A test report multi-source data automatic gathering and interpretation generation method and system

Abstract

The present application relates to a kind of test report multi-source data automatic gathering and interpretation generation method and system, belong to test data report automatic generation and interpretation technical field.By configuring multiple types of data sources and defining the label mapping relationship of report field and actual data source;According to steady-state / non-steady-state condition, define steady-state formula and non-steady-state formula;According to machine type and test type, report template is organized into tree structure;After test, data is automatically collected and gathered and structured according to template field archive;According to test task and machine type, automatically match and load template;According to label mapping, locate data, call steady-state or non-steady-state formula interpretation calculation according to working condition;The result is filled into template to generate test report.The present application solves the technical problems of existing technology, such as dispersed data source, interpretation relies on manual, field and data source coupling, template needs manual matching, report generation and data collection is split, realizes the automatic, standardization generation of test report.

Description

Technical Field

[0001] This invention relates to the field of automatic generation and interpretation of test data reports, specifically to a method and system for automatic aggregation and interpretation of multi-source data in test reports. Background Technology

[0002] The digital management platform for the entire process of aero-engine testing (running) divides the entire testing process into collaborative subsystems, including a management subsystem, a program configuration subsystem, a strategy subsystem, and an execution subsystem. The execution subsystem includes test report services, responsible for the collection, interpretation, and report generation of test data. During the test, the data acquisition system collects time-series data from high-frequency sensors, the central system interprets and controls parameters, and record sheets contain manually recorded data. After the test, the data scattered across multiple systems needs to be aggregated, interpreted, and calculated to generate a standardized test report.

[0003] Currently, test data in test reports is scattered across multiple heterogeneous systems such as data acquisition systems, central systems, and record sheets. Data sources are dispersed and cannot be uniformly aggregated. Test data interpretation relies on human experience and lacks a formulaic interpretation system. Report templates lack an automatic matching mechanism with machine models and test types. Report generation is disconnected from data acquisition.

[0004] Therefore, there is an urgent need for a test report automatic generation technology solution that can achieve unified aggregation of multiple types of data sources, decoupling of report fields from data sources, formulaic interpretation of steady-state / non-steady-state operating conditions, automatic matching of report templates by machine type and test type, and automatic completion of the entire process of data collection and aggregation, structured archiving, interpretation calculation and report generation after the test. Summary of the Invention

[0005] To address the technical problems existing in the prior art, the purpose of this invention is to provide a method and system for automatically gathering and interpreting test reports from multiple sources. This method achieves unified data gathering and field decoupling by configuring multiple data sources and establishing a label mapping relationship between report fields and actual data sources. It also enables formulaic interpretation of data by defining steady-state and non-steady-state formulas according to steady-state and non-steady-state operating conditions. Furthermore, it achieves automatic template matching and loading by organizing report templates into a tree structure according to machine type and test type. Finally, after the test, the method sequentially executes a complete process of automatic data collection and gathering, structured archiving, automatic template matching and loading, formula interpretation and calculation based on operating conditions, and report generation by filling in the interpretation results. This improves the automation and standardization level of test report generation.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A method for automatically aggregating and interpreting test report data from multiple sources, applied to a digital management platform for the entire process of aero-engine testing, includes the following steps: Configure multiple data sources and define the label mapping relationship between report fields and actual data sources; Define the calculation formulas and statistical methods for the reports, and distinguish the calculation formulas into steady-state formulas and unsteady-state formulas according to steady-state and unsteady-state operating conditions; Organize the report templates into a tree structure according to machine type and test type; After the experiment, experimental data was automatically collected and aggregated from various data sources and categorized by data source type. Based on the mapping relationship between report fields and actual data sources, the collected and aggregated test data is stored and archived in a structured manner according to the report template fields. Based on the test task and machine model, the corresponding report template is automatically matched from the tree structure and loaded; The archived data is located based on the label mapping relationship between the report fields and the actual data source, and the archived data is interpreted and calculated by calling steady-state formulas or non-steady-state formulas according to the working conditions. Fill the report template with the interpretation and calculation results to generate the test report.

[0007] Preferably, the multiple data sources include curve interpretation, XY curves, performance data, record data, record sheets, central interpretation, and production control.

[0008] Preferably, the specific method for defining the label mapping relationship between report fields and actual data sources is as follows: bind the report fields to the actual data source through data source labels to achieve decoupling between the report fields and the actual data source; wherein, the actual data source includes the parameter channel of the data acquisition system, the judgment result of the central system, and the record item of the record sheet.

