Visual analysis method and device for coal mine disaster monitoring and early warning data

Abstract

The invention provides a visual analysis method and device for coal mine disaster monitoring and early warning data. The method comprises the following steps: receiving instruction information of selecting one report visualization template library from at least one report visualization template library by a user; acquiring historical operation behavior information and preference information of the user based on the user information; based on the historical operation behavior information, using a pre-trained long short-term memory (LSTM) network model to predict future operation behavior information of the user and data items of disaster early warning data of interest; generating a recommended report processing template according to the future operation behavior information and the data items of the interested disaster early warning data in combination with a report visualization template library; and under the condition that the user selects the recommended report processing template, a visual report custom interface is provided, so that the user can conveniently carry out custom configuration. According to the application, the coal mine disaster monitoring and early warning efficiency can be improved, the data visualization effect is improved, and accurate data sharing and analysis are realized.

Description

Technical Field

[0001] The present application relates to the technical field of coal mine safety monitoring, and in particular to a method, device and electronic equipment for visual analysis of coal mine disaster monitoring and early warning data. Background Art

[0002] In the coal mine production process, coal mine disaster monitoring and early warning report data processing is a key link in production management. In related technologies, manual filling and calculation of reports are usually used to form coal mine disaster monitoring and early warning reports. However, the large number of coal mine disasters leads to complex and numerous daily report types. Technical personnel rely on Excel processing, which is a huge workload and inefficient, and it is even more difficult to ensure the accuracy and timeliness of data. Summary of the invention

[0003] The embodiments of the present application provide a method, device and electronic equipment for visual analysis of coal mine disaster monitoring and early warning data.

[0004] According to a first aspect of an embodiment of the present application, a method for visualizing and analyzing coal mine disaster monitoring and early warning data is provided, comprising: receiving instruction information of a user selecting a report visualization template library from at least one report visualization template library; the instruction information includes user information of the user; at least one report visualization template library corresponds to different report application scenarios, and each report visualization template library is associated with multiple basic visualization chart templates; Based on user information, historical operation behavior information and preference information of users in the coal mine disaster monitoring and early warning system are obtained; Based on historical operation behavior information, a pre-trained long short-term memory network LSTM model is used to predict the user's future operation behavior information and data items of interested disaster warning data; According to the user's future operation behavior information and the data items of the disaster warning data of interest, combined with the selected report visualization template library, a recommended report processing template matching the category of the disaster warning data of interest is generated; When the user selects a recommended report processing template, a visual report customization interface is provided, and the recommended report processing template is rendered based on the user's operations in the report customization interface and real-time disaster monitoring data; wherein, the report customization interface displays relevant indicators of the disaster warning data of interest and basic visualization chart templates associated with the relevant indicators, and the basic visualization chart templates associated with the relevant indicators are determined based on historical operation behavior information and preference information.

[0005] According to a second aspect of an embodiment of the present application, a visual analysis device for coal mine disaster monitoring and early warning data is provided, comprising: A receiving module, used for receiving instruction information of a user selecting a report visualization template library from at least one report visualization template library; the instruction information includes user information of the user; at least one report visualization template library corresponds to different report application scenarios, and each report visualization template library is associated with multiple basic visualization chart templates; An acquisition module is used to acquire historical operation behavior information and preference information of the user in the coal mine disaster monitoring and early warning system based on the user information; A prediction module is used to predict the user's future operation behavior information and the data items of the disaster warning data of interest based on the historical operation behavior information by using a pre-trained long short-term memory network LSTM model; A generation module, for generating a recommended report processing template matching the category of the disaster warning data of interest based on the user's future operation behavior information and the data items of the disaster warning data of interest, in combination with the selected report visualization template library; A rendering module is used to provide a visual report customization interface when a user selects a recommended report processing template, and to render the recommended report processing template based on the user's operations in the report customization interface and real-time disaster monitoring data; wherein the report customization interface displays relevant indicators of the disaster warning data of interest and basic visualization chart templates associated with the relevant indicators, and the basic visualization chart templates associated with the relevant indicators are determined based on the historical operation behavior information and the preference information.

[0006] According to a third aspect of an embodiment of the present application, a coal mine disaster monitoring and early warning system is provided, comprising the visual analysis device for coal mine disaster monitoring and early warning data as described in the second aspect above.

[0007] According to a fourth aspect of an embodiment of the present application, there is provided an electronic device, including: at least one processor; and a memory communicatively connected to at least one processor; wherein, The memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor so that the at least one processor can execute the method described in the first aspect above.

