A method and device for matching and mapping digital and real test data of aerospace equipment

Abstract

The present invention discloses a method and device for matching and mapping digital and physical test data of aerospace equipment, which belongs to the fields of electronic engineering and computer science. The method is applicable to aerospace equipment that can simultaneously conduct digital tests and physical tests, and includes digital and physical test data file reading, digital and physical test data spatial coordinate matching, digital and physical test data time series matching, digital and physical test data magnitude matching, and digital and physical test data mapping. The present invention takes into account the differences in data magnitude, time dimension, and space dimension of digital and physical test data of aerospace equipment, and establishes a corresponding relationship between digital and physical test data through the invented mapping and matching method, which is conducive to the full integration and utilization of digital and physical test data.

Description

Technical Field

[0001] The present invention belongs to the field of electronic engineering and computer science, and specifically relates to a method and device for matching and mapping digital and real test data of aerospace equipment. Background Art

[0002] For aerospace equipment, testing is an important way to measure its performance. Current testing methods mainly include digital testing and physical testing. Traditional physical testing often causes damage to the tested products and is time-consuming and labor-intensive. With the emergence of digital testing, the reliance on physical testing has been reduced to a certain extent, but there is a disadvantage that the digital test results are inaccurate. Digital-physical fusion testing of aerospace equipment has become an important development trend in future testing. However, the current consideration of the multi-dimensional differences in time, space, and magnitude of digital-physical test data is not comprehensive. How to achieve the matching and mapping of physical test data and digital test data of aerospace equipment is urgently needed. There is no relevant method for matching and mapping digital-physical test data of aerospace equipment in the existing technology. Summary of the invention

[0003] In order to overcome the shortcomings of the prior art, the present invention provides a method and device for matching and mapping digital and real test data of aerospace equipment, which fully considers the differences in spatial position, time series, and data magnitude, supports all-round matching and mapping of digital and real test data of aerospace equipment, and reduces the workload of data analysis and processing and the computational cost of digital and real test data through reasonable data extraction strategies.

[0004] The present invention solves the technical problem by adopting the following technical solution: a method for matching and mapping digital and real test data of aerospace equipment, comprising the following steps:

[0005] Step (1), reading digital and physical test data of aerospace equipment, the aerospace equipment performs digital tests to generate digital test data files related to performance, obtains physical test data files related to physical tests of aerospace equipment with the help of sensors or controllers, and parses the test data file format to realize the reading of digital and physical test data; the digital test of aerospace equipment is a process in which the aerospace equipment model inputs the set initial conditions and environmental conditions in the digital space, and evaluates the performance of aerospace equipment based on physical mechanisms and algorithm simulation;

[0006] Step (2), classifying the digital test data of aerospace equipment, classifying the test data according to the data source, and using different data processing schemes for different types of test data; the digital test data are all labeled data obtained during the test of aerospace equipment;

[0007] Step (3): for the physical test data obtained from the physical test, data cleaning, data integration, data transformation, and data specification are performed in sequence to ensure the quality of the physical test data;

[0008] Step (4): Based on the differences between digital test data and physical test data in terms of spatial dimension, time dimension, and data magnitude, coordinate transformation, time series matching, and data sampling are performed on the digital test data to support the matching of digital and physical test data of aerospace equipment.

[0009] Step (5): Process the extracted aerospace equipment digital and real test data to further establish a mapping and matching relationship between the physical test data and the digital test data.

[0010] The present invention also provides a device for matching and mapping digital and real test data of aerospace equipment, comprising the following modules:

[0011] The digital and real test data reading module of aerospace equipment is used to generate digital test data files related to performance through digital tests, obtain relevant physical test data files of aerospace equipment physical tests with the help of sensors or controllers, and parse the test data file format to realize the reading of digital and real test data; the digital test of aerospace equipment is a process in which the aerospace equipment model inputs the set initial conditions and environmental conditions in the digital space, and evaluates the performance of aerospace equipment based on physical mechanisms and algorithm simulation;

[0012] The aerospace equipment digital test data classification module is used to classify the test data according to the data source and adopt different data processing schemes for different types of test data; the digital test data are all labeled data obtained during the aerospace equipment test;

[0013] The physical experiment data processing module performs data cleaning, data integration, data transformation, and data reduction in order to ensure the quality of the physical experiment data;

[0014] The digital-to-physical test data matching module performs coordinate transformation, time series matching, and data sampling on the digital test data according to the differences between the digital test data and the physical test data in terms of spatial dimension, time dimension, and data magnitude, so as to support the matching of digital-to-physical test data of aerospace equipment.

