Method and system for automatically checking various disaster data of coal mine

Abstract

The invention provides a method and system for automatically checking various disaster data of a coal mine, and the method comprises the steps: obtaining expected checking coal mine disaster data, determining formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected checking coal mine disaster data, and constructing a data model; performing custom rule configuration and scene configuration on the data model based on the check attribute item, and associating the disaster index with a custom rule configuration and scene configuration result to obtain a coal mine disaster data automatic check model; performing model analysis on the accessed disaster data flow based on the coal mine disaster data automatic checking model, determining a corresponding checking rule, and performing data checking on the disaster data flow based on the checking rule; and recording and analyzing the data checking result, generating a checking result and a checking report of the analysis result, and checking and managing the checking report. And the efficiency and the accuracy of automatic checking of the coal mine disaster data are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method and system for automatically checking coal mine multiple disaster data. Background Art

[0002] At present, coal mines face a variety of disasters during production, such as gas explosions, coal dust explosions, roof accidents, water seepage accidents, etc. In order to effectively prevent these disasters, a large amount of disaster-related data needs to be monitored and analyzed; However, the original data verification work not only requires a lot of manual work, but also involves a lot of duplication of work in the data verification of various disasters. The standards and rules are diverse, and the relationship between data and rules is confusing, which is not convenient for unified management, analysis and expansion, thus greatly reducing the verification effect of various disaster data; Therefore, in order to overcome the above-mentioned defects, the present invention provides a method and system for automatically checking various disaster data in coal mines. Summary of the invention

[0003] The present invention provides a method and system for automatically verifying various disaster data in coal mines, which are used to determine the multi-dimensional attributes of the expected verified coal mine disaster data, and determine the formatting parameters of the coal mine disaster data according to the multi-dimensional attributes, so as to realize the effective construction of the data model. Secondly, the data model is customized according to the verification attribute items. The disaster index is associated with the configuration result, so as to realize the effective construction of the automatic verification model of the coal mine disaster data, which provides convenience and guarantee for the automatic verification of the coal mine disaster data. Finally, the connected disaster data stream is parsed and the data is verified through the automatic verification model of the coal mine disaster data, and a corresponding verification report is generated according to the verification result, and the verification report is viewed and managed, so as to ensure the efficiency and accuracy of the automatic verification of the coal mine disaster data. At the same time, the automated processing reduces manual participation, and the customized standardized rules and scenarios can flexibly and efficiently verify the data of different disasters.

[0004] The present invention provides a method for automatically checking coal mine disaster data, comprising: Step 1: Obtain the expected verification coal mine disaster data, and determine the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and build a data model; Step 2: Based on the verification attribute items, the data model is customized with rule configuration and scenario configuration, and the disaster indicators are associated with the customized rule configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data; Step 3: Based on the coal mine disaster data automatic verification model, the model of the connected disaster data stream is analyzed, the corresponding verification rules are determined, and the disaster data stream is verified based on the verification rules; Step 4: Record and analyze the data verification results, generate a verification report of the verification results and analysis results, and review and manage the verification report.

[0005] Preferably, a method for automatically verifying multiple disaster data of coal mines, in step 1, obtaining the expected verification coal mine disaster data, including: Obtaining the system composition of the coal mine, and determining the original disaster data generated during the operation of the coal mine based on the system composition; Obtaining expected verification coal mine disaster data based on original disaster data, and extracting data state representation of the expected verification coal mine disaster data; Based on the data status representation, the preset verified coal mine disaster data is divided into disaster data types, and based on the disaster data type division results, the coal mine disaster knowledge base is accessed to determine the management dimension of each disaster data type; Based on the management dimension, the multi-dimensional attributes of the expected verification coal mine disaster data under each disaster data type are obtained.

[0006] Preferably, a method for automatically verifying multiple coal mine disaster data, step 1: obtaining expected verification coal mine disaster data, and determining formatting parameters for the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and constructing a data model, including: Obtain the multi-dimensional attributes of the expected verification coal mine disaster data and determine the semantic features of each dimensional attribute; At the same time, based on the management terminal, the verification process and verification business of each dimension attribute in the expected verification coal mine disaster data of different categories are obtained, and the differentiated format requirements for each dimension attribute in the expected verification coal mine disaster data of different categories are determined based on semantic features, verification process and verification business; The formatting parameters of the coal mine disaster data are determined based on the differentiated format requirements, and the formatting parameters of different dimensional attributes of different categories of coal mine disaster data are classified and recorded to obtain a data model.