[0008] According to the technical solution of the present application, by introducing the LSTM model to mine the user's operation behavior pattern, it is possible to accurately predict the user's usage habits, intelligently recommend a suitable report processing template to the user based on the prediction results, and provide the user with a report customization interface based on the user's usage habits and preference information when the user selects the recommended report processing template, so that the user can customize the report based on the recommended report processing template, meet the diverse needs, and save the user's operation steps and time cost of creating reports, thereby improving the efficiency of coal mine disaster monitoring and early warning, improving data visualization, and realizing accurate data sharing and analysis. The present application can render the recommended report processing template based on the user's operations in the report customization interface and real-time disaster monitoring data to automatically achieve data adaptation, and can also ensure the accuracy and timeliness of the data in the report.

[0009] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which: Figure 1 A flow chart of a method for visualizing and analyzing coal mine disaster monitoring and early warning data provided in an embodiment of the present application; Figure 2 A block diagram of a visual analysis device for coal mine disaster monitoring and early warning data provided in an embodiment of the present application; Figure 3 is a block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0011] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0012] The terms used in one or more embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of the present application. The singular forms of "a", "said" and "the" used in one or more embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of the present application refers to and includes any or all possible combinations of one or more associated listed items.

[0013] It should be understood that, although the terms first, second, etc. may be used to describe various information in one or more embodiments of the present application, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0014] It should be noted that in the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals. The information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with the relevant laws, regulations and standards of relevant countries and regions.

[0015] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0016] In the coal mine production process, the data processing of coal mine disaster monitoring and early warning reports is a key link in production management, but there are many problems with existing technologies. In the early days, reports were mostly filled out and calculated manually, which not only consumed a lot of manpower, but was also prone to errors and made it difficult to ensure the accuracy and timeliness of the data. With the development of technology, reporting tools such as Excel, BIRT (Business Intelligence and Reporting Tools) and report processing systems based on coal mine disaster early warning systems have emerged one after another, which have alleviated the pressure of manual processing to a certain extent, but have still failed to fundamentally solve the problem.

[0017] The large number of coal mine disasters has led to complex daily report types and a large number of them. Technical personnel rely on Excel processing, which is a huge workload and inefficient. Coal mine disaster data has multi-source heterogeneous characteristics. Its sources include sensors, instruments, smart terminals, and manual entry. The data types are diverse and the quality is uneven, which increases the difficulty of report processing, and the development and use thresholds are high, and the professional requirements for developers and implementers are strict. At the same time, the reporting system is highly customized, closely related to disasters and businesses, difficult to transplant and promote, fixed data flows, poor data scalability, and cannot meet the needs of other applications or systems. Moreover, the report type is single, and the content is not designed for different user roles, which is not conducive to decision makers to fully grasp the information and affects decision-making efficiency. At the same time, the existing system is difficult to meet the diverse needs of different users in different usage scenarios. It lacks accurate data push and personalized report display functions, and cannot effectively assist coal mine production decisions.

[0018] Based on this, the embodiments of the present application provide a method, device and electronic equipment for visual analysis of coal mine disaster monitoring and early warning data, which can improve the efficiency of coal mine disaster monitoring and early warning, enhance data visualization effects, and realize accurate data sharing and analysis.

[0019] The following describes the visualization analysis method, device and electronic equipment for coal mine disaster monitoring and early warning data in an embodiment of the present application with reference to the accompanying drawings.

[0020] Among them, it should be noted that the execution subject of the visualization analysis method of coal mine disaster monitoring and early warning data in the embodiment of the present application can be a visualization analysis device for coal mine disaster monitoring and early warning data, which can be implemented by software and / or hardware. The device can be included in a coal mine disaster monitoring and early warning system. Exemplarily, the coal mine disaster monitoring and early warning system can be configured in an electronic device. Exemplarily, the electronic device can include but is not limited to a terminal, a server, etc. It should also be noted that in some embodiments, the terms "coal mine disaster data", "coal mine disaster monitoring and early warning data", "disaster data", "disaster early warning data", "coal mine disaster monitoring data", "disaster monitoring data" and the like can be replaced with each other.

[0021] Figure 1 This is a flow chart of a method for visualizing and analyzing coal mine disaster monitoring and early warning data provided in an embodiment of the present application. Figure 1 As shown, the visualization analysis method of coal mine disaster monitoring and early warning data may include but is not limited to the following steps.

[0022] In step 101, an instruction message of a user selecting a report visualization template library from at least one report visualization template library is received, wherein the instruction message may include but is not limited to user information of the user. Exemplarily, the user information may include but is not limited to a user identifier (such as a user ID) and the like.

[0023] In some embodiments, at least one report visualization template library may correspond to different report application scenarios. Exemplarily, the report application scenarios may include 6 types, such as disaster report overview application scenarios, data query application scenarios, data periodic storage application scenarios, data historical analysis application scenarios, data anomaly tracking application scenarios, and decision-making assistance application scenarios. According to the 6 different report application scenarios, 6 report visualization template libraries may be divided, for example, disaster report overview template library, query processing report template library, periodic storage report template library, historical analysis report template library, anomaly tracking report template library, and decision-making assistance report template library. Exemplarily, the disaster report overview template library can provide an overall view of coal mine disaster data, displaying comprehensive data of six disasters: gas, water damage, roof pressure, rock burst, fire, and dust. The disaster report overview template library may have a comprehensive dashboard style, which displays data in the form of charts such as bar charts, pie charts, regional heat maps, and maps through a comprehensive dashboard, and can intuitively display the frequency, severity, and spatial distribution of various disasters, which is used to quickly understand the overall disaster situation of coal mines, and has a real-time data update function to ensure that the displayed information is the latest.

