suspected fault point of the signal reflector includes: Determine the reflection coefficient and key operating parameters of the reflector based on the historical monitoring data in the monitoring status data; Performing data processing on the reflection coefficient and the key operating parameters to obtain processed reflection coefficient and the key operating parameters; Performing feature extraction on the processed reflection coefficient and key operating parameters to extract fault features related to the signal reflector fault; Creating a prediction model, and training the prediction model according to the fault characteristics to obtain a trained prediction model; The real-time monitoring data is input into the prediction model for prediction to determine the suspected fault point of the signal reflector.

5. The mine safety monitoring method based on 5G big data according to claim 1 is characterized in that: The control displays the current abnormal information and safety warning information, and then further includes: Acquire mine image information, and construct a three-dimensional mine environment based on features in the mine image information; Retrieving the personnel information responsible for maintaining different areas in the mine respectively, and connecting the personnel information to the three-dimensional environment of the mine; The current abnormal information and the safety warning information are connected to the three-dimensional environment of the mine. According to the activity of the personnel information and the resource allocation in the three-dimensional environment of the mine, the maintenance personnel responsible for the current abnormal information and the safety warning information are dynamically selected, and the maintenance personnel are authorized to view the current abnormal information and the safety warning information.

6. A mine safety monitoring system based on 5G big data, characterized in that: include: An information acquisition module is used to obtain safety monitoring data and historical monitoring information at different locations within a preset area of ​​the mine based on a 5G communication network; A data processing module is used to perform data cleaning and integration processing on the safety monitoring data to obtain processed safety monitoring data; An abnormality analysis module, used to perform abnormality warning analysis on the processed safety monitoring data according to the historical monitoring information, and obtain current abnormality information and safety warning information within a preset time period; When the abnormality analysis module performs abnormality warning analysis on the processed safety monitoring data according to the historical monitoring information to obtain the current abnormality information and the safety warning information within a preset time period, it is specifically used to: Analyze the historical monitoring information to obtain monitoring data of different mine locations at different times in the historical monitoring information and data change sequences of different mine locations at different unit times; Associating the monitoring data and the data change sequence according to the mine location to obtain first associated data; Based on the monitoring data and the data change sequence, associating the data corresponding to the adjacent mine locations of each mine location with the first associated data to obtain second associated data; Determine monitoring parameter characteristics and time series length based on the second associated data, and predict the historical monitoring information according to the monitoring parameter characteristics and time series length to obtain parameter data sequences in which different monitoring parameter characteristics change over time; Determine the time node information and monitoring location information when the safety monitoring data is acquired, and determine the target data sequence corresponding to the parameter data sequence according to the time node information and monitoring location information; Determine whether there is a preset abnormal range of data in the target data sequence, and if so, perform warning processing on the sequence nodes in the target data sequence that have the preset abnormal range of data based on the abnormal warning standard information to obtain safety warning information; The control display module is used to control the display of the current abnormal information and safety warning information.

7. An electronic device, characterized in that: include: at least one processor; Memory; At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a mine safety monitoring method based on 5G big data as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and executed according to any one of claims 1 to 5, for a mine safety monitoring method based on 5G big data.

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