Method and device for judging failure measurement data of aircraft structure static test, equipment and medium

Abstract

This application provides a method, apparatus, equipment, and medium for judging failure measurement data in static strength tests of aircraft structures, belonging to the technical field of static strength testing of aircraft structures. The method includes marking failure measurement points already determined by the data acquisition system's self-check or other methods before the test begins; during the test, for each set of data acquired, a sliding window method is used to cyclically judge the failure data for each data point in that set. The failure data judgment includes: determining whether the current measurement point has already been marked as a failure measurement point; if so, judging the next measurement point according to preset judgment parameters; the preset judgment parameters include an upper limit for the measurement value, a lower limit for the measurement value, a starting load, an upper limit for the load, a number of fitting blocks, a first-check coefficient, and a lower limit for the coefficient. Through the processing scheme of this application, automatic judgment and marking of test failure data are achieved, improving the efficiency of failure measurement data judgment.

Description

Technical Field

[0001] This application relates to the field of static strength testing technology for aircraft structures, and in particular to a method, device, equipment and medium for judging the measurement data of static test failure of aircraft structures. Background Technology

[0002] In aircraft structural static strength testing, to ensure the safe and smooth conduct of the test, it is necessary to analyze the measurement data in real time, promptly identify abnormal data, and conduct analysis and evaluation to avoid unexpected structural damage and reduce test risks. However, the presence of failure data significantly impacts the efficiency of real-time data analysis, especially in full-aircraft static strength testing, where the number of measurement points continuously increases, reaching up to over 30,000, resulting in hundreds of failure data points. Furthermore, failure data is often mixed with abnormal test data, greatly increasing the workload of measurement personnel in real-time data analysis and reducing analysis efficiency. Therefore, a method for judging failure measurement data in aircraft structural static strength testing is needed to mark or remove failure data. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method for judging failure measurement data in static strength tests of aircraft structures, to solve the technical problem in the prior art where failure data and abnormal test data are mixed in static strength tests of aircraft structures, resulting in a large workload and low efficiency for measurement personnel in real-time data analysis. The method includes:

[0004] Before the test begins, mark the failure measurement points that have been identified by the data acquisition system's self-test or other methods; During the experiment, for each set of data collected, a sliding window method was used to cyclically judge each data point in the set as a failed data point. The failed data judgment includes: judging whether the current measurement point has been marked as a failed measurement point. If so, the next measurement point is judged according to the preset judgment parameters. The preset judgment parameters include the upper limit of the measured value, the lower limit of the measured value, the starting load, the upper limit of the load, the number of fitting blocks, the first inspection coefficient, and the lower limit of the coefficient. The starting load is set to the load after the test tare is completed, the upper limit of the load is set to the maximum load of the linear change of the aircraft structure, the number of fitting blocks is set to the number of measurement data in the sliding window, the first inspection coefficient is set to the correlation coefficient threshold value when the measurement point is judged for the first time when the condition is met, and the lower limit of the coefficient is set to the correlation coefficient threshold value when the measurement point is not judged for the first time when the condition is met.

[0005] According to a specific implementation of this application, the correlation coefficient is used to represent the correlation between the measurement data and the applied load on the test piece, and the expression for the correlation coefficient is: , Where r is the correlation coefficient, xi For the percentage of load measured step by step, y i For x i The corresponding measured value, where n is the measured value y i The total number.

[0006] According to a specific implementation of an embodiment of this application, the step of determining the next measurement point based on preset judgment parameters includes: Determine whether the measured value of the current measurement point exceeds the set upper limit of the measurement value. If so, mark it as invalid and then determine the next measurement point. Determine if the current load is not less than the starting load and not greater than the upper limit of the load; if not, determine the next measurement point. Determine if the number of data points within the sliding window meets the set number of fitting blocks; if not, proceed to the next measurement point. Determine whether the measured value at the current measurement point is not less than the set lower limit of the measured value; if not, determine the next measurement point. Calculate the correlation coefficient between the measured values ​​and the load within the sliding window; Whether a measurement point is being used for the first time is determined based on the correlation coefficient, and the failure measurement point is determined based on the initial inspection coefficient and the lower limit of the coefficient. Once all measurement points have been evaluated, wait for the next set of data and repeat the process of evaluating failed data.