[0009] Preferably, the steady-state formula is used for statistical calculation of steady-state step condition data, and the unsteady-state formula is used for transient calculation of transitional condition data; the formulas are constructed using experimental parameter symbols.

[0010] Preferably, during the process of filling the interpretation and calculation results into the report template to generate the test report, the text, numerical values, and chart content can be edited online; and after the test report is generated, the required fields and data compliance of the test report are checked, and the report is submitted for review after the verification is passed. Once approved, the test report will be archived. Archived historical reports can be queried by engine number, mission number, aircraft type, test type, and time range.

[0011] Preferably, during the process of automatically collecting and aggregating experimental data from various data sources, manual supplementation of missing data is supported, and digital signature confirmation is supported for key data.

[0012] An automatic aggregation and interpretation system for test reports from multiple sources includes a report model configuration side and a report generation side; The report model configuration side includes: The report template management module is used to manage the basic information of report templates, including template name, applicable models, test type, and template version. The data source label maintenance module is used to define the mapping relationship between report fields and actual data sources; The multi-data source configuration module is used to configure the multiple data sources referenced by the report. The steady-state / unsteady-state formula configuration module is used to define the calculation formulas and statistical methods for reports, and to distinguish the formulas according to steady-state and unsteady-state operating conditions. The template tree organization module is used to organize report templates into a tree structure according to machine model and test type; The report generation side includes: The multi-source data automatic acquisition and aggregation module is used to automatically aggregate data from various data sources after the experiment, and to classify and aggregate the data according to multiple types of data sources. The structured archiving module is used to store and archive the collected data in a structured manner according to the report template fields. The template auto-matching and loading module is used to automatically match and load the corresponding report templates based on the test task and machine model. The formula interpretation and calculation module is used to interpret and calculate archived data according to steady-state formulas and non-steady-state formulas. The report filling and online editing module is used to fill the report template with the interpretation and calculation results to generate the test report, and supports online editing of the report; The integrity verification and submission for review module is used to check the required fields and data compliance of the report, and submit it for review after the verification is passed.

[0013] Preferably, the data sources configured by the multi-type data source configuration module include curve interpretation, XY curves, performance data, record data, record sheets, central interpretation, and production control data.

[0014] Preferably, in the data source label maintenance module, each data source label binds a report field to a specific actual data source, wherein the actual data source includes the parameter channel of the data acquisition system, the interpretation result of the central system, and the record items of the record sheet.

[0015] Preferably, in the steady-state formula / non-steady-state formula configuration module, the steady-state formula is used for statistical calculation of steady-state step condition data, and the non-steady-state formula is used for transient calculation of transition condition data; the formulas are constructed using experimental parameter symbols.

[0016] In summary, the present invention has the following advantages: 1. This invention achieves unified aggregation of multi-source data: multiple types of data sources are uniformly aggregated through label mapping, overcoming the problems of scattered data sources and the need for manual piecing together from multiple systems in existing technologies, and significantly improving the efficiency of experimental data collection.

[0017] 2. This invention achieves formulaic and standardized interpretation: steady-state formulas / non-steady-state formulas are interpreted and calculated according to operating conditions, overcoming the problems of existing technologies that rely on human experience and have inconsistent results. The interpretation results are standardized and consistent, reducing differences and errors in human interpretation.

[0018] 3. This invention decouples fields from data sources: Data source label mapping decouples report fields from actual data sources. Changes to the data source only require adjustments to the mapping, overcoming the problems of field-data source coupling and high maintenance costs in existing technologies.

[0019] 4. This invention achieves automatic template matching: report templates are organized in a tree structure according to machine model and test type and automatically matched and loaded, overcoming the problem of manual template selection and filling in of existing technologies, and the report generation is highly automated.

[0020] 5. This invention achieves a closed loop for report generation: automatic data collection and aggregation → structured archiving → template loading and filling → online editing → integrity verification → submission for review, forming a closed loop. This overcomes the problem of the separation between report generation and data collection in existing technologies and supports multi-condition querying and tracing of historical reports. Attached Figure Description

[0021] Figure 1 This is a flowchart of a method for automatically aggregating and interpreting multi-source data to generate experimental reports.

[0022] Figure 2 This is a schematic diagram of an experimental report system for automatic aggregation and interpretation of multi-source data. Detailed Implementation

[0023] The present invention will now be described in further detail with reference to specific embodiments.

