A data storage management method for aircraft testing

Abstract

This invention discloses a data storage management method for aircraft testing, belonging to the technical field of aircraft testing and data storage management. The method includes database configuration management, database table creation management, database query management, and database monitoring management. Database configuration management includes login configuration and backup configuration; database table creation management includes data frame format initialization, modification, querying, display, exporting, table creation, and table deletion; database query management includes querying, processing, displaying, and exporting; database monitoring information includes the rate of row entry, total number of rows entered, and total space occupied. This invention designs a database table creation method and data storage rules, improving the efficiency of database table creation, reducing the number of tables created, and reducing the workload of maintenance personnel. Simultaneously, it designs data query and data monitoring methods, which are beneficial for multi-dimensional data analysis and use, and allow maintenance personnel to monitor data aggregation in real time.

Description

Technical Field

[0001] This invention belongs to the field of aircraft testing and data storage management technology, and specifically relates to a data storage management method for aircraft testing. Background Technology

[0002] During aircraft flight test missions, all data is aggregated to the data center via the PDXP protocol. Currently, for each test mission, data center operations personnel need to rebuild tables using SQL statements on the database management platform. Different personnel using different table-building methods lead to data storage chaos, hindering subsequent data management and analysis. Operations personnel write different SQL queries for different data analysis needs, requiring strong expertise due to the specialized nature of SQL. Furthermore, the lack of monitoring of stored data during test missions makes it impossible to track the amount of data stored and the data aggregation status for each mission. These factors significantly increase the difficulty and workload of data management during test missions. Therefore, an efficient and convenient data storage management method is needed for aircraft testing.

[0003] The Aircraft Aerodynamic Test Data Management System and Method (CN201810332986.0) proposes managing test data through steps such as feature acquisition, template matching, and variable name mapping. This method extracts effective data from the generated data through data mining before storing it in the database. However, this method is completely unsuitable for aircraft test missions, as aircraft test mission data needs to be stored in real time and is structured data that does not require data mining before database storage. A Rail Vehicle Single-Vehicle Test Data Management System (CN202020661919.6) provides a system that eliminates paper reports, simplifies the single-vehicle test inspection process, and improves operational efficiency. However, this method does not specify methods for storing and retrieving test data, making it unsuitable for data storage management in aircraft testing. A Data Monitoring Management System and Method (CN201310703018.3) is a monitoring management system for on-site monitoring video image data and laboratory experimental status data, which is unsuitable for PDXP data packet management in aircraft testing. In summary, while many patents exist regarding data management, the following issues remain for aircraft testing missions:

[0004] (1) It does not take into account that the data in the aircraft test mission are all data packets generated based on the PDXP protocol.

[0005] (2) No method was proposed for storing the test data in an orderly and efficient manner for each task.

[0006] (3) No method was proposed for simple and effective monitoring of PDXP data collection or for querying PDXP data. Summary of the Invention

[0007] The purpose of this invention is to provide a data storage management method for aircraft testing, which solves the problem of efficiently and conveniently storing, monitoring, and querying all PDXP data packets generated in all aircraft testing tasks in a data center.

[0008] To achieve the above objectives and solve the above technical problems, the present invention provides the following technical solution.

[0009] A data storage management method for aircraft testing includes the following steps:

[0010] S1. Configure the database, including database login configuration and backup configuration;

[0011] S11. Log in to the database and configure the login settings as follows: database IP address, port number, database name, username, and password;

[0012] S12 uses a combination of full backup and incremental backup to upload data to a remote FTP server; the backup configuration includes: backup cycle, FTP server;

[0013] S2. Create database tables.

[0014] Before storing PDXP data packets in the database, create tables in the database first; the specific table creation process is as follows:

[0015] S21. Data frame format initialization;

[0016] Import one or more data frame template files from any file path. Supported file formats are .csv, .xls, and .txt. The data frame template file must have the same fixed format as the initialization frame data format. Generate one or more initialization templates at once based on the imported data frame template files. If no data frame template file is imported or the imported data frame template file is incorrect, the initialization template will have the same format as the initialization frame data.