[0007] Preferably, a method for automatically verifying coal mine disaster data of various types, in step 2, customizing rule configuration and scenario configuration of the data model based on the verification attribute items, including: Based on the management terminal, the verification targets of various coal mine disaster data are obtained, and based on the verification targets, the multi-dimensional attributes of the expected coal mine disaster data are divided into groups to obtain the verification attribute items corresponding to each verification target; Determine sample representations of different verification attribute items under each verification target respectively, and determine data types of different verification attribute items based on the sample representations; Based on the coal mine disaster management system, the basic business logic of different verification attribute items is retrieved, and the underlying logic verification focus of different verification attribute items is determined based on the basic business logic. At the same time, the customized verification focus of different verification attribute items is determined based on the management objectives; Determine the verification rules for different verification attribute items based on the data type, and determine the rule content corresponding to the verification rules based on the underlying logic verification focus and custom verification focus points; Nesting the rule content and the verification rule to obtain the target verification rule, and obtaining the available format requirements for the target verification rule based on the nesting result; The target verification rule is converted based on the available format requirements, and the custom rule configuration result is obtained based on the content conversion result, and the data model is converted based on the custom rule configuration result to obtain the corresponding rule model; Acquire pre-application scenarios for the rule model based on the management terminal, and extract scenario restriction factors of the pre-application scenarios; Determine application conditions and requirements of different pre-application scenarios based on scenario constraints, and group rule models based on the application conditions and requirements to obtain a set of rule models corresponding to each pre-application scenario; At the same time, based on the application conditions and requirements of different pre-application scenarios, the adaptive correction parameters of the rule parameters of each rule model in the corresponding rule model set are determined, and the rule parameters of each rule model are adaptively adjusted based on the adaptive correction parameters to complete the scenario configuration of the rule model.

[0008] Preferably, a method for automatically checking various disaster data in a coal mine, in step 2, the disaster indicator is associated with the custom rule configuration and the scenario configuration result to obtain an automatic verification model for the coal mine disaster data, including: Obtain disaster indicators and receive scene association instructions for disaster indicators submitted by management users based on the configuration page; Determine the correlation between disaster indicators and scenario configuration results based on scenario correlation instructions, and generate a drainage reference table for disaster data based on the correlation; Based on the diversion reference table, the routing adaptation of the data stream interface is performed on the custom rule configuration and scenario configuration results, and an automatic verification model for coal mine disaster data is obtained based on the routing adaptation results.

[0009] Preferably, a method for automatically verifying multiple disaster data in a coal mine, in step 3, based on the automatic verification model of coal mine disaster data, a model analysis is performed on the connected disaster data stream, a corresponding verification rule is determined, and data verification is performed on the disaster data stream based on the verification rule, including: Obtain the disaster data stream, and input the disaster data stream into the coal mine disaster data automatic verification model for model analysis to obtain the specific verification rules corresponding to the disaster data stream; Based on the attribute restriction requirements of the specific verification rules, the disaster data stream is divided into data groups to be verified. At the same time, the verification dimensions of the specific verification rules are extracted, and the specific verification rules are mapped and matched with the data groups to be verified based on the verification dimensions; Based on the mapping and matching results, the full verification process corresponding to the specific verification rules is retrieved to perform automatic data verification on the data group to be verified under the corresponding verification dimension.

[0010] Preferably, a method for automatically verifying data of various disasters in coal mines, in step 4, the data verification results are recorded and analyzed, and a verification report of the verification results and analysis results is generated, including: Obtain the data verification results of coal mine disaster data and record the data verification results; Based on the record results, the data verification results are divided into a verification pass set and a verification fail set, and the source data of the verification fail set is traced to obtain the corresponding original coal mine disaster data and the reasons for the verification failure; The original coal mine disaster data and reasons for failure to pass the verification corresponding to the set that failed to pass the verification are configured as a drill-down data viewing list; At the same time, a comparison chart of the passed and failed verification sets is generated based on the verification time, and the drill-down data viewing list is associated and bound with the corresponding failed verification set in the comparison chart; Generate a verification report of the verification results and analysis results based on the association binding results.

[0011] Preferably, in a method for automatically verifying coal mine multiple disaster data, in step 4, the verification report is reviewed and managed, including: Obtain the verification report and determine the viewing method of the verification report, wherein the viewing method includes previewing, downloading and printing; Perform background management parameter configuration for the verification report based on the viewing mode, and enable multi-channel viewing permissions for the verification report based on the background management parameter configuration; The verification report is validated based on multi-channel viewing permissions, completing the viewing management of the verification report.

[0012] The present invention provides a system for automatically checking various disaster data in coal mines, comprising: A data model building module is used to obtain the expected verification coal mine disaster data, determine the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and build a data model; A verification model building module is used to perform custom rule configuration and scenario configuration on the data model based on the verification attribute items, and associate the disaster indicators with the custom rule configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data; The data verification module is used to perform model analysis on the connected disaster data stream based on the automatic verification model of coal mine disaster data, determine the corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules; The verification report management module is used to record and analyze data verification results, generate verification reports of verification results and analysis results, and view and manage verification reports.

[0013] Preferably, a system for automatically checking coal mine disaster data, a data model building module, includes: A data acquisition unit, used to acquire the system configuration of the coal mine, and determine the original disaster data generated during the operation of the coal mine based on the system configuration; An attribute determination unit for: Obtaining expected verification coal mine disaster data based on original disaster data, and extracting data state representation of the expected verification coal mine disaster data; Based on the data status representation, the preset verified coal mine disaster data is divided into disaster data types, and based on the disaster data type division results, the coal mine disaster knowledge base is accessed to determine the management dimension of each disaster data type; Based on the management dimension, the multi-dimensional attributes of the expected verification coal mine disaster data under each disaster data type are obtained.