[0024] For example, the query processing report template library can be used to filter and retrieve data according to different conditions and display them visually, such as disaster type, time range, severity, etc. The template supports multi-condition combination query and can handle complex query requirements. In order to improve query efficiency, it also has data sorting and grouping functions, for example, you can sort query results by time, location or disaster type, or group and count data by different disaster types, and support list view and chart view result display methods.

[0025] For example, the periodic storage report template library can be used to record and display disaster data stored regularly (such as daily, weekly, and monthly), and store them by time period, supporting the aggregation and comparison of data within the period, such as the monthly periodic storage report of roof pressure, which displays the roof pressure data curve graph within a certain month and indicates the maximum value, average value, abnormal points, etc. In the periodic storage report template, data query and access are also provided, and a certain disaster data record within a specific time period can be viewed as needed.

[0026] Exemplarily, the historical analysis report template library can be used to display and analyze long-term coal mine disaster data trends. The template supports time series analysis and provides trend charts, curve charts, waterfall charts and other chart types suitable for data analysis. Optionally, the embodiment of the present application can also identify the periodicity, seasonality or other correlations of disasters through analysis of historical data in historical analysis reports, thereby predicting future disaster risks. The historical analysis report template also supports a variety of data analysis methods such as statistical analysis and regression analysis, and provides flexible data selection and analysis tools. For example, when obtaining a historical analysis report, the system background can use a variety of data analysis methods such as statistical analysis and regression analysis to analyze the data in the historical analysis report.

[0027] Exemplarily, the exception tracking report template library can be used to handle abnormal situations in coal mine disaster monitoring data, promptly identify potential problems and take measures. The exception tracking report template has the ability to automatically detect abnormal data. For example, the system background can identify abnormal events or data points that are beyond the normal range, and perform detailed abnormal records and tracking in the exception tracking report template, including the time, location, cause and processing status of the abnormality, and display warning information. When an abnormality is detected, detailed abnormal information and recommended handling measures can also be provided in a timely manner in the exception tracking report template. The exception tracking report template also supports the recording and auditing of the exception handling process to ensure that abnormal events are handled in a timely and effective manner.

[0028] For example, the decision-making support report template library can be used to provide data-driven decision support and help formulate effective management and safety strategies. The decision-making support report template integrates various data sources, integrates different types of data, provides comprehensive data analysis tools and visual reports, supports in-depth analysis of six disaster data such as coal mine gas, water damage, roof pressure, rock burst, fire and dust, and generates decision support reports and suggestions. The decision-making support report template can generate strategic decision reports, risk assessment reports and action plan suggestions to support decision-making needs at different levels.

[0029] In some embodiments, each report visualization template library is associated with a variety of basic visualization chart templates. Exemplarily, the basic visualization chart templates can be configured in the visualization chart library. In some embodiments, the visualization chart library and the report visualization template library can be pre-established in the following ways: using a dual-dimensional classification mechanism, combining a variety of preset basic visualization chart templates according to disaster types and chart forms to establish a visualization chart library; using dynamic parameter binding technology to bind corresponding parameters to each basic visualization chart template, the parameters include at least data fields, chart attributes and display rules; based on the report application scenario, the basic visualization chart templates that match the report application scenario are screened out from the established visualization chart library, and a report visualization template library corresponding to the report application scenario is established based on the screened basic visualization chart templates.

[0030] For example, a dual-dimensional classification mechanism can be used to combine a variety of preset basic visualization chart templates according to the type of disaster and the form of the chart. From the dimension of disaster type, it is divided into six major categories: gas, rock burst, roof pressure, water damage, fire, and dust; from the dimension of chart form, it covers nine basic types: bar chart, curve chart, area chart, bar chart, pie chart, sliding window trend chart, heat map, coupling area chart, and correlation matrix chart. For example, the gas template subset can include style designs such as concentration change trend curve chart, over-limit area heat map, and outflow statistical bar chart, as shown in Table 1 below, which shows the visualization template configuration scheme for various types of disaster data.

[0031] Table 1 Visualization template configuration scheme for various disaster data

[0032] Dynamic parameter binding technology is used to bind corresponding parameters to each basic visualization chart template. Each basic visualization chart template predefines three core parameter groups: data fields, chart attributes, and display rules. After completing the mapping relationship configuration between real-time monitoring data fields and template parameters through the visualization configuration interface, the system can automatically adapt the data. For example, when the user selects the "Maximum Drilling Stress-Histogram" template, the monitoring area, time range, warning threshold and other parameters are specified through the parameter configuration interface. The system can generate a visualization chart based on the preset color scheme, axis scale and annotation rules in the basic visualization chart template.