[0007] According to a specific implementation of an embodiment of this application, the step of determining the failure measurement point based on the initial inspection coefficient and the lower limit of the coefficient includes: If the measurement point is being judged for the first time based on the correlation coefficient, then it is determined whether the correlation coefficient is greater than the set initial inspection coefficient. If not, it is marked as a failed measurement point, and then the next measurement point is judged. If the measurement point is not being judged based on the correlation coefficient for the first time, then it is determined whether the correlation coefficient is greater than the set lower limit of the coefficient. If not, it is marked as a failed measurement point, and then the next measurement point is judged.

[0008] This invention also provides a device for judging failure measurement data in static strength tests of aircraft structures, to solve the technical problem in the prior art where failure data and abnormal test data are mixed in static strength tests of aircraft structures, resulting in a large workload and low efficiency for measurement personnel in real-time data analysis. The device includes: The marking module is used to mark the failed measurement points that have been identified by the data acquisition system's self-test or other methods before the test begins. The judgment module is used during the test to perform failure data judgment on each data in the data set in a sliding window manner after each set of data is collected. The failure data judgment includes: judging whether the current measurement point has been marked as a failure measurement point. If so, the next measurement point is judged according to the preset judgment parameters. The preset judgment parameters include the upper limit of the measured value, the lower limit of the measured value, the starting load, the upper limit of the load, the number of fitting blocks, the first inspection coefficient, and the lower limit of the coefficient. The starting load is set to the load after the test tare is completed, the upper limit of the load is set to the maximum load of the linear change of the aircraft structure, the number of fitting blocks is set to the number of measurement data in the sliding window, the first inspection coefficient is set to the correlation coefficient threshold value when the measurement point is judged for the first time when the condition is met, and the lower limit of the coefficient is set to the correlation coefficient threshold value when the measurement point is not judged for the first time when the condition is met.

[0009] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned methods for judging the failure measurement data of static strength tests of aircraft structures, thereby solving the technical problem in the prior art where failure data and abnormal test data are mixed in static strength tests of aircraft structures, resulting in a large workload and low efficiency for measurement personnel in real-time data analysis.

[0010] This invention also provides a computer-readable storage medium storing a computer program that executes any of the above-described methods for judging the failure measurement data of static test of aircraft structures. This addresses the technical problem in the prior art where failure data and abnormal test data are mixed in static strength tests of aircraft structures, resulting in a large workload and low efficiency for measurement personnel in real-time data analysis.

[0011] Beneficial effects: In previous aircraft structural strength tests, there was a lack of effective methods for judging failure data. Typically, data analysts would observe changes in curves and manually determine whether the test data indicated failure, which was inefficient. Because failure data judgment was based on manual intervention, real-time early warning and automated analysis of the data were impossible.

[0012] The method for judging the failure measurement data of static strength test of aircraft structure in this application realizes the automatic judgment and marking of failure data of static strength test of aircraft structure, which greatly improves the judgment efficiency of failure measurement data, thereby laying the foundation for further analysis of measurement data and real-time early warning of the test. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1A flowchart of a method for judging the failure measurement data of an aircraft structure static test according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a sliding window model according to an embodiment of the present invention; Figure 3 This is a schematic diagram of parameter settings according to an embodiment of the present invention. Detailed Implementation

[0015] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0016] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0017] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0018] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0019] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0020] Reference Figure 1 This invention provides a method for judging failure measurement data in static strength tests of aircraft structures, addressing the technical problem in existing technologies where failure data and abnormal test data are mixed in static strength tests of aircraft structures, leading to a large workload and low efficiency for measurement personnel in real-time data analysis. The method includes: Before the test begins, mark the failure measurement points that have been identified by the data acquisition system's self-test or other methods; During the experiment, for each set of data collected, a sliding window method was used to cyclically judge each data point in the set as a failed data point. The failed data judgment includes: judging whether the current measurement point has been marked as a failed measurement point. If so, the next measurement point is judged according to the preset judgment parameters. The preset judgment parameters include the upper limit of the measured value, the lower limit of the measured value, the starting load, the upper limit of the load, the number of fitting blocks, the first inspection coefficient, and the lower limit of the coefficient. The starting load is set to the load after the test tare is completed, the upper limit of the load is set to the maximum load of the linear change of the aircraft structure, the number of fitting blocks is set to the number of measurement data in the sliding window, the first inspection coefficient is set to the correlation coefficient threshold value when the measurement point is judged for the first time when the condition is met, and the lower limit of the coefficient is set to the correlation coefficient threshold value when the measurement point is not judged for the first time when the condition is met.