[0015] The mapping and matching relationship establishment module processes the extracted digital and real test data of aerospace equipment and further establishes the mapping and matching relationship between the physical test data and the digital test data.

[0016] The advantages of the present invention compared with the prior art are:

[0017] The present invention simultaneously takes into account the differences in spatial and temporal dimensions of digital test data of aerospace equipment. Based on the analysis of the differences in the characteristics of the digital test data, the spatial and temporal unification and consistency of the digital test data are ensured through a spatial coordinate system based on coordinate transformation, data time series selection based on similarity, and data extraction based on criticality assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a flowchart of a method for matching and mapping digital and real test data of aerospace equipment.

[0019] Figure 2 It is a comparison diagram of the effects of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in each embodiment of the present invention described below can be combined with each other as long as they do not conflict with each other. To achieve the above-mentioned purpose, the present invention adopts the following technical scheme.

[0021] The present invention relates to a method for matching and mapping digital and physical test data of aerospace equipment, which is suitable for aerospace equipment that can simultaneously conduct digital tests and physical tests. One of the key links in realizing the integration of digital and physical tests of aerospace equipment is to establish the matching and mapping relationship of digital and physical test data. Limited by the test conditions and test equipment, there are differences in many aspects between the physical test measurement data and the performance-related data generated by the digital test. Therefore, how to achieve the matching and mapping of digital test data and physical test data has become an urgent problem to be solved. The method disclosed in the present invention includes digital and physical test data file reading, digital and physical test data spatial coordinate matching, digital and physical test data time series matching, digital and physical test data magnitude matching, and digital and physical test data mapping. In the matching process, the differences in time, space and magnitude are fully considered, and the analysis and calculation complexity of the data is reduced through a reasonable data extraction strategy, so as to establish a mapping relationship of digital and physical test data to provide support for the performance evaluation of aerospace equipment.

[0022] The flowchart of the present invention is as follows Figure 1 As shown, Figure 1 The key steps involved are as follows:

[0023] Step (1) reads the digital and physical test data of aerospace equipment, and parses and reads the source data of different formats generated by physical test measurement and digital test. The physical test measurement data is data obtained by using sensors such as temperature sensors, pressure sensors, vibration sensors, etc. that can measure the environment and the equipment's own status information. The digital test generated data refers to data obtained by simulating and emulating the digital model of aerospace equipment and the environment model under set conditions with the help of finite element methods.

[0024] Step (2) classifies the digital and physical test data read in step (1). On the one hand, it is divided into digital test data and physical test data from the source, and on the other hand, it is divided into spatial coordinate data, time series data, and spatial coordinate time series data according to its data attributes. Different data processing methods are used for different data types. The data obtained from the physical test needs to be cleaned, integrated, transformed, and reduced. For the coordinate data related to the digital test data that only contains spatial information, the coordinate transformation needs to be performed, the time series data that only contains time information needs to be selected, and the time series data that contains spatial coordinate information needs both coordinate transformation and data selection.

[0025] Step (3) For the physical test data that has been classified in step (2), data cleaning, data integration, data transformation, and data reduction are performed in sequence to ensure the quality of the data obtained from the physical test, including:

[0026] Step (3.1) first cleans the data. For missing values, use interpolation-based data completion methods. For outliers, after identifying outliers, use deletion, filling, and conversion methods according to the actual situation. For duplicate values, delete the duplicate values ​​after identifying them.

[0027] Step (3.2) Data integration is the process of processing data from different sources to form a unified data set. In this step, the dimensional difference, numerical conflict, and redundancy problems are solved in turn. For different dimensions, normalization is used to deal with them. For numerical conflicts, empirical knowledge is used to make choices. For data redundancy, chi-square test, numerical data correlation coefficient, and covariance are used to detect redundancy, and then redundant values ​​are deleted.

[0028] Step (3.3) Data transformation is to transform the aerospace equipment physical test data into the expected form and range by mathematical function transformation, that is, the original data x is transformed by the formula Get normalized data ,in is the minimum value in the test data set, is the maximum value in the test data set.

[0029] Step (3.4) uses numerical reduction and attribute reduction methods to reduce the physical test data of aerospace equipment, thereby reducing the amount of data while maintaining the integrity and value of the original test data, thereby reducing data storage costs and improving data utilization efficiency. The attribute reduction is to use principal component analysis to replace more variables in the original data with fewer variables to reduce strongly correlated data variables. The numerical reduction is to use sampling, clustering, and regression methods to reduce the amount of numerical test data.