[0033] On the basis of the above-established basic visualization chart templates, a report visualization template library corresponding to different report application scenarios can be established. Exemplarily, for each report application scenario, based on the report application scenario, the basic visualization chart template matching the report application scenario can be screened out from the established visualization chart library, and the screened basic visualization chart templates can be combined to establish a report visualization template library corresponding to the report application scenario, so that a report visualization template library under different report application scenarios can be obtained. Thus, by constructing a report visualization template library and formulating visualization standards, the standardized and normalized display of coal mine disaster data can be achieved. The template libraries formulated for a variety of different application scenarios have different functions. The overview report provides an overall view of coal mine disaster data, the query processing report supports natural language query, the periodic storage report can intelligently adjust the storage period, the historical analysis report can analyze disaster risks, the abnormal tracking report monitors and warns in real time, and the auxiliary decision report provides decision suggestions. Users can quickly select the appropriate style from the rich template library, or customize and generate high-quality reports through simple operations, which greatly shortens the report production time and improves work efficiency.

[0034] In an embodiment of the present application, when a user uses a coal mine disaster monitoring and early warning system, a user interaction interface is provided to the user. The user interaction interface may have a selection control for a pre-established report visualization template library. The user can use the selection control to select which report visualization template library to use. After the user confirms the selection, the electronic device can receive instruction information from the user to select a report visualization template library from at least one report visualization template library. The instruction information may include the user information of the user, and may also include an identifier of the selected report visualization template library to indicate which specific report visualization template library is selected.

[0035] Optionally, in some embodiments, an upgrade instruction of at least one of a visualization chart library and a report visualization template library may be received; based on the upgrade instruction, at least one of the visualization chart library and the report visualization template library may be upgraded. Exemplarily, when the visualization chart library and / or the report visualization template library in the coal mine disaster monitoring and early warning system need to be upgraded, the cloud server may send an upgrade instruction for the visualization chart library and / or the report visualization template library to the client of the coal mine disaster monitoring and early warning system, and when the client receives the upgrade instruction, the visualization chart library and / or the report visualization template library may be upgraded. Exemplarily, the upgrade of the visualization chart library and / or the report visualization template library may support breakpoint resume technology. Thus, when the visualization chart and / or the report visualization template need to be updated, it is only necessary to upgrade the visualization chart library and / or the report visualization template library in the coal mine disaster monitoring and early warning system, which can greatly reduce the development cost.

[0036] In step 102, historical operation behavior information and preference information of the user in the coal mine disaster monitoring and early warning system is obtained based on the user information.

[0037] In an embodiment of the present application, the historical operation behavior information and preference information of the user in the coal mine disaster monitoring and early warning system can be obtained based on the historical behavior operation data, and stored in the database in the coal mine disaster monitoring and early warning system, so that it can be obtained from the database based on the user information when in use. Exemplarily, the historical operation behavior information of the user (such as a technician, but not limited to this) in the coal mine disaster monitoring and early warning system in multiple dimensions such as operation logs, access frequency, common functions, data item selection, operation duration, number of wrong operations, etc. can be collected in advance, and these data can be deeply mined and analyzed to accurately identify the user's usage mode and preference. Optionally, the historical operation behavior information can also include text information, feedback opinions, etc. input by the user in the coal mine disaster monitoring and early warning system. Natural language processing technology can be used to perform sentiment analysis and semantic understanding on the text information and feedback opinions input by the user in the system, and to mine its hidden needs and preferences, thereby obtaining the user's preference information. For example, if the user frequently mentions in the feedback that the analysis of certain data is not intuitive enough, the coal mine disaster monitoring and early warning system can identify its need for improvement of the visualization effect of the data.

[0038] In step 103, based on the historical operation behavior information, a pre-trained long short-term memory network (LSTM) model is used to predict the user's future operation behavior information and data items of the disaster warning data of interest.

[0039] In the embodiment of the present application, the forget gate in the LSTM model , Input Gate , output gate Respectively expressed as:

[0040]

[0041]

[0042] in, is the sigmoid activation function, , , are the weight parameters calculated for the three structural gates, Indicates the state of the memory unit at the previous moment, represents the output of the memory unit at the previous moment, Represents the input at the current moment, , , The bias items calculated for the three types of structural gates are as follows. The parameter information contained in the technician's operation behavior at the current moment can be comprehensively considered. and Output:

[0043] in , Respectively represent the state of the memory unit at the current moment and the previous moment, is the state of the candidate unit at the previous moment.