[0014] Compared with the prior art, the present invention has the following beneficial effects: By determining the multi-dimensional attributes of the expected verification of coal mine disaster data, and determining the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes, the data model can be effectively constructed. Secondly, the data model is customized according to the verification attribute items. The disaster indicators are associated with the configuration results to achieve the effective construction of the automatic verification model for coal mine disaster data, which provides convenience and guarantee for the automatic verification of coal mine disaster data. Finally, the automatic verification model for coal mine disaster data is used to parse and verify the connected disaster data stream, generate a corresponding verification report based on the verification results, and view and manage the verification report, ensuring the efficiency and accuracy of the automatic verification of coal mine disaster data. At the same time, automated processing reduces manual participation, and customized standardized rules and scenarios can flexibly and efficiently verify data for different disasters.

[0015] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0016] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a flow chart of a method for automatically checking multiple disaster data in a coal mine according to an embodiment of the present invention; Figure 2 A schematic diagram of constructing a data model for gas data in a method for automatically checking data on multiple disasters in a coal mine in an embodiment of the present invention; Figure 3 This is an example diagram of a custom rule configuration in a method for automatically checking data on multiple disasters in a coal mine in an embodiment of the present invention; Figure 4 This is an example diagram of data verification in a method for automatically verifying data on multiple disasters in a coal mine in an embodiment of the present invention; Figure 5 A comparison diagram of a set of data that passed the verification and a set of data that failed the verification in a method for automatically verifying multiple disaster data in a coal mine according to an embodiment of the present invention; Figure 6 This is a structural diagram of a system for automatically checking data on various disasters in coal mines in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0019] Embodiment 1: This embodiment provides a method for automatically checking various disaster data in coal mines. Figure 1 As shown, including: Step 1: Obtain the expected verification coal mine disaster data, and determine the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and build a data model; Step 2: Based on the verification attribute items, the data model is customized with rule configuration and scenario configuration, and the disaster indicators are associated with the customized rule configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data; Step 3: Based on the coal mine disaster data automatic verification model, the model of the connected disaster data stream is analyzed, the corresponding verification rules are determined, and the disaster data stream is verified based on the verification rules; Step 4: Record and analyze the data verification results, generate a verification report of the verification results and analysis results, and review and manage the verification report.

[0020] In this embodiment, the coal mine disaster data to be verified refers to the coal mine disaster data that needs to be managed through data verification.

[0021] In this embodiment, the multi-dimensional attributes refer to different attributes included in the coal mine disaster data to be verified, such as time, gas concentration, disaster data type, and other attributes.

[0022] In this embodiment, the formatting parameter refers to a method or measure for formatting coal mine disaster data with different multi-dimensional attributes.

[0023] In this embodiment, the data model refers to the result obtained after formatting and limiting the coal mine disaster data with multi-dimensional attributes, and is used to represent the specific formatting steps or standards for the coal mine disaster data.

[0024] In this embodiment, the verification attribute item refers to a data item that needs to be verified.

[0025] In this embodiment, the custom rule configuration and scenario configuration refer to the configuration of verification rules and application scenarios for the data model, thereby facilitating corresponding verification operations on various disaster data through the configured rules and scenarios.

[0026] In this embodiment, the disaster index is used to characterize the type of disaster data applicable to different verification rules and scenarios, that is, the type of disaster data that can be processed.

[0027] In this embodiment, the coal mine disaster data automatic verification model refers to a tool that is finally obtained and can perform coal mine disaster data verification.

[0028] The working principle and beneficial effects of the above technical solution are: by determining the multi-dimensional attributes of the expected verification of coal mine disaster data, and determining the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes, the data model is effectively constructed; secondly, the data model is customized according to the verification attribute items. Rules and scenarios are configured, and the disaster indicators are associated with the configuration results to achieve effective construction of the automatic verification model for coal mine disaster data, which provides convenience and guarantee for the automatic verification of coal mine disaster data; finally, the automatic verification model for coal mine disaster data is used to parse and verify the connected disaster data stream, and a corresponding verification report is generated according to the verification results, and the verification report is reviewed and managed, ensuring the efficiency and accuracy of the automatic verification of coal mine disaster data. At the same time, automated processing reduces manual participation, and customized standardized rules and scenarios can flexibly and efficiently verify data for different disasters.

[0029] Embodiment 2: Based on Example 1, this example provides a method for automatically verifying various disaster data in coal mines. In step 1, obtaining the expected verification coal mine disaster data includes: Obtaining the system composition of the coal mine, and determining the original disaster data generated during the operation of the coal mine based on the system composition; Obtaining expected verification coal mine disaster data based on original disaster data, and extracting data state representation of the expected verification coal mine disaster data; Based on the data status representation, the preset verified coal mine disaster data is divided into disaster data types, and based on the disaster data type division results, the coal mine disaster knowledge base is accessed to determine the management dimension of each disaster data type; Based on the management dimension, the multi-dimensional attributes of the expected verification coal mine disaster data under each disaster data type are obtained.

[0030] In this embodiment, the system composition refers to the components of the coal mine, so as to facilitate the determination of the data types generated by the coal mine system during operation.