[0030] Step (4), digital test data is not restricted by test sites and test conditions, and can simulate the status of aerospace equipment in more complex scenes and conditions. In addition, it can obtain aerospace equipment information at more points. Therefore, it is different from physical test data in terms of spatial dimension, time dimension and data magnitude. Therefore, in the process of digital test data processing, guided by physical test data, the processing of digital test data is carried out from three aspects: spatial coordinates, time series and data magnitude, so as to achieve the purpose of matching and mapping digital and physical test data of aerospace equipment, including:

[0031] Step (4.1) Matching of space coordinate information of virtual test of aerospace equipment: Compare the coordinate system of measured data of physical test with the coordinate system of virtual test, perform space transformation according to the difference of their coordinate systems, and obtain the transformed new coordinate data respectively. The coordinate systems are all three-dimensional rectangular coordinate systems; the coordinate system of physical test data set A is O-xyz, the coordinate system of digital test data set B is O'-x'y'z', and the coordinate of P in O'-x'y'z' coordinate system is , the coordinates of P in the O-xyz coordinate system are , then the formula for transforming from the O'-x'y'z' coordinate system to the O-xyz coordinate system is ,in is the rotation matrix, is the translation vector, and the above coordinate transformation supports the matching of numerical experimental data in the spatial dimension;

[0032] Step (4.2) Matching of digital test time series data of aerospace equipment: First, based on the known physical test data, narrow the search range of virtual test data, and then use discrete Fourier transform to calculate the distance of time series data by comparing the Fourier parameters of digital and real test time series data, so as to realize the search and matching of virtual test time series data of aerospace equipment;

[0033] Step (4.3) Match the magnitude of digital and physical test data of aerospace equipment, and reasonably extract digital test data according to the magnitude of physical test data after specification. In terms of spatial coordinates, on the premise of selecting the digital test spatial coordinate information corresponding to the coordinate information obtained by the physical test, further select representative key point data. In terms of time series, after searching and matching the virtual test time series data, further data sampling is performed to reduce the data magnitude. By processing the time and space related data, the digital test data of aerospace equipment and the physical test data can be matched in terms of data magnitude.

[0034] Step (5) establishes a mapping relationship between the physical test data processed in step (3) and the digital test data extracted in step (4), that is, the correspondence between the spatial coordinates of the digital and physical tests at the same time and the corresponding attribute values, establishes a specific mapping relationship network, and stores the mapping relationship. Through the constructed mapping relationship, the association and difference between the digital and physical tests can be clarified, thereby further giving play to the characteristic advantages of the digital and physical tests, and realizing the integration of digital and physical tests and the comprehensive and accurate evaluation of the performance of aerospace equipment.

[0035] The present invention also provides a device for matching and mapping digital and real test data of aerospace equipment, comprising the following modules:

[0036] The digital and real test data reading module of aerospace equipment is used to generate digital test data files related to performance through digital tests, obtain relevant physical test data files of aerospace equipment physical tests with the help of sensors or controllers, and parse the test data file format to realize the reading of digital and real test data; the digital test of aerospace equipment is a process in which the aerospace equipment model inputs the set initial conditions and environmental conditions in the digital space, and evaluates the performance of aerospace equipment based on physical mechanisms and algorithm simulation;

[0037] The aerospace equipment digital test data classification module is used to classify the test data according to the data source and adopt different data processing schemes for different types of test data; the digital test data are all labeled data obtained during the aerospace equipment test;

[0038] The physical experiment data processing module performs data cleaning, data integration, data transformation, and data reduction in order to ensure the quality of the physical experiment data;

[0039] The digital-to-physical test data matching module performs coordinate transformation, time series matching, and data sampling on the digital test data according to the differences between the digital test data and the physical test data in terms of spatial dimension, time dimension, and data magnitude, so as to support the matching of digital-to-physical test data of aerospace equipment.

[0040] The mapping and matching relationship establishment module processes the extracted digital and real test data of aerospace equipment and further establishes the mapping and matching relationship between the physical test data and the digital test data.