[0044] That is to say, in an embodiment of the present application, an LSTM architecture can be introduced to capture the long-term and short-term dependencies in the user's operation behavior sequence. Exemplarily, the user's operation behavior information can be encoded and converted into a vector representation suitable for LSTM model processing. During the model training process, the model can learn the association and importance between different operation behaviors by adjusting the memory unit weights. For example, for users who often view a certain type of report in a specific time period and frequently perform specific data screening operations, the model can identify the close connection between these behaviors, and train the model through a large amount of historical behavior data, so that it can accurately predict the user's future operation behavior information and data items of disaster warning data that may be of interest.

[0045] In step 104, based on the user's future operation behavior information and the data items of the disaster warning data of interest, combined with the selected report visualization template library, a recommended report processing template matching the category of the disaster warning data of interest is generated.

[0046] In an embodiment of the present application, based on the user's future operation behavior information predicted by the LSTM model and the data items of the disaster warning data of interest, combined with the report visualization template library selected by the user, a recommended report processing template matching the category of the disaster warning data of interest can be generated. For example, the user selects a type of report visualization template library in the report visualization template library, such as a query processing report template library. The system determines that the user frequently accesses the gas concentration monitoring data in the current month based on the user's usage habits (operation behavior information). The system can generate a recommended report processing template matching the category of the disaster warning data of interest (such as gas concentration monitoring data) based on the user's future operation behavior information predicted by the LSTM model and the data items of the disaster warning data of interest (such as gas concentration monitoring data), combined with the query processing report template library selected by the user, that is, the gas disaster data query processing report template can be intelligently recommended to the user.

[0047] In step 105, when the user selects the recommended report processing template, a visual report customization interface is provided, and the recommended report processing template is rendered based on the user's operation in the report customization interface and the real-time disaster monitoring data. The report customization interface displays the relevant indicators of the disaster warning data of interest and the basic visualization chart templates associated with the relevant indicators, and the basic visualization chart templates associated with the relevant indicators are determined based on the historical operation behavior information and the preference information.

[0048] For example, when the user selects a recommended report processing template, such as a gas disaster data query processing report template, the system can provide a visual report customization interface to display relevant indicators (such as all indicators) of the disaster warning data of interest (such as disaster warning data of gas disaster type) and basic visualization chart templates associated with the relevant indicators. For example, the relevant indicators of the disaster warning data of the gas disaster type may include gas concentration peak ratio, change rate, number of times exceeding blue warning, gas outburst volume, inverted gas content, etc.

[0049] The system can render the recommended report processing template based on the user's operations in the report customization interface and the real-time disaster monitoring data, and can automatically achieve data adaptation, that is, the report obtained after rendering is based on the real-time disaster monitoring data, which is convenient for users to understand the real-time disaster monitoring data in the coal mine through the visual report. In a possible implementation method, based on the user's indicator configuration operation in the report customization interface, the real-time disaster monitoring data to be processed that matches the indicator configuration operation can be obtained from the data warehouse; the indicator configuration operation includes the selection of specific indicators and / or the selection of data ranges; based on the application scenario associated with the recommended report processing template, the real-time disaster monitoring data to be processed is processed accordingly to obtain disaster warning data, and based on the user's basic visualization chart template configuration operation in the report customization interface, the disaster warning data is filled into the user-configured basic visualization chart template.

[0050] In some embodiments, users can be supported to flexibly adjust chart styles, report structures, and edit text, etc., to ensure that the display of each element is more in line with user habits. Users can also save customized reports into the report visualization template library for easy use next time.

[0051] In some embodiments, the layout of the recommended report processing template can be adjusted using an intelligent layout algorithm based on historical operation behavior information and preference information. Exemplarily, when recommending a report processing template to a user, the layout of the recommended report processing template can also be adjusted using an intelligent layout algorithm based on the user's historical operation behavior information and preference information, for example, placing data items that the user frequently views in a prominent position in the report, and displaying them in a more intuitive chart form, etc. Exemplarily, the intelligent layout algorithm can be based on machine learning and deep learning technology to achieve automated, dynamic and personalized layout optimization, but is not limited to this. For example, machine learning and deep learning technology can be used to automatically recommend user-preferred layout styles based on historical data, or dynamically adjust the prominence of key information in the report, such as training a model based on labeled data to predict the priority or layout mode of elements; or optimize layout strategies through user feedback (such as click-through rate, dwell time).

[0052] In some embodiments, the layout, content and display method of the recommended report processing template can be adjusted according to the user's personnel information and / or the usage scenario of the coal mine disaster monitoring and early warning system. Among them, the user's personnel information may include but is not limited to the user's department, role, etc. Exemplarily, the user's user ID can be used to obtain the user's personnel information, such as the user's department, role, etc., and the layout, content and display method of the recommended report processing template can be adjusted according to the user's department, role, usage scenario of the coal mine disaster monitoring and early warning system, etc., to ensure that the report can provide the best user experience in different devices and environments. For example, when a user uses a mobile device such as a mobile phone to access, the size and layout of the charts in the recommended report processing template page can be automatically adjusted to ensure that the data is clear and readable, and to improve the convenience and efficiency of user operations.