[0024] This invention relates to a digital management platform for the entire process of aero-engine testing (prototype testing). The platform divides the entire testing process into several collaborative subsystems: a management subsystem, a program configuration subsystem, a strategy subsystem, and an execution subsystem. The execution subsystem includes a test report service, responsible for the automatic acquisition and aggregation of test data, formula interpretation, and test report generation. During the test, the data acquisition system collects time-series data from high-frequency sensors, the central system performs parameter interpretation and control, and record sheets carry manually recorded data. After the test, the report service aggregates the data scattered across multiple systems, performs formula interpretation and calculation, and matches report templates to generate standardized test reports. This invention primarily addresses the problem of the "automatic aggregation and interpretation generation of multi-source test report data."

[0025] Example 1: System Configuration and Model Building; like Figures 1-2 As shown, this embodiment mainly describes the initialization process of the report model configuration side before the experiment begins, and the report model is configured first.

[0026] (a) Configuration of multiple data source types; The multi-type data source configuration module is associated with the data source label maintenance module and the steady-state / non-steady-state formula configuration module, receiving label mappings and formula configurations. The function of the multi-type data source configuration module is to configure the various data sources referenced by the report. It configures the seven types of data sources referenced by the report. Specifically, these include: Curve interpretation data source: Configure the interpretation parameters and thresholds of the test curve for automated interpretation of steady-state / non-steady-state curves; XY Curve Data Source: Configures the source of curve data acquisition for the XY coordinate system, used for correlation analysis between performance parameters; Performance data source: Configure the acquisition channels for engine performance parameters (such as thrust, fuel consumption rate, pressure ratio, etc.); Record data source: Configure the symbols and record numbers for the data recorded during the experiment; Data source for test record form: Configure the value fields for the test record form; Central interpretation data source: Configure the interpretation result data interface of the central system to obtain real-time interpretation conclusions; Production control data source: Configure task information data for the production control system.

[0027] (ii) Data source tag mapping; The data source tag maintenance module, associated with the multi-type data source configuration module, provides a mapping basis for data source aggregation. It defines the mapping relationship between report fields and actual data sources. By binding report fields to actual data sources through data source tags, it decouples report fields from their data sources. For example: The "Exhaust Temperature" field in the report is linked to the temperature parameter channel of the data acquisition system via the label "EGT"; The "Steady-state Compliance" field is bound to the steady-state interpretation result of the central system through the label "STB_VALID"; The “Record Form Remarks” field is linked to the remarks record item of the record form via the label “REMARK”.

[0028] When the data acquisition channel changes, only the physical address pointed to by the label "EGT" needs to be modified; there is no need to modify all fields in the report that reference "exhaust temperature".

[0029] (III) Steady-state / unsteady-state formula configuration; The steady-state / non-steady-state formula configuration module defines calculation formulas and statistical methods, distinguishing between steady-state and non-steady-state operating conditions. Steady-state formulas are used for statistical calculations such as the mean and deviation of steady-state step data, while non-steady-state formulas are used for transient calculations of transitional data. This module is associated with the multi-type data source configuration module, providing formulas for interpretation calculations. Formulas are constructed using experimental parameter symbols. Steady-state formula example: Calculate the average and standard deviation of the collected values ​​of a parameter within the steady-state step, such as `AVG(PARAM)` and `STD(PARAM)`, to evaluate the stability of the parameter under steady-state conditions; Example of an unsteady-state formula: Calculate the response time for transient parameters, such as `T_RESPONSE = T_END - T_START`, to evaluate transient performance such as acceleration / deceleration.

[0030] (iv) Tree-structured organization of report templates; The template tree organization module organizes report templates into a hierarchical structure of "template name → model → test type → template version," forming a tree index. For example: First layer: Test reports (such as the test of the XX type turbofan engine); Second layer: Engine type (e.g., XX type turbofan engine, YY type turbojet engine); Third layer: Test type (such as performance test, durability test, calibration test); Fourth layer: Template version (such as V1.0, V2.0).

[0031] This tree structure provides a fast retrieval basis for subsequent automatic template matching.

[0032] Automatic test report generation process; This embodiment mainly describes the complete process of automatically generating a report after the test is completed.

[0033] (v) Automatic acquisition and aggregation of test data; After the experiment, the multi-source data automatic acquisition and aggregation module was activated. This module automatically retrieves data from each data source based on the data source label mapping: For data acquisition systems, sensor timing data is read via OPC UA or similar industrial communication protocols; For the central nervous system, the interpretation results are obtained through the API interface; For record sheets, manually entered data is retrieved from a database or spreadsheet.