[0041] In summary, the present invention discloses a method and device for matching and mapping digital and real test data of aerospace equipment, including digital and real test data file reading, digital and real test data spatial coordinate matching, digital and real test data time series matching, digital and real test data magnitude matching, and digital and real test data mapping. By fully analyzing and considering the differences in different dimensions of time, space, and magnitude of digital and real test data, and using reasonable data extraction strategies, while establishing the matching and mapping relationship of digital and real test data, the magnitude of test data to be processed is reduced, and the processing efficiency of digital and real test data is improved. Specific embodiment:

[0043] This embodiment takes the performance test of a certain aircraft engine as an example, and obtains the cylinder temperature, exhaust temperature, intake pressure, fuel pressure, whole machine vibration frequency, and whole machine amplitude through temperature sensors, pressure sensors, and vibration sensors, respectively. With the help of finite element analysis tools, the operation process of a certain aircraft engine is simulated and calculated under the same conditions as the physical test to obtain digital test data related to temperature distribution, pressure distribution, and structural vibration. There are differences between digital test data and physical test data in spatial coordinates, time series, and data magnitude. In order to support the performance evaluation of a certain type of aircraft engine, it is necessary to achieve accurate matching and mapping of digital test data and physical test data.

[0044] The specific steps are as follows:

[0045] The first step is to read the physical test data collected from a certain type of aircraft engine and the data generated by digital test simulation.

[0046] The second step is to classify the data types. The temperature data, pressure data, and vibration data used in this embodiment are time series data containing spatial information, that is, they are temperature sequences, pressure sequences, and vibration sequences at specific spatial points.

[0047] The third step is to clean, integrate, transform and reduce the classified data. Data with a standard score greater than 3 is defined as an outlier and removed. In the data transformation, the range of digital test and physical test data is defined, such as min (cylinder temperature) = 120℃, max (cylinder temperature) = 250℃.

[0048] The fourth step is to match the digital test data of a certain type of aircraft engine performance with the physical test data in terms of spatial coordinates, time series, and data magnitude. Spatial coordinate matching means that in the case of a unified coordinate system, the temperature data of the points corresponding to the digital test are selected according to the coordinate information of the sensor measurement points arranged in the physical test; time series matching means that through similarity calculation, a group of data with the highest similarity is selected as the matching and mapping data; in terms of data magnitude, the digital test data set is re-extracted according to the sampling frequency and period of the physical test data to achieve data magnitude matching.

[0049] like Figure 2 As shown in the figure, when the spatial coordinates are not mapped and matched, the time series data matching rate is less than 50%, and the comprehensive matching rate is also less than 50%. When the spatial coordinates are matched and mapped, but the time series is not mapped and matched, the comprehensive matching rate is also less than 50%. That is, the digital test data and physical test data that have not been fully matched are lowly correlated. However, through the matching and mapping method of digital and physical test data of aerospace equipment of the present invention, the comprehensive matching rate of the reliability digital test of a certain aerospace equipment in the spatial dimension, time dimension and data magnitude reaches more than 95%.

[0050] The contents not described in detail in the specification of the present invention belong to the prior art known to the professional and technical personnel in this field.

[0051] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for matching and mapping digital and real test data of aerospace equipment, characterized in that: The method steps are as follows: Step (1), reading digital and physical test data of aerospace equipment, the aerospace equipment performs digital tests to generate digital test data files related to performance, obtains physical test data files related to physical tests of aerospace equipment with the help of sensors or controllers, and parses the test data file format to realize the reading of digital and physical test data; the digital test of aerospace equipment is a process in which the aerospace equipment model inputs the set initial conditions and environmental conditions in the digital space, and evaluates the performance of aerospace equipment based on physical mechanisms and algorithm simulation; Step (2), classifying the digital test data of aerospace equipment, classifying the test data according to the data source, and using different data processing schemes for different types of test data; the digital test data are all labeled data obtained during the test of aerospace equipment; Step (3): for the physical test data obtained from the physical test, data cleaning, data integration, data transformation, and data specification are performed in sequence to ensure the quality of the physical test data; Step (4): Based on the differences between digital test data and physical test data in terms of spatial dimension, time dimension, and data magnitude, coordinate transformation, time series matching, and data sampling are performed on the digital test data to support the matching of digital and physical test data of aerospace equipment. Step (5), processing the extracted digital and real test data of aerospace equipment, and further establishing a mapping and matching relationship between the physical test data and the digital test data; Step (4) specifically includes: Step (4.1) Coordinate transformation of digital test data; Step (4.2) digital test data timing selection; Step (4.3) digital test data extraction; Step (4.1) specifically includes: For the spatial position data, the coordinate system of the physical test data set A is first determined to be O-xyz, and the coordinate system of the digital test simulation data set B is O'-x'y'z'; according to the difference in the relative position and angle of the two coordinate axes, the spatial position coordinates in the data set are transformed, and the coordinates of P in the O'-x'y'z' coordinate system are , the coordinates of P in the O-xyz coordinate system are ,but ,in is the rotation matrix, is the translation vector, thus supporting the matching of digital and real experimental data in the spatial dimension.