[0017] The initialization template includes the task name, MID, source name, SID, information category, BID, whether to split into tables, table splitting period, and PDXP frame header format. Fields marked with [] cannot be changed and are identified by []. The data type can be selected as unsigned or signed. Whether to split into tables can be selected as yes or no. The table splitting period can be selected as week, day, or hour. The number of bytes should be filled in as an integer according to the actual situation. The quantization unit should be filled in according to the actual quantization unit. If it is empty, it means no processing.

[0018] S22. Data frame format modification; provides functions for adding, deleting, and modifying fields in imported or generated data frame formats;

[0019] S23. Data frame format query; supports querying by multiple indexes such as MID, SID, and BID. The index value can be one or more of these. To facilitate index query, a list of index values ​​should be provided. The display format is: MID (number)_task name, SID (number)_source name, BID (number)_information category.

[0020] S24. Data frame format export; supports exporting data frame format query results as file templates. Exported file formats include .csv, .xls, and .txt. It also supports setting a template directly as the initialization template.

[0021] S25. Data frame format display; displays the data frame table name, frame field meaning, and frame field length, and allows direct modification of the displayed frame field meaning. When displaying the table name, it includes the information category meaning. Display format: t_MID (number)_BID (number)_information category;

[0022] S26. Data frame format table creation; using MID as the mode, data frames with the same MID value are in the same mode, and each data frame in the same mode creates a data table, with BID as the primary key; the mode name, data frame table name, and data frame table field name adopt a regular and fixed naming method.

[0023] Pattern naming rules: M_MID (number), data frame table naming rules: t_MID (number)_BID (number), table field naming rules: n_starting byte count_number of bytes occupied by this field_data frame name_quantization unit;

[0024] S27. Delete table for data frame format; If a table has already been created in the current task for the queried data frame format, select delete table.

[0025] S3. Perform a database query;

[0026] Query management is used to query historical data stored in the database, process it, and then display and export it.

[0027] Query: Provides query for MID, SID, BID, DATE, and TIME index values; among which DATE and TIME indexes are optional, but MID, SID, and BID indexes must be present in one or more. To facilitate index query, a list of index values ​​must be provided, with the display format being MID (number)_task name, SID (number)_source name, and BID (number)_information category.

[0028] Processing: Before displaying and exporting query results, select to quantify the data. The quantification logic can be obtained from the table field names. At the same time, it can delete the queried table data.

[0029] Display: The query results can be displayed. If the query results are not unique, the first result will be displayed. The number of results to display, ascending / descending order, sorting criteria, and whether to display the frame header can be selected.

[0030] Export: Enables exporting query data, supporting export file formats such as .csv, .xls, and .txt;

[0031] S4. Perform database monitoring;

[0032] Data monitoring is used to grasp the data aggregation status of the data center in real time and take corresponding measures according to the status; data monitoring performs real-time and scheduled monitoring of aggregated data according to tasks; monitoring objects: a certain task, all data tables under a certain task; monitoring information: the rate of row entry, the total number of rows entered, and the total space occupied; at the same time, the monitoring information will be written to the log file in real time, and the monitoring information chart of a certain data table can be selected to visualize the monitoring status of a certain data table.

[0033] Furthermore, the backup cycle in S12 can be selected as monthly, weekly, daily, or immediate.

[0034] Furthermore, the FTP server in S12 includes an IP address, username, and password.

[0035] Furthermore, the S26 field type automatically selects the optimal type based on the number of bytes and the data type.

[0036] The advantages of this invention compared to the prior art are as follows:

[0037] 1. Based on the characteristics of aircraft testing, a database table creation method and data storage rules were designed. A method for creating data tables through template file export and import was proposed, and an initialization template file format was designed, improving the efficiency of database table creation and reducing the workload of maintenance personnel. A method for storing data under the same MID in the same schema was proposed, and schema, table, and field naming rules were designed, reducing the number of tables created, making the data storage process clearer and more direct, and facilitating subsequent processing and use of the stored data.