[0031] In this embodiment, the original disaster data refers to specific disaster data generated during the production or operation of the coal mine determined according to the system configuration.

[0032] In this embodiment, the data status representation refers to the characteristics or phenomena presented by the expected verification coal mine disaster data, including data value characteristics and structural conditions.

[0033] In this embodiment, the coal mine disaster knowledge base is constructed in advance and is used to store the management dimension of each disaster data type, wherein the management dimension refers to the management aspect of each disaster data type, including data compliance and legality.

[0034] The working principle and beneficial effects of the above technical scheme are: by determining the system structure of the coal mine, the original disaster data generated during the operation of the coal mine can be determined through the system structure, and then the expected verification coal mine disaster data can be locked; secondly, the data state representation of the expected verification coal mine disaster data can be determined, and the disaster data type can be divided according to the data state representation and the management dimension of each disaster data type can be determined; finally, the multi-dimensional attributes of the expected verification coal mine disaster data under each disaster data type can be obtained according to the management dimension, which provides convenience for the automatic verification of coal mine disaster data.

[0035] Embodiment 3: Based on Example 1, this example provides a method for automatically checking various disaster data in coal mines, such as Figure 2 As shown, step 1: obtain the expected verification coal mine disaster data, and determine the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and build a data model, including: Obtain the multi-dimensional attributes of the expected verification coal mine disaster data and determine the semantic features of each dimensional attribute; At the same time, based on the management terminal, the verification process and verification business of each dimension attribute in the expected verification coal mine disaster data of different categories are obtained, and the differentiated format requirements for each dimension attribute in the expected verification coal mine disaster data of different categories are determined based on semantic features, verification process and verification business; The formatting parameters of the coal mine disaster data are determined based on the differentiated format requirements, and the formatting parameters of different dimensional attributes of different categories of coal mine disaster data are classified and recorded to obtain a data model.

[0036] In this embodiment, for example, an abstract model is established for gas disaster data: 140XXXXXX771;XX coal mine;2024-08-20 14:14:13~14060201277101MN0043586;laser methane;XX methane T2;0.00; 2024-08-20 14:13:49~After formatting, it is: 1.mineCode;mineName;dataTime; 2. SensorCode; sensorType; sensorName; sensorValue; sensorTime The data model construction diagram of gas data is as follows Figure 2 shown.

[0037] In this embodiment, the semantic feature refers to the core content corresponding to each dimensional attribute or the information content corresponding to each dimensional attribute.

[0038] In this embodiment, the differentiated format requirements refer to different formatting requirements corresponding to different dimensional attributes, that is, different dimensional attributes correspond to different format requirements.

[0039] The working principle and beneficial effects of the above technical solution are: by parsing the multi-dimensional attributes of the expected verification coal mine disaster data, the semantic features, verification process and verification business corresponding to each dimensional attribute are locked, and then the differentiated format requirements for each dimensional attribute in the expected verification coal mine disaster data are determined according to the semantic features, verification process and verification business. Finally, the formatting parameters of the coal mine disaster data are locked according to the differentiated format requirements, and finally the data model is accurately and effectively constructed, which provides convenience and guarantee for the automatic verification of various coal mine disaster data.

[0040] Embodiment 4: Based on Example 1, this example provides a method for automatically checking various disaster data in coal mines, such as Figure 3 As shown, in step 2, the data model is customized with rule configuration and scenario configuration based on the verification attribute items, including: Based on the management terminal, the verification targets of various coal mine disaster data are obtained, and based on the verification targets, the multi-dimensional attributes of the expected coal mine disaster data are divided into groups to obtain the verification attribute items corresponding to each verification target; Determine sample representations of different verification attribute items under each verification target respectively, and determine data types of different verification attribute items based on the sample representations; Based on the coal mine disaster management system, the basic business logic of different verification attribute items is retrieved, and the underlying logic verification focus of different verification attribute items is determined based on the basic business logic. At the same time, the customized verification focus of different verification attribute items is determined based on the management objectives; Determine the verification rules for different verification attribute items based on the data type, and determine the rule content corresponding to the verification rules based on the underlying logic verification focus and customized verification focus points; Nesting the rule content and the verification rule to obtain the target verification rule, and obtaining the available format requirements for the target verification rule based on the nesting result; The target verification rule is converted based on the available format requirements, and the custom rule configuration result is obtained based on the content conversion result, and the data model is converted based on the custom rule configuration result to obtain the corresponding rule model; Acquire pre-application scenarios for the rule model based on the management terminal, and extract scenario restriction factors of the pre-application scenarios; Determine application conditions and requirements of different pre-application scenarios based on scenario constraints, and group rule models based on the application conditions and requirements to obtain a set of rule models corresponding to each pre-application scenario; At the same time, based on the application conditions and requirements of different pre-application scenarios, the adaptive correction parameters of the rule parameters of each rule model in the corresponding rule model set are determined, and the rule parameters of each rule model are adaptively adjusted based on the adaptive correction parameters to complete the scenario configuration of the rule model.