[0053] It is worth noting that the coal mine disaster monitoring data may come from various sensors and monitoring equipment. In order to facilitate data management and processing, the original disaster monitoring data from multiple monitoring sources can be standardized. Optionally, in some embodiments, various original disaster monitoring data from multiple monitoring sources can be obtained in real time by interfacing with various sensors and monitoring equipment in coal mines; the obtained original disaster monitoring data is formatted to obtain real-time disaster monitoring data that meets the unified data standard; the formatting process includes at least one of the following operations: data type verification, unit conversion, and data cleaning; the real-time disaster monitoring data obtained after the formatting process is stored in a data warehouse, which is a distributed column-based database that supports efficient query and analysis.

[0054] Exemplarily, the types of disaster monitoring data may include but are not limited to gas, water damage, roof pressure, rock burst, fire and dust. The coal mine disaster monitoring and early warning system can be interfaced with various sensors and monitoring equipment in the coal mine to obtain various disaster monitoring data such as gas, water damage, roof pressure, rock burst, fire and dust in real time. For example, the gas concentration sensor uploads data once a minute, and the roof pressure sensor uploads data regularly at a set time interval. Optionally, the coal mine disaster monitoring and early warning system can communicate with various sensors and monitoring equipment in the coal mine using message middleware, thereby ensuring the efficiency and stability of data transmission.

[0055] Exemplarily, the collected raw disaster monitoring data can be formatted to meet unified data standards, for example, it can include data type verification, unit conversion and data cleaning operations, such as converting the unit of gas concentration from mg / m3 to percentage, and ensuring that the value is within a reasonable range. Optionally, missing values ​​and abnormal values ​​that deviate significantly from the normal range can also be processed to ensure that the processed data has high availability. Optionally, a distributed columnar data warehouse that supports efficient query and analysis can be used to manage processed data and perform regular data backup to ensure data security and integrity.

[0056] In the above embodiment, by introducing the LSTM model to mine the user's operation behavior pattern, it is possible to accurately predict the user's usage habits, intelligently recommend a suitable report processing template to the user based on the prediction results, and provide the user with a report customization interface based on the user's usage habits and preference information when the user selects the recommended report processing template, so that the user can customize the report based on the recommended report processing template, meet the diverse needs, and save the user's operation steps and time cost of creating reports, thereby improving the efficiency of coal mine disaster monitoring and early warning, improving data visualization effects, and realizing accurate data sharing and analysis. The present application can render the recommended report processing template based on the user's operations in the report customization interface and real-time disaster monitoring data to automatically achieve data adaptation, and can also ensure the accuracy and timeliness of the data in the report.

[0057] Figure 2 A block diagram of a visual analysis device for coal mine disaster monitoring and early warning data provided in an embodiment of the present application. Figure 2 As shown, the visualization analysis device for coal mine disaster monitoring and early warning data may include: a receiving module 201 , an acquisition module 202 , a prediction module 203 , a generation module 204 and a rendering module 205 .

[0058] Among them, the receiving module 201 is used to receive instruction information from a user to select a report visualization template library from at least one report visualization template library; the instruction information includes user information of the user; at least one report visualization template library corresponds to different report application scenarios, and each report visualization template library is associated with multiple basic visualization chart templates.

[0059] The acquisition module 202 is used to acquire the historical operation behavior information and preference information of the user in the coal mine disaster monitoring and early warning system based on the user information.

[0060] The prediction module 203 is used to predict the user's future operation behavior information and data items of the disaster warning data of interest based on the historical operation behavior information by using a pre-trained long short-term memory network LSTM model.

[0061] The generation module 204 is used to generate a recommended report processing template matching the category of the disaster warning data of interest based on the user's future operation behavior information and the data items of the disaster warning data of interest, in combination with the selected report visualization template library.

[0062] The rendering module 205 is used to provide a visual report customization interface when the user selects a recommended report processing template, and to render the recommended report processing template based on the user's operations in the report customization interface and real-time disaster monitoring data; wherein the report customization interface displays relevant indicators of the disaster warning data of interest and basic visualization chart templates associated with the relevant indicators, and the basic visualization chart templates associated with the relevant indicators are determined based on historical operation behavior information and preference information.

[0063] In some embodiments, the visualization analysis device for coal mine disaster monitoring and early warning data may also include a data acquisition and normalization module. The data acquisition and normalization module is used to: obtain a variety of original disaster monitoring data from multiple monitoring sources in real time by interfacing with various sensors and monitoring equipment in coal mines; format the acquired original disaster monitoring data to obtain real-time disaster monitoring data that meets the unified data standard; the formatting process includes at least one of a data type verification operation, a unit conversion operation, and a data cleaning operation; and store the real-time disaster monitoring data obtained after the formatting process in a data warehouse, which is a distributed column database that supports efficient query and analysis.