[0034] During the data collection process, data is categorized and aggregated according to data source type (curve interpretation, XY curves, performance data, record data, record sheets, central interpretation, production control). For data missing from automatic collection, the system supports manual supplementation; key data (such as the signature of the test leader and key performance parameters) supports digital signature confirmation.

[0035] (vi) Structured archiving; The structured archiving module stores and archives the collected experimental data in a structured manner according to the report template fields based on the tag mapping relationship between report fields and actual data sources. It establishes a key-value pair storage structure of "field name - data value" so that the aggregated data corresponds one-to-one with the template fields.

[0036] (vii) Automatic template matching and loading; The template auto-matching and loading module automatically retrieves and matches the corresponding report template from the template tree structure based on the model of the current test task (e.g., "XX type turbofan engine") and the test type (e.g., "performance test"), and loads the template's format, field definitions, and associated formulas.

[0037] (viii) Formula interpretation and calculation; The formula interpretation and calculation module locates archived data based on the label mapping relationship between report fields and actual data sources, and determines whether each data point belongs to a steady-state or non-steady-state operating condition based on its operating condition label. If it is a steady-state condition, call the corresponding steady-state formula to perform statistical calculations such as mean and deviation; If it is a non-steady-state condition, call the corresponding non-steady-state formula to perform transient calculations such as response time and rate of rise.

[0038] The calculation results are temporarily stored in the calculation cache.

[0039] (ix) Report filling and online editing; The report population and online editing module fills in the calculation results according to the data source tags into the corresponding fields of the template, generating a preliminary test report. Users can supplement, adjust, and modify various content types such as text, numerical values, and charts in the online editing interface.

[0040] (x) Completeness verification and submission review; The integrity verification and submission review module checks the required fields and data compliance of the test report before the user submits it. Check that all required fields are filled in; Check if the data format meets the requirements (such as numerical range, units, etc.); Check whether the interpretation result is within a reasonable threshold.

[0041] If the verification fails, the system will return to the editing interface with a message indicating the specific problem; if the verification passes, the system will be submitted to the approval process for review.

[0042] Once approved, the test report is archived. Archived historical reports support multi-condition queries and tracing by engine number, mission number, aircraft type, test type, and time range.

[0043] Example 2: Alternative Implementation Scheme and System Variation; This embodiment provides supplementary explanations of foreseeable variations of the above scheme.

[0044] (a) Variations in data source categories; The seven data source categories mentioned above (curve interpretation, XY curves, performance data, recorded data, record sheets, central interpretation, and production control) represent the preferred classification method for aero-engine testing. In other types of testing fields (such as aerospace propulsion testing, marine power testing, and ground-based gas turbine testing), data source categories can be added or removed based on actual operational needs. For example, "vibration data source" or "lubricating oil spectral analysis data source" can be added; any solution that includes a classification, aggregation, and label mapping mechanism for multiple data sources is an equivalent alternative to this invention.

[0045] (ii) Variations in the mapping of data source tags to targets; The mapping target of the data source label is not limited to the parameter channel of the data acquisition system, the interpretation result of the central system, and the record item of the record sheet. It can also be extended to the data interface of other experimental data management systems (such as TDM system, MES system, quality management system, etc.). It is only necessary to ensure that the data source address pointed to by the label can be resolved and accessed by the system.

[0046] (iii) Variations in formula configuration; The specific mathematical expressions for the steady-state / non-steady-state formulas can be adjusted according to different engine models and test standards. The steady-state formula is not limited to mean and standard deviation calculations, but may also include statistical quantities such as maximum, minimum, range, and coefficient of variation; the non-steady-state formula is not limited to response time, but may also include transient characteristic quantities such as overshoot, settling time, rate of rise, and time constant. The formulas are constructed using symbolic references to test parameters and remain unchanged.

[0047] (iv) Variations of template tree organization; The tree-like organizational hierarchy of report templates is not limited to "Model → Trial Type → Template Version". It can also be expanded to include organizational dimensions such as "Trial Project", "Trial Phase" and "Trial Task Type" according to actual business needs, forming a multi-dimensional tree-like index structure to support finer template matching granularity.

[0048] (v) Variations in system applications; Although this invention describes the application scenario as a digital management platform for the entire process of aero-engine testing, its core mechanisms—multi-source data label mapping and aggregation, steady-state / non-steady-state formula interpretation, template tree organization and automatic matching, and report generation closed loop—are also applicable to test data management and automatic report generation scenarios for other complex equipment (such as ship propulsion systems, large generator sets, and space launch vehicles). All applications employing the above-mentioned core mechanisms fall within the protection scope of this invention.