[0041] In this embodiment, a custom rule is configured for the attribute items that need to be checked, for example, by setting basic data values, regular expressions or custom function rules for the attributes in the model to convert the data model into a specific rule model. If no rule is set, it means there is no rule. For example, setting the "^\\d{9}$" regular rule for mineCode in the data model requires the data content to be 9 characters long; setting the "beforeTime(dataTime)" function rule for sensorTime in the data model requires the sensorTime time to be before the dataTime time. The following is an example of custom rule configuration: Figure 3 shown.

[0042] In this embodiment, the verification target refers to the object of verification when verifying the coal mine disaster data and the verification purpose that needs to be achieved during the verification.

[0043] In this embodiment, group division refers to dividing the multi-dimensional attributes according to the verification target, that is, one verification target may correspond to one dimensional attribute or multiple dimensional attributes.

[0044] In this embodiment, the sample representation refers to the specific value and structure of the data items of different verification attribute items.

[0045] In this embodiment, the coal mine disaster management system is constructed in advance and is used to record the business logic corresponding to different verification attribute items during operation.

[0046] In this embodiment, the bottom-level logic verification emphasis refers to the corresponding business logic verification emphasis when verifying different verification attribute items.

[0047] In this embodiment, the management objectives are known in advance.

[0048] In this embodiment, the custom verification focus refers to the points that require additional verification of different verification attribute items in addition to the underlying logic verification focus determined according to the basic business logic, and can be added, deleted and adjusted.

[0049] In this embodiment, the verification rule refers to the specific requirements corresponding to the verification of different verification attribute items, for example, it may be the verification of values.

[0050] In this embodiment, the rule content refers to the specific content corresponding to the verification rule. For example, when the verification rule is a numerical verification, the rule content is a specific numerical requirement, and when the verification rule is a custom function, the rule content is a specific function expression, etc.

[0051] In this embodiment, the target verification rule refers to the result obtained by binding the determined verification rule and the rule content, that is, the rule that can be finally applied.

[0052] In this embodiment, the available format requirement refers to the format that can be used when the target verification rule is deployed.

[0053] In this embodiment, the rule model refers to the result obtained by processing the data model according to the obtained custom rule configuration result, that is, the specific content under the data model is converted by the verification rule.

[0054] In this embodiment, the pre-application scenario refers to a specific scenario or business in which the rule model can be used.

[0055] In this embodiment, the scenario restriction factor refers to the requirements of different pre-application scenarios on the runtime of the rule model when working, that is, the characteristics of different pre-application scenarios when running.

[0056] In this embodiment, the rule model set refers to all rule models corresponding to different pre-application scenarios.

[0057] In this embodiment, the rule parameters refer to specific requirements and parameters corresponding to the verification rules included in each rule model.

[0058] The working principle and beneficial effects of the above technical scheme are: by determining the verification targets for various coal mine disaster data, the verification attribute items are determined according to the verification targets, and then the underlying logical verification focus and custom verification concerns of different verification attribute items are locked; secondly, the verification rules and rule contents for different verification attribute items are determined according to the data type, underlying logical verification focus and custom verification concerns, so as to effectively formulate the target verification rules, and convert the obtained target verification rules into content writing, so as to effectively obtain the custom rule configuration results; finally, the data model is converted through the custom rule configuration results to obtain the corresponding rule model, and the rule model is configured for the scenario, ensuring that different scenarios correspond to different rule models, thereby improving the automatic verification efficiency and verification accuracy of coal mine disaster data in different scenarios.

[0059] Embodiment 5: Based on Example 1, this example provides a method for automatically checking various disaster data in coal mines. In step 2, the disaster indicators are associated with the custom rule configuration and the scenario configuration results to obtain an automatic verification model for coal mine disaster data, including: Obtain disaster indicators and receive scene association instructions for disaster indicators submitted by management users based on the configuration page; Determine the correlation between disaster indicators and scenario configuration results based on scenario correlation instructions, and generate a drainage reference table for disaster data based on the correlation; Based on the diversion reference table, the routing adaptation of the data stream interface is performed on the custom rule configuration and scenario configuration results, and an automatic verification model for coal mine disaster data is obtained based on the routing adaptation results.

[0060] In this embodiment, the configuration page is an interactive interface for online configuration, which can submit configuration requirements.

[0061] In this embodiment, the scenario association instruction refers to the scenarios that need to correspond to different disaster indicators submitted through the configuration page.

[0062] In this embodiment, the diversion reference table is generated based on the association between the disaster indicators and the scenario configuration results, and is used to guide different disaster data to flow into the corresponding rule model.

[0063] The working principle and beneficial effects of the above technical solution are: obtaining the user's economic and production association instructions for different disaster indicators through the configuration page, determining the association between the disaster indicators and the scene configuration results according to the scene association instructions, and then generating a drainage reference table for disaster data according to the association relationship. Finally, the routing adaptation of the data flow interface is performed on the custom rule configuration and the scene configuration results through the drainage reference table, thereby realizing the accurate and effective construction of the automatic verification model for coal mine disaster data, which provides great convenience and guarantee for the automatic verification of various disaster data in coal mines.