[0038] 2. A data query method was designed to address the characteristics of aircraft testing. A visualization query method using multiple index values ​​(MID, SID, BID, DATE, TIME) was proposed, along with a method for quantifying, displaying, and exporting data, which facilitates multi-dimensional data analysis.

[0039] 3. A data monitoring method was designed to address the characteristics of aircraft testing. A method for real-time and timed monitoring of collected data based on mission requirements was proposed. The designed monitoring information includes the database row insertion rate, total number of rows stored, and total data storage space, facilitating real-time monitoring of data collection by maintenance personnel. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the database table creation process of this invention;

[0041] Figure 2 This is a diagram illustrating the configuration management interface of the present invention.

[0042] Figure 3 This is a diagram illustrating the interface for table creation and management in this invention.

[0043] Figure 4 This is a screenshot of the query management interface of the present invention;

[0044] Figure 5 This is a diagram of the monitoring and management interface of the present invention. Detailed Implementation

[0045] The present invention will now be explained and described in detail with reference to the accompanying drawings and embodiments.

[0046] The design concept of this invention is explained as follows: In typical aircraft flight test missions, the real-time data transmission protocol uses the PDXP protocol based on UDP. The PDXP protocol consists of a frame header and data fields. The frame header fields consist of version number VER, mission flag MID, source address SID, destination address DID, information flag BID, packet sequence number No, information processing flag FLAG, reserved word Default, transmission date DATE, transmission time TIME, and data length L. The length of the frame header fields is fixed, but the field padding information changes depending on the different test missions and message generators. The length of the data fields is not fixed; both the field length and padding information change depending on the different test missions and message generators. Therefore, each test mission will generate a large amount of diverse PDXP data packets.

[0047] All experimental data generated during the mission will be collected in the data center via the PDXP protocol. The data center must have the following capabilities:

[0048] (1) Data storage function. The data storage function allows all data collected in the data center to be stored in the database and permanently preserved.

[0049] (2) Data query function. The data query function allows maintenance personnel to query any historical data stored, which is convenient for data analysis, export, etc.

[0050] (3) Data monitoring function. The data monitoring function enables operation and maintenance personnel to keep abreast of the data collection status of the data center in real time and take corresponding measures according to the status.

[0051] For all PDXP data packets generated during all aircraft test missions, providing efficient and convenient data storage, monitoring, and query functions in the data center is crucial to the success of the test missions.

[0052] Therefore, the present invention provides a data storage management method for aircraft testing, which specifically includes the following steps:

[0053] S1. Configure the database, including database login and backup configurations; such as... Figure 2 As shown;

[0054] S11. Log in to the database and configure the login settings as follows: database IP address, port number, database name, username, and password;

[0055] S12, the backup design can improve data reliability, adopting a combination of full backup and incremental backup and uploading data to a remote FTP server; the backup configuration includes: backup period (selectable monthly, weekly, daily, immediate backup), FTP server (IP address, username, password).

[0056] S2. Create database tables. Tables must be created in the database before the PDXP data package is stored. Figure 1 As shown;

[0057] S21. Data frame format initialization;

[0058] To facilitate table creation, one or more data frame template files can be imported from any file path. The file formats supported are .csv, .xls, and .txt. The fixed format of the data frame template file must be the same as the format of the initialization frame data, as shown in Table 1. One or more initialization templates can be generated at once based on the imported data frame template file. If no data frame template file is imported or the imported data frame template file is incorrect, the initialization template will be in the format of Table 1, that is, the same as the format of the initialization frame data.