[0064] In some embodiments, the rendering module 205 is used to: based on the indicator configuration operation performed by the user in the report customization interface, obtain the real-time disaster monitoring data to be processed that matches the indicator configuration operation from the data warehouse; the indicator configuration operation includes the selection of specific indicators and / or the selection of data ranges; based on the application scenario associated with the recommended report processing template, perform corresponding processing on the real-time disaster monitoring data to be processed to obtain disaster warning data, and based on the basic visualization chart template configuration operation performed by the user in the report customization interface, fill the disaster warning data into the basic visualization chart template configured by the user.

[0065] In some embodiments, the rendering module 205 is further used to: based on the historical operation behavior information and the preference information, use an intelligent layout algorithm to adjust the layout of the recommended report processing template.

[0066] In some embodiments, the rendering module 205 is further used to adjust the layout, content and display method of the recommended report processing template according to the user's personnel information and / or the usage scenario of the coal mine disaster monitoring and early warning system.

[0067] In some embodiments, the visualization analysis device for coal mine disaster monitoring and early warning data may also include a template establishment module. The template establishment module is used to: adopt a dual-dimensional classification mechanism to combine a variety of preset basic visualization chart templates according to the disaster type and chart form to establish a visualization chart library; adopt dynamic parameter binding technology to bind corresponding parameters to each basic visualization chart template, and the parameters include at least data fields, chart attributes and display rules; based on the report application scenario, filter out the basic visualization chart template that matches the report application scenario from the established visualization chart library, and establish a report visualization template library corresponding to the report application scenario based on the filtered basic visualization chart template.

[0068] In some embodiments, the visual analysis device for coal mine disaster monitoring and early warning data may further include an upgrade module, wherein the upgrade module is used to: receive an upgrade instruction of at least one of the visualization chart library and the report visualization template library; and upgrade at least one of the visualization chart library and the report visualization template library based on the upgrade instruction.

[0069] It should be noted that the above explanation of the embodiment of the method for visual analysis of coal mine disaster monitoring and early warning data is also applicable to the device for visual analysis of coal mine disaster monitoring and early warning data of this embodiment, and will not be repeated here.

[0070] Based on the above embodiments, the embodiments of the present application also provide a coal mine disaster monitoring and early warning system, including a visualization analysis device for coal mine disaster monitoring and early warning data involved in any of the aforementioned device embodiments, wherein the function and structure of the visualization analysis device for coal mine disaster monitoring and early warning data can be referred to the optional implementation method described in the aforementioned device embodiment, which will not be repeated here.

[0071] According to an embodiment of the present application, the present application also provides an electronic device and a readable storage medium.

[0072] like Figure 3 , is a block diagram of an electronic device according to an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. Exemplarily, the electronic device can be a wearable exoskeleton device, and exemplary, the exoskeleton device can have an electromyographic signal acquisition module for collecting electromyographic signals. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0073] like Figure 3 As shown, the electronic device includes: one or more processors 301, a memory 302, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In other embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 3 A processor 301 is taken as an example.

[0074] The memory 302 is a non-transitory computer-readable storage medium provided in the present application. The memory stores instructions executable by at least one processor, so that the at least one processor executes the visualization analysis method for coal mine disaster monitoring and early warning data provided in the present application. The non-transitory computer-readable storage medium of the present application stores computer instructions, which are used to enable a computer to execute the visualization analysis method for coal mine disaster monitoring and early warning data provided in the present application.

[0075] The memory 302 is a non-transient computer-readable storage medium that can be used to store non-transient software programs, non-transient computer executable programs and modules, such as the program instructions / modules corresponding to the visualization analysis method for coal mine disaster monitoring and early warning data in the embodiment of the present application (for example, the attached Figure 2 The processor 301 executes various functional applications and data processing of the server by running the non-transient software programs, instructions and modules stored in the memory 302, that is, the visualization analysis method of coal mine disaster monitoring and early warning data in the above method embodiment is realized.

[0076] The memory 302 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 302 may optionally include a memory remotely arranged relative to the processor 301, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0077] The electronic device may further include: an input device 303 and an output device 304. The processor 301, the memory 302, the input device 303 and the output device 304 may be connected via a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0078] The input device 303 can receive input digital or character information, and generate key signal input related to user settings and function control of the electronic device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator rod, one or more mouse buttons, a trackball, a joystick, and other input devices. The output device 304 may include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display, and a plasma display. In some embodiments, the display device may be a touch screen.