[0064] Embodiment 6: Based on Example 1, this example provides a method for automatically checking various disaster data in coal mines, such as Figure 4 As shown, in step 3, based on the coal mine disaster data automatic verification model, the model of the connected disaster data stream is analyzed, the corresponding verification rules are determined, and the disaster data stream is verified based on the verification rules, including: Obtain the disaster data stream, and input the disaster data stream into the coal mine disaster data automatic verification model for model analysis to obtain the specific verification rules corresponding to the disaster data stream; Based on the attribute restriction requirements of the specific verification rules, the disaster data stream is divided into data groups to be verified. At the same time, the verification dimensions of the specific verification rules are extracted, and the specific verification rules are mapped and matched with the data groups to be verified based on the verification dimensions; Based on the mapping and matching results, the full verification process corresponding to the specific verification rules is retrieved to perform automatic data verification on the data group to be verified under the corresponding verification dimension.

[0065] In this embodiment, the data verification example is shown in FIG. Figure 4 shown.

[0066] In this embodiment, the specific verification rule refers to the data verification rule applicable to the current disaster data flow.

[0067] In this embodiment, the attribute limitation requirement refers to the verification process and conditions corresponding to the specific verification rules.

[0068] In this embodiment, the verification dimension refers to the aspect of data that needs to be verified by the specific verification rule, that is, the specific requirement that needs to be verified.

[0069] The working principle and beneficial effects of the above technical solution are: by inputting the disaster data stream into the coal mine disaster data automatic verification model for model analysis, the specific verification rules corresponding to the disaster data stream are accurately and effectively locked. Secondly, the obtained specific verification rules are analyzed to divide the disaster data stream into data groups to be verified according to the specific verification rules, and then the verification dimensions of the specific verification rules are used to automatically verify the data groups to be verified under the corresponding verification dimensions, thereby improving the efficiency and accuracy of data verification.

[0070] Embodiment 7: Based on Example 1, this example provides a method for automatically checking various disaster data in coal mines, such as Figure 5 As shown, in step 4, the data verification results are recorded and analyzed, and a verification report of the verification results and analysis results is generated, including: Obtain the data verification results of coal mine disaster data and record the data verification results; Based on the record results, the data verification results are divided into a verification pass set and a verification fail set, and the source data of the verification fail set is traced to obtain the corresponding original coal mine disaster data and the reasons for the verification failure; The original coal mine disaster data and reasons for failure to pass the verification corresponding to the set that failed to pass the verification are configured as a drill-down data viewing list; At the same time, a comparison chart of the passed and failed verification sets is generated based on the verification time, and the drill-down data viewing list is associated and bound with the corresponding failed verification set in the comparison chart; Generate a verification report of the verification results and analysis results based on the association binding results.

[0071] In this embodiment, the comparison diagram of the set that passed the verification and the set that failed the verification is as follows: Figure 5 shown.

[0072] In this embodiment, the verification report includes basic verification information (verification date, verification object, verification scope, verification purpose), verification method (rule parsing, data type judgment, regular expression judgment, function method judgment), verification results (overall success and failure ratio, detailed results), and improvement suggestions.

[0073] In this embodiment, source data tracing refers to searching for the original data of the data that has not passed the set verification.

[0074] In this embodiment, drilling down the data viewing list refers to setting the original coal mine disaster data and the reasons for failure of verification as a detailed list, and the user can view the corresponding specific information by clicking when the user needs to view it.

[0075] The working principle and beneficial effects of the above technical solution are: by recording the data verification results of coal mine disaster data and splitting the recorded verification results, the verification passed set and the verification failed set can be effectively determined. Secondly, the source data of the verification failed set is traced to determine the original coal mine disaster data and the reasons for the verification failure, and a drill-down data viewing list is generated. Finally, a comparison chart of the verification passed set and the verification failed set is generated, and the drill-down data viewing list is associated and bound with the corresponding verification failed set in the comparison chart, so that users can comprehensively and effectively view the verification status of the coal mine disaster data.

[0076] Embodiment 8: Based on Example 1, this example provides a method for automatically verifying multiple disaster data in a coal mine. In step 4, the verification report is viewed and managed, including: Obtain the verification report and determine the viewing method of the verification report, wherein the viewing method includes previewing, downloading and printing; Perform background management parameter configuration for the verification report based on the viewing mode, and enable multi-channel viewing permissions for the verification report based on the background management parameter configuration; The verification report is validated based on multi-channel viewing permissions, completing the viewing management of the verification report.

[0077] In this embodiment, the multi-channel viewing authority refers to the configuration of the authority of the verification report, that is, different user identities correspond to different viewing authorities.

[0078] The working principle and beneficial effects of the above technical solution are: by managing the viewing method of the verification report and configuring permissions, the reliability of viewing and management of the verification report is ensured, and the security and reliability of the data are ensured.

[0079] Embodiment 9: This embodiment provides a system for automatically checking various disaster data in coal mines, such as Figure 6 As shown, including: A data model building module is used to obtain the expected verification coal mine disaster data, determine the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and build a data model; A verification model building module is used to perform custom rule configuration and scenario configuration on the data model based on the verification attribute items, and associate the disaster indicators with the custom rule configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data; The data verification module is used to perform model analysis on the connected disaster data stream based on the automatic verification model of coal mine disaster data, determine the corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules; The verification report management module is used to record and analyze data verification results, generate verification reports of verification results and analysis results, and view and manage verification reports.