[0059] Table 1 Initialization Frame Format

[0060]

[0061] The initialization template mainly includes the task name, MID, source name, SID, information category, BID, whether to split into tables, table splitting period, and PDXP frame header format. Fields marked with [] cannot be changed and are identified by []. Data type can be unsigned or signed. Whether to split into tables can be filled in as yes or no. Table splitting period can be filled in as week, day, or hour. The number of bytes can be filled in as an integer number according to the actual situation. The quantization unit should be filled in according to the actual quantization unit. If it is empty, it means no processing.

[0062] S22. Data frame format modification; provides functions for adding, deleting, and modifying fields in imported or generated data frame formats;

[0063] S23. Data frame format query; supports querying by multiple indexes such as MID, SID, and BID. The index value can be one or more of these. To facilitate index query, a list of index values ​​should be provided. The display format is: MID (number)_task name, SID (number)_source name, BID (number)_information category.

[0064] S24. Data frame format export; supports exporting data frame format query results as file templates. Exported file formats include .csv, .xls, and .txt. It also supports setting a template directly as the initialization template.

[0065] S25. Data frame format display; displays the data frame table name, frame field meaning, and frame field length, and allows direct modification of the displayed frame field meaning. When displaying the table name, it includes the information category meaning. Display format: t_MID (number)_BID (number)_information category;

[0066] S26. Data frame format table creation; using MID as the mode, data frames with the same MID value belong to the same mode, and each data frame under the same mode creates a data table, with BID as the primary key; the mode name, data frame table name, and data frame table field names adopt a regular and fixed naming convention for ease of operation and maintenance. When creating the table, the field type is automatically selected based on the number of bytes and the data type.

[0067] The schema naming convention is: M_MID (number), the data frame table naming convention is: t_MID (number)_BID (number), and the table field naming convention is: n_starting byte count_byte count of this field_data frame name_quantization unit. This naming convention eliminates the need for the database to create additional information data tables such as MID, source, destination, and quantization unit.

[0068] S27. Delete table for data frame format; If a table has already been created in the current task for the queried data frame format, select delete table.

[0069] S3. Perform a database query;

[0070] Query management is used to query historical data stored in the database, process it, and then display and export it; for example... Figure 4 As shown;

[0071] Query: Provides query for MID, SID, BID, DATE, and TIME index values; among which DATE and TIME indexes are optional, but MID, SID, and BID indexes must be present in one or more. To facilitate index query, a list of index values ​​must be provided, with the display format being MID (number)_task name, SID (number)_source name, and BID (number)_information category.

[0072] Processing: Before displaying and exporting query results, select to quantify the data. The quantification logic can be obtained from the table field names. At the same time, it can delete the queried table data.

[0073] Display: The query results can be displayed. If the query results are not unique, the first result will be displayed. The number of results to display, ascending / descending order, sorting criteria, and whether to display the frame header can be selected.

[0074] Export: Enables exporting query data, supporting export file formats such as .csv, .xls, and .txt.

[0075] S4. Perform database monitoring and management;

[0076] Data monitoring enables operations and maintenance personnel to grasp the real-time status of data aggregation in the data center and take corresponding measures accordingly. Monitoring management performs real-time and scheduled monitoring of aggregated data by task; monitoring objects: a specific task, and all data tables under a defined task; monitoring information: the rate of row entry, the total number of rows entered, and the total space occupied; simultaneously, monitoring information is written to log files in real time, and the monitoring information of a specific data table can be displayed in charts, visualizing the monitoring status of that data table; for example... Figure 5 As shown.