[0021] This embodiment analyzes various factors affecting data measurement in aircraft structural static strength tests, sets monitoring thresholds for measurement data, and establishes a judgment algorithm and process for failure measurement data to achieve real-time judgment of failure data in aircraft structural static strength tests. In specific implementation, this method selects sample data for judging failure measurement data using a sliding window. The number of measurement data points within the sliding window remains constant. Each time a new measurement data point enters, if the sliding window is full, the first measurement data point entered is deleted, and the sliding window is updated; otherwise, the newly entered measurement data is added to the end of the sliding window. The sliding window model is as follows: Figure 2 As shown.

[0022] In specific implementation, the preset judgment parameters in this embodiment are explained as follows: Upper limit of measurement value: The maximum value that may occur at all measurement points during the test. If the measured value exceeds this set value, it will be directly judged as a failed measurement data. Lower limit of measurement value: The minimum value that the measured value (absolute value) must reach when judging failure data during the test. If the measured value (absolute value) is less than this set value, failure data judgment will not be performed. Initial Load: During the test, due to the influence of the test facilities, the load is applied non-linearly in the initial stage, therefore failure data cannot be determined. The initial load is generally set to the load at which the test tare is completed. Failure data is not determined if the test load is less than this set value. Load Limit: In aircraft structural strength tests, some structures are allowed to experience instability or enter the plastic stage after a certain load. In these cases, the measured data exhibits a non-linear relationship with the test load, making failure data assessment impossible. The load limit is generally the maximum load that linearly changes within the aircraft structure. Failure data assessment is not performed when the test load exceeds this set value. Number of fitted blocks: The number of measurement data points within the sliding window. If the number of measurement data points within the sliding window is less than this set value, no invalid data will be identified. First-inspection coefficient: The threshold value for the correlation coefficient when judging failure data for the first time at each measurement point, under certain conditions. If the correlation coefficient is less than this set value, the data is judged as failure data. Lower limit of the coefficient: The threshold value of the correlation coefficient when the measurement point is not being judged as failure data for the first time, provided that the conditions are met. If the correlation coefficient is less than this set value, the data is judged as failure data.

[0023] Furthermore, the correlation coefficient is used to represent the correlation between the measured data and the applied load on the test piece, and the expression for the correlation coefficient is: , Where r is the correlation coefficient, x i For the percentage of load measured step by step, y i For x i The corresponding measured value, where n is the measured value y i The total number.

[0024] In one embodiment, refer to Figure 1 The step of determining the next measurement point based on preset judgment parameters includes: Determine whether the measured value of the current measurement point exceeds the set upper limit of the measurement value. If so, mark it as invalid and then determine the next measurement point. Determine if the current load is not less than the starting load and not greater than the upper limit of the load; if not, determine the next measurement point. Determine if the number of data points within the sliding window meets the set number of fitting blocks; if not, proceed to the next measurement point. Determine whether the measured value at the current measurement point is not less than the set lower limit of the measured value; if not, determine the next measurement point. Calculate the correlation coefficient between the measured values ​​and the load within the sliding window; Whether a measurement point is being used for the first time is determined based on the correlation coefficient, and the failure measurement point is determined based on the initial inspection coefficient and the lower limit of the coefficient. Once all measurement points have been evaluated, wait for the next set of data and repeat the process of evaluating failed data.

[0025] Furthermore, the determination of failure measurement points based on the initial inspection coefficient and the lower limit of the coefficient includes: If the measurement point is being judged for the first time based on the correlation coefficient, then it is determined whether the correlation coefficient is greater than the set initial inspection coefficient. If not, it is marked as a failed measurement point, and then the next measurement point is judged. If the measurement point is not being judged based on the correlation coefficient for the first time, then it is determined whether the correlation coefficient is greater than the set lower limit of the coefficient. If not, it is marked as a failed measurement point, and then the next measurement point is judged.