[0080] The working principle and beneficial effects of the above technical solution are: by determining the multi-dimensional attributes of the expected verification of coal mine disaster data, and determining the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes, the data model is effectively constructed; secondly, the data model is customized according to the verification attribute items. Rules and scenarios are configured, and the disaster indicators are associated with the configuration results to achieve effective construction of the automatic verification model for coal mine disaster data, which provides convenience and guarantee for the automatic verification of coal mine disaster data; finally, the automatic verification model for coal mine disaster data is used to parse and verify the connected disaster data stream, and a corresponding verification report is generated according to the verification results, and the verification report is reviewed and managed, ensuring the efficiency and accuracy of the automatic verification of coal mine disaster data. At the same time, automated processing reduces manual participation, and customized standardized rules and scenarios can flexibly and efficiently verify data for different disasters.

[0081] Embodiment 10: Based on Example 9, this example provides a system for automatically checking coal mine disaster data, and a data model building module, including: A data acquisition unit, used to acquire the system configuration of the coal mine, and determine the original disaster data generated during the operation of the coal mine based on the system configuration; An attribute determination unit for: Obtaining expected verification coal mine disaster data based on original disaster data, and extracting data state representation of the expected verification coal mine disaster data; Based on the data status representation, the preset verified coal mine disaster data is divided into disaster data types, and based on the disaster data type division results, the coal mine disaster knowledge base is accessed to determine the management dimension of each disaster data type; Based on the management dimension, the multi-dimensional attributes of the expected verification coal mine disaster data under each disaster data type are obtained.

[0082] The working principle and beneficial effects of the above technical scheme are: by determining the system structure of the coal mine, the original disaster data generated during the operation of the coal mine can be determined through the system structure, and then the expected verification coal mine disaster data can be locked; secondly, the data state representation of the expected verification coal mine disaster data can be determined, and the disaster data type can be divided according to the data state representation and the management dimension of each disaster data type can be determined; finally, the multi-dimensional attributes of the expected verification coal mine disaster data under each disaster data type can be obtained according to the management dimension, which provides convenience for the automatic verification of coal mine disaster data.

[0083] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for automatically checking coal mine disaster data, characterized in that: include: Step 1: Obtain the expected verification coal mine disaster data, and determine the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and build a data model; Step 2: Based on the verification attribute items, the data model is customized with rule configuration and scenario configuration, and the disaster indicators are associated with the customized rule configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data; Step 3: Based on the coal mine disaster data automatic verification model, the model of the connected disaster data stream is analyzed, the corresponding verification rules are determined, and the disaster data stream is verified based on the verification rules; Step 4: Record and analyze the data verification results, generate a verification report of the verification results and analysis results, and review and manage the verification report.

2. The method for automatically checking coal mine disaster data according to claim 1, characterized in that: In step 1, the expected verification coal mine disaster data is obtained, including: Obtaining the system composition of the coal mine, and determining the original disaster data generated during the operation of the coal mine based on the system composition; Obtaining expected verification coal mine disaster data based on original disaster data, and extracting data state representation of the expected verification coal mine disaster data; Based on the data status representation, the preset verified coal mine disaster data is divided into disaster data types, and based on the disaster data type division results, the coal mine disaster knowledge base is accessed to determine the management dimension of each disaster data type; Based on the management dimension, the multi-dimensional attributes of the expected verification coal mine disaster data under each disaster data type are obtained.

3. The method for automatically checking coal mine disaster data according to claim 1, characterized in that: Step 1: Obtain the expected verification coal mine disaster data, and determine the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and build a data model, including: Obtain the multi-dimensional attributes of the expected verification coal mine disaster data and determine the semantic features of each dimensional attribute; At the same time, based on the management terminal, the verification process and verification business of each dimension attribute in the expected verification coal mine disaster data of different categories are obtained, and the differentiated format requirements for each dimension attribute in the expected verification coal mine disaster data of different categories are determined based on semantic features, verification process and verification business; The formatting parameters of the coal mine disaster data are determined based on the differentiated format requirements, and the formatting parameters of different dimensional attributes of different categories of coal mine disaster data are classified and recorded to obtain a data model.

4. The method for automatically checking coal mine disaster data according to claim 1, characterized in that: In step 2, the data model is customized with rule configuration and scenario configuration based on the verification attribute items, including: Based on the management terminal, the verification targets of various coal mine disaster data are obtained, and based on the verification targets, the multi-dimensional attributes of the expected coal mine disaster data are divided into groups to obtain the verification attribute items corresponding to each verification target; Determine sample representations of different verification attribute items under each verification target respectively, and determine data types of different verification attribute items based on the sample representations; Based on the coal mine disaster management system, the basic business logic of different verification attribute items is retrieved, and the underlying logic verification focus of different verification attribute items is determined based on the basic business logic. At the same time, the customized verification focus of different verification attribute items is determined based on the management objectives; Determine the verification rules for different verification attribute items based on the data type, and determine the rule content corresponding to the verification rules based on the underlying logic verification focus and custom verification focus points; Nesting the rule content and the verification rule to obtain the target verification rule, and obtaining the available format requirements for the target verification rule based on the nesting result; The target verification rule is converted based on the available format requirements, and the custom rule configuration result is obtained based on the content conversion result, and the data model is converted based on the custom rule configuration result to obtain the corresponding rule model; Acquire pre-application scenarios for the rule model based on the management terminal, and extract scenario restriction factors of the pre-application scenarios; Determine application conditions and requirements of different pre-application scenarios based on scenario constraints, and group rule models based on the application conditions and requirements to obtain a set of rule models corresponding to each pre-application scenario; At the same time, based on the application conditions and requirements of different pre-application scenarios, the adaptive correction parameters of the rule parameters of each rule model in the corresponding rule model set are determined, and the rule parameters of each rule model are adaptively adjusted based on the adaptive correction parameters to complete the scenario configuration of the rule model.