[0079] Various implementations of the systems and techniques described herein can be realized in digital electronic circuit systems, integrated circuit systems, dedicated ASICs (application specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0080] These computer programs (also referred to as programs, software, software applications, or code) include machine instructions for programmable processors and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or means (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0081] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0082] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0083] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0084] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0085] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A visual analysis method for coal mine disaster monitoring and early warning data, characterized in that: include: receiving instruction information of a user selecting a report visualization template library from at least one report visualization template library; The instruction information includes user information of the user; The at least one report visualization template library corresponds to different report application scenarios, and each report visualization template library is associated with a plurality of basic visualization chart templates; Based on the user information, historical operation behavior information and preference information of the user in the coal mine disaster monitoring and early warning system are obtained; Based on the historical operation behavior information, a pre-trained long short-term memory network LSTM model is used to predict the user's future operation behavior information and data items of the disaster warning data of interest; According to the user's future operation behavior information and the data items of the disaster warning data of interest, combined with the selected report visualization template library, a recommended report processing template matching the category of the disaster warning data of interest is generated; When the user selects the recommended report processing template, a visual report customization interface is provided, and the recommended report processing template is rendered based on the user's operations in the report customization interface and real-time disaster monitoring data; wherein, the report customization interface displays relevant indicators of the disaster warning data of interest and basic visualization chart templates associated with the relevant indicators, and the basic visualization chart templates associated with the relevant indicators are determined based on the historical operation behavior information and the preference information.

2. The method according to claim 1, characterized in that The method further comprises: By interfacing with various sensors and monitoring equipment in coal mines, a variety of original disaster monitoring data from multiple monitoring sources can be obtained in real time; Formatting the acquired original disaster monitoring data to obtain real-time disaster monitoring data that complies with unified data standards; the formatting process includes at least one of a data type verification operation, a unit conversion operation, and a data cleaning operation; The real-time disaster monitoring data obtained after the formatting process is stored in a data warehouse, which is a distributed column-based database supporting efficient query and analysis.

3. The method according to claim 2, characterized in that The rendering of the recommended report processing template based on the user's operation in the report customization interface and the real-time disaster monitoring data further includes: Based on the indicator configuration operation performed by the user in the report customization interface, the real-time disaster monitoring data to be processed that matches the indicator configuration operation is obtained from the data warehouse; the indicator configuration operation includes the selection of specific indicators and / or the selection of a data range; Based on the application scenario associated with the recommended report processing template, the real-time disaster monitoring data to be processed is processed accordingly to obtain disaster warning data, and based on the user's basic visualization chart template configuration operation in the report customization interface, the disaster warning data is filled into the basic visualization chart template configured by the user.

4. The method according to claim 1, characterized in that The method further comprises: Based on the historical operation behavior information and the preference information, an intelligent layout algorithm is used to adjust the layout of the recommended report processing template.

5. The method according to claim 1, characterized in that The method further comprises: The layout, content and display method of the recommended report processing template are adjusted according to the personnel information of the user and / or the usage scenario of the coal mine disaster monitoring and early warning system.

6. The method according to any one of claims 1 to 5, characterized in that The method further comprises: A dual-dimensional classification mechanism is adopted to combine a variety of preset basic visualization chart templates according to disaster types and chart forms to establish a visualization chart library; Adopting dynamic parameter binding technology to bind corresponding parameters to each basic visualization chart template, wherein the parameters at least include data fields, chart attributes and display rules; Based on the report application scenario, a basic visualization chart template matching the report application scenario is screened out from the established visualization chart library, and a report visualization template library corresponding to the report application scenario is established based on the screened basic visualization chart templates.

7. The method according to claim 6, characterized in that The method further comprises: Receiving an upgrade instruction of at least one of the visualization chart library and the report visualization template library; Based on the upgrade instruction, at least one of the visualization chart library and the report visualization template library is upgraded.

8. A visual analysis device for coal mine disaster monitoring and early warning data, characterized in that: include: A receiving module, configured to receive instruction information of a user selecting a report visualization template library from at least one report visualization template library; The instruction information includes user information of the user; The at least one report visualization template library corresponds to different report application scenarios, and each report visualization template library is associated with a plurality of basic visualization chart templates; An acquisition module, used for acquiring historical operation behavior information and preference information of the user in the coal mine disaster monitoring and early warning system based on the user information; A prediction module, used to predict the user's future operation behavior information and data items of the disaster warning data of interest based on the historical operation behavior information by using a pre-trained long short-term memory network LSTM model; A generating module, configured to generate a recommended report processing template matching the category of the disaster warning data of interest based on the user's future operation behavior information and the data items of the disaster warning data of interest, in combination with the selected report visualization template library; A rendering module is used to provide a visual report customization interface when the user selects the recommended report processing template, and to render the recommended report processing template based on the user's operations in the report customization interface and real-time disaster monitoring data; wherein the report customization interface displays relevant indicators of the disaster warning data of interest and basic visualization chart templates associated with the relevant indicators, and the basic visualization chart templates associated with the relevant indicators are determined based on the historical operation behavior information and the preference information.

9. A coal mine disaster monitoring and early warning system, comprising the visual analysis device for coal mine disaster monitoring and early warning data as claimed in claim 8.

10. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

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