[0049] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for automatically gathering and interpreting test report data from multiple sources, applied to a digital management platform for the entire process of aero-engine testing, characterized in that... Includes the following steps: Configure multiple data sources and define the label mapping relationship between report fields and actual data sources; Define the calculation formulas and statistical methods for the reports, and distinguish the calculation formulas into steady-state formulas and unsteady-state formulas according to steady-state and unsteady-state operating conditions; Organize the report templates into a tree structure according to machine type and test type; After the experiment, experimental data was automatically collected and aggregated from various data sources and categorized by data source type. Based on the mapping relationship between report fields and actual data sources, the collected and aggregated test data is stored and archived in a structured manner according to the report template fields. Based on the test task and machine model, the corresponding report template is automatically matched from the tree structure and loaded; The archived data is located based on the label mapping relationship between the report fields and the actual data source, and the archived data is interpreted and calculated by calling steady-state formulas or non-steady-state formulas according to the working conditions. Fill the report template with the interpretation and calculation results to generate the test report.

2. The method for automatic aggregation and interpretation of multi-source data in test reports according to claim 1, characterized in that, The various data sources include curve interpretation, XY curves, performance data, record data, record sheets, central interpretation, and production control.

3. The method for automatic aggregation and interpretation of multi-source data in test reports according to claim 1, characterized in that, The specific method for defining the label mapping relationship between report fields and actual data sources is as follows: bind the report fields to the actual data source through data source labels to achieve decoupling between the report fields and the actual data source; wherein, the actual data source includes the parameter channel of the data acquisition system, the judgment result of the central system, and the record items of the record sheet.

4. The method for automatic aggregation and interpretation of multi-source data in test reports according to claim 1, characterized in that, The steady-state formula is used for statistical calculation of steady-state step condition data, and the unsteady-state formula is used for transient calculation of transition condition data; the formulas are constructed using experimental parameter symbols.

5. The method for automatic aggregation and interpretation of multi-source data in test reports according to claim 1, characterized in that, During the process of filling the interpretation and calculation results into the report template to generate the test report, the text, numerical values ​​and charts can be edited online; and after the test report is generated, the required fields and data compliance of the test report are checked, and the report is submitted for review after the verification is passed. Once approved, the test report will be archived. Archived historical reports can be queried by engine number, mission number, aircraft type, test type, and time range.

6. The method for automatic aggregation and interpretation of multi-source data in test reports according to claim 1, characterized in that, During the process of automatically collecting and aggregating experimental data from various data sources, manual entry is supported for missing data, and digital signature confirmation is supported for key data.

7. A system for automatically gathering and interpreting multi-source data in experimental reports, characterized in that, This includes the report model configuration side and the report generation side; The report model configuration side includes: The report template management module is used to manage the basic information of report templates, including template name, applicable models, test type, and template version. The data source label maintenance module is used to define the mapping relationship between report fields and actual data sources; The multi-data source configuration module is used to configure the multiple data sources referenced by the report. The steady-state / unsteady-state formula configuration module is used to define the calculation formulas and statistical methods for reports, and to distinguish the formulas according to steady-state and unsteady-state operating conditions. The template tree organization module is used to organize report templates into a tree structure according to machine model and test type; The report generation side includes: The multi-source data automatic acquisition and aggregation module is used to automatically aggregate data from various data sources after the experiment, and to classify and aggregate the data according to multiple types of data sources. The structured archiving module is used to store and archive the collected data in a structured manner according to the report template fields. The template auto-matching and loading module is used to automatically match and load the corresponding report templates based on the test task and machine model. The formula interpretation and calculation module is used to interpret and calculate archived data according to steady-state formulas and non-steady-state formulas. The report filling and online editing module is used to fill the report template with the interpretation and calculation results to generate the test report, and supports online editing of the report; The integrity verification and submission for review module is used to check the required fields and data compliance of the report, and submit it for review after the verification is passed.

8. The system according to claim 7, characterized in that, The multi-type data source configuration module configures data sources including curve interpretation, XY curves, performance data, record data, record sheets, central interpretation, and production control data.

9. The system according to claim 7, characterized in that, In the data source label maintenance module, each data source label binds the report field to a specific actual data source, which includes the parameter channel of the data acquisition system, the interpretation result of the central system, and the record items of the record sheet.

10. The system according to claim 7, characterized in that, In the steady-state formula / non-steady-state formula configuration module, the steady-state formula is used for statistical calculation of steady-state step condition data, and the non-steady-state formula is used for transient calculation of transition condition data; the formulas are constructed using experimental parameter symbols.

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