5. The method for automatically checking coal mine disaster data according to claim 1, characterized in that: In step 2, the disaster indicators are associated with the custom rule configuration and scenario configuration results to obtain the automatic verification model of coal mine disaster data, including: Obtain disaster indicators and receive scene association instructions for disaster indicators submitted by management users based on the configuration page; Determine the correlation between disaster indicators and scenario configuration results based on scenario correlation instructions, and generate a drainage reference table for disaster data based on the correlation; Based on the diversion reference table, the routing adaptation of the data stream interface is performed on the custom rule configuration and scenario configuration results, and an automatic verification model for coal mine disaster data is obtained based on the routing adaptation results.

6. The method for automatically checking coal mine disaster data according to claim 1, characterized in that: In step 3, the model of the disaster data stream connected is analyzed based on the automatic verification model of coal mine disaster data, the corresponding verification rules are determined, and the disaster data stream is verified based on the verification rules, including: Obtain the disaster data stream, and input the disaster data stream into the coal mine disaster data automatic verification model for model analysis to obtain the specific verification rules corresponding to the disaster data stream; Based on the attribute restriction requirements of the specific verification rules, the disaster data stream is divided into data groups to be verified. At the same time, the verification dimensions of the specific verification rules are extracted, and the specific verification rules are mapped and matched with the data groups to be verified based on the verification dimensions; Based on the mapping and matching results, the full verification process corresponding to the specific verification rules is retrieved to perform automatic data verification on the data group to be verified under the corresponding verification dimension.

7. The method for automatically checking coal mine disaster data according to claim 1, characterized in that: In step 4, the data verification results are recorded and analyzed, and a verification report of the verification results and analysis results is generated, including: Obtain the data verification results of coal mine disaster data and record the data verification results; Based on the record results, the data verification results are divided into a verification pass set and a verification fail set, and the source data of the verification fail set is traced to obtain the corresponding original coal mine disaster data and the reasons for the verification failure; The original coal mine disaster data and reasons for failure to pass the verification corresponding to the set that failed to pass the verification are configured as a drill-down data viewing list; At the same time, a comparison chart of the passed and failed verification sets is generated based on the verification time, and the drill-down data viewing list is associated and bound with the corresponding failed verification set in the comparison chart; Generate a verification report of the verification results and analysis results based on the association binding results.

8. The method for automatically checking coal mine disaster data according to claim 1, characterized in that: In step 4, the verification report is reviewed and managed, including: Obtain the verification report and determine the viewing method of the verification report, wherein the viewing method includes previewing, downloading and printing; Perform background management parameter configuration for the verification report based on the viewing mode, and enable multi-channel viewing permissions for the verification report based on the background management parameter configuration; The verification report is validated based on multi-channel viewing permissions, completing the viewing management of the verification report.

9. A system for automatically checking various disaster data in coal mines, characterized in that: include: A data model building module is used to obtain the expected verification coal mine disaster data, determine the formatting parameters of the coal mine disaster data based on the multi-dimensional attributes of the expected verification coal mine disaster data, and build a data model; A verification model building module is used to perform custom rule configuration and scenario configuration on the data model based on the verification attribute items, and associate the disaster indicators with the custom rule configuration and scenario configuration results to obtain an automatic verification model for coal mine disaster data; The data verification module is used to perform model analysis on the connected disaster data stream based on the automatic verification model of coal mine disaster data, determine the corresponding verification rules, and perform data verification on the disaster data stream based on the verification rules; The verification report management module is used to record and analyze data verification results, generate verification reports of verification results and analysis results, and view and manage verification reports.

10. A system for automatically checking coal mine disaster data according to claim 9, characterized in that: Data model building blocks, including: A data acquisition unit, used to acquire the system configuration of the coal mine, and determine the original disaster data generated during the operation of the coal mine based on the system configuration; An attribute determination unit for: Obtaining expected verification coal mine disaster data based on original disaster data, and extracting data state representation of the expected verification coal mine disaster data; Based on the data status representation, the preset verified coal mine disaster data is divided into disaster data types, and based on the disaster data type division results, the coal mine disaster knowledge base is accessed to determine the management dimension of each disaster data type; Based on the management dimension, the multi-dimensional attributes of the expected verification coal mine disaster data under each disaster data type are obtained.

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