[0077] The above are preferred embodiments of the present invention and are not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the disclosed technical content to create equivalent embodiments. Any simple modifications, equivalent changes, and modifications made according to the technical solution of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A data storage management method for aircraft testing, characterized in that, Includes the following steps: S1. Configure the database, including database login configuration and backup configuration; S11. Log in to the database and configure the login settings as follows: database IP address, port number, database name, username, and password; S12 uses a combination of full backup and incremental backup to upload PDXP data packets to a remote FTP server; the backup configuration includes: backup cycle, FTP server; S2. Create database tables. Before storing PDXP data packets in the database, create tables in the database first; the specific table creation process is as follows: S21. Data frame format initialization; Import one or more data frame template files from any file path. The file format supports .csv, .xls, and .txt. The fixed format of the data frame template file must be the same as the format of the initial data frame template. One or more initialization templates are generated at once based on the imported data frame template file; If no data frame template file is imported or the imported data frame template file is incorrect, the initialization template will be in the same format as the initialization frame data. The initialization template includes the task name, MID, source name, SID, information category, BID, whether to split into tables, table splitting period, and PDXP frame header format. Fields marked with [] cannot be changed and are identified by []. For data type, select either unsigned or signed; for whether to split tables, select yes or no; for the splitting period, select week, day, or hour; for the number of bytes, enter an integer number according to the actual situation; for the quantization unit, enter the actual quantization unit, otherwise no processing will be performed. S22, Data frame format modification; Provides functions for adding, deleting, and modifying fields in imported or generated data frame formats; S23, Data frame format query; Supports multi-index queries by MID, SID, and BID. Index values ​​can be one or more of these. To facilitate index queries, a list of index values ​​must be provided. The display format is: MID_Task Name, SID_Source Name, BID_Information Category. S24. Data frame format export; supports exporting data frame format query results as file templates. Exported file formats include .csv, .xls, and .txt. It also supports setting a template directly as the initialization template. S25. Data frame format display; displays the data frame table name, frame field meaning, and frame field length, and allows direct modification of the displayed frame field meaning. When displaying the table name, it includes the information category meaning. Display format: t_MID_BID_Information Category; S26. Create a table using the data frame format; Using MID as the pattern, data frames with the same MID value are in the same pattern. Each data frame in the same pattern creates a data table with BID as the primary key. The pattern name, data frame table name, and data frame table field name adopt a fixed naming pattern. Pattern naming convention: M_MID, data frame table naming convention: t_MID_BID, table field naming convention: n_starting byte count_byte count of this field_data frame name_quantization unit; S27. Delete table for data frame format; If a table has already been created in the current task for the queried data frame format, select delete table. S3. Perform a database query; Database query management is used to query historical data stored in the database, process it, and then display and export it. Query: Provides query functions for MID, SID, BID, DATE, and TIME index values; The DATE and TIME indexes are optional, but one or more MID, SID, and BID indexes are required. To facilitate index queries, a list of index values ​​must be provided, with the display format being MID_task name, SID_source name, and BID_information category. Processing: Before displaying and exporting query results, select to quantify the data. The quantification logic can be obtained from the table field names. At the same time, it can delete the queried table data. Display: The query results can be displayed. If the query results are not unique, the first result will be displayed. The number of results to display, ascending / descending order, sorting criteria, and whether to display the frame header can be selected. Export: Enables exporting query data, supporting export file formats such as .csv, .xls, and .txt; S4. Perform database monitoring; Database data monitoring is used to monitor the data aggregation status of the data center in real time and take corresponding measures based on the status. Data monitoring performs real-time and scheduled monitoring of aggregated data according to tasks. The monitoring objects of data monitoring are: a specific task and all data tables under a specific task. The monitoring information of data monitoring includes: the rate of row entry, the total number of rows entered, and the total space occupied. At the same time, the data monitoring information will be written to the log file in real time, and the monitoring information chart of a specific data table can be selected to visualize the monitoring status of a specific data table.

2. The data storage management method for aircraft testing according to claim 1, characterized in that, The backup cycle described in S12 can be selected as monthly, weekly, daily, or immediate.

3. The data storage management method for aircraft testing according to claim 1, characterized in that, The FTP server described in S12 includes an IP address, username, and password.

4. The data storage management method for aircraft testing according to claim 1, characterized in that, The field type described in S26 automatically selects the optimal type based on the number of bytes and the data type.

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