2. A method for matching and mapping digital and real test data of aerospace equipment according to claim 1, characterized in that: Step (2) specifically includes: dividing it into digital test data and physical test data from the source point of view, and dividing it into coordinate data containing only spatial information, time series data containing only time information, and time series data containing spatial coordinates according to its data attributes.

3. A method for matching and mapping digital and real test data of aerospace equipment according to claim 1, characterized in that: Step (3) specifically includes: Step (3.1) data cleaning; including: performing missing value processing, duplicate value processing, and outlier processing on the obtained aerospace equipment physical test data; the missing value processing is to compensate for the missing values ​​by interpolation, the duplicate value processing is to delete the duplicate values, and the outlier processing is to delete or interpolate the outliers; Step (3.2) Data integration: including: connecting and merging data from different sources, thereby coordinating different data, eliminating redundant data, and integrating data into the same data set; data merging is the process of combining data into a large data set for three situations: specific identical fields, specific identical record types but different fields, and attribute types with certain associations; Step (3.3) Data transformation: including: format conversion, standardization and normalization of aerospace equipment physical test data for subsequent analysis and utilization; Step (3.4) data reduction; including: using attribute reduction and numerical reduction methods to reduce the amount of data while maintaining the original appearance of the data; the attribute reduction is to use principal component analysis to replace more variables in the original data with fewer variables to reduce strongly correlated data variables; the numerical reduction is to use sampling, clustering, and regression methods to reduce the amount of physical test data.

4. A method for matching and mapping digital and real test data of aerospace equipment according to claim 3, characterized in that: Step (4.2) specifically includes: The similarity of the digital real test data is calculated based on discrete Fourier transform. The similarity calculation method is to map the time domain data to the frequency domain through Fourier transform, and calculate the distance of the time series data by comparing the Fourier parameters of the digital real test time series data, so as to select the time series data of the digital test with the highest similarity to the physical test time series data, so as to support the matching of the digital real test data in the time dimension.

5. A method for matching and mapping digital and real test data of aerospace equipment according to claim 4, characterized in that: Step (4.3) specifically includes: By comparing the magnitude difference between digital test data and physical test data, a corresponding data extraction strategy is adopted for the digital test data; for the spatial coordinate data transformed in step (4.1), the extracted digital test data is matched with the coordinate information of the key points that can be obtained from the physical test; for the time series data selected in step (4.2), further sampling is performed to reduce the data magnitude while ensuring the match between the digital and physical test data, thereby reducing the data processing and calculation costs; data extraction follows the principle of dense sampling of key data and sparse sampling of non-key data.

6. A method for matching and mapping digital and real test data of aerospace equipment according to claim 1, characterized in that: Digital and physical tests are carried out simultaneously on aerospace equipment.

7. A device for matching and mapping digital and real test data of aerospace equipment according to any one of claims 1 to 6, characterized in that: Includes the following modules: The digital and real test data reading module of aerospace equipment is used to generate digital test data files related to performance through digital tests, obtain relevant physical test data files of aerospace equipment physical tests with the help of sensors or controllers, and parse the test data file format to realize the reading of digital and real test data; the digital test of aerospace equipment is a process in which the aerospace equipment model inputs the set initial conditions and environmental conditions in the digital space, and evaluates the performance of aerospace equipment based on physical mechanisms and algorithm simulation; The aerospace equipment digital test data classification module is used to classify the test data according to the data source and adopt different data processing schemes for different types of test data; the digital test data are all labeled data obtained during the aerospace equipment test; The physical experiment data processing module performs data cleaning, data integration, data transformation, and data reduction in order to ensure the quality of the physical experiment data; The digital-to-physical test data matching module performs coordinate transformation, time series matching, and data sampling on the digital test data according to the differences between the digital test data and the physical test data in terms of spatial dimension, time dimension, and data magnitude, so as to support the matching of digital-to-physical test data of aerospace equipment. The mapping and matching relationship establishment module processes the extracted digital and real test data of aerospace equipment and further establishes the mapping and matching relationship between the physical test data and the digital test data.

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