[0026] In this embodiment, the aforementioned hierarchical and progressive judgment logic enables precise screening and failure identification of measurement data in static tests of aircraft structures. First, preliminary judgment of the upper and lower limits of measured values ​​quickly eliminates abnormal data that significantly exceeds reasonable ranges, preventing subsequent invalid calculations. Limiting the load range ensures that the validity of data judgment is only applicable to the effective range of the test load, excluding interference data from non-loading phases. Verification of the number of data points within the sliding window provides a sufficient sample size for subsequent correlation coefficient calculations, ensuring the reliability of the fitting analysis. Based on the correlation coefficient judgment, the differentiated setting of the initial detection coefficient and the lower limit of the coefficient considers both the potential instability of data in the initial stage of measurement points and the strict control of data quality during subsequent continuous monitoring, effectively identifying failures caused by structural damage or other reasons leading to a decrease in the correlation between measurement data and load. This multi-dimensional, step-by-step judgment method comprehensively improves the accuracy and efficiency of failure measurement data judgment, providing strong data support for the safety assessment and result analysis of static tests of aircraft structures.

[0027] The method for judging aircraft structural strength test failure measurement data in this application generally serves as the basis for real-time analysis and early warning of test data. Before the test, relevant parameters are set; during the test, as data is collected, the program automatically marks the failure measurement points.

[0028] Parameter settings are as follows Figure 3 As shown: a) Reading failed measurement points: Failed measurement points that have been identified by the data acquisition system's self-test or other methods; b) Set the upper limit of the measurement value based on theoretical results, material properties, sensor range, etc. c) Set the starting load based on the load spectrum analysis results; d) Set the upper limit of the load and the lower limit of the measured value based on the theoretical analysis results; e) Based on experience with data acquisition systems and the accuracy of sensors, determine the number of fitting blocks, the initial detection coefficient, and the lower limit of the coefficient.

[0029] During the experiment, the data acquisition system continuously acquires load and strain (or displacement, etc.) data at each measurement point according to a preset sampling frequency. The program initiates the failure measurement data judgment process, as follows: (a) Before the test begins, mark the failure measurement points that have been identified by the data acquisition system self-test or other means; (b) During the experiment, for each set of data collected, failure judgment is performed cyclically on each data point, including: (1) Determine whether the current measurement point has been marked as a failed measurement point. If "yes", then determine the next measurement point. (2) Determine whether the measured value of the current measurement point exceeds the set upper limit of the measurement value. If "yes", mark it as invalid and then determine the next measurement point; (3) Determine whether the current load is not less than the starting load and not greater than the upper limit of the load. If "no", then determine the next measurement point; (4) Determine whether the number of data in the sliding window meets the set number of fitting blocks. If "no", then determine the next measurement point. (5) Determine whether the measured value of the current measurement point is not less than the set lower limit of the measured value. If "no", then determine the next measurement point. (6) Calculate the correlation coefficient between the measured values ​​and the load within the sliding window; (7) Determine whether the measurement point is being judged for the first time based on the correlation coefficient: If the initial assessment is "yes", then check if the correlation coefficient is greater than the set initial inspection coefficient; if "no", mark it as a failed measurement point. Then check the next measurement point. If the initial judgment is "No", then check if the correlation coefficient is greater than the set lower limit. If "No", mark it as a failed measurement point. Then check the next measurement point; (c) If all measurement points have been determined, wait for the next set of data and repeat step (b).

[0030] Through such real-time dynamic monitoring and multi-condition judgment, failure measurement data can be identified in a timely and accurate manner during the test, and warning prompts can be issued to the test personnel through the program interface, so that the test personnel can take corresponding measures according to the actual situation, such as pausing the test to check the sensor status or adjusting the test plan, thereby ensuring the smooth progress of the static test and the reliability of the test data.

[0031] This invention also provides a device for judging failure measurement data in static strength tests of aircraft structures, to solve the technical problem in the prior art where failure data and abnormal test data are mixed in static strength tests of aircraft structures, resulting in a large workload and low efficiency for measurement personnel in real-time data analysis. The device includes: The marking module is used to mark the failed measurement points that have been identified by the data acquisition system's self-test or other methods before the test begins. The judgment module is used during the test to perform failure data judgment on each data in the data set in a sliding window manner after each set of data is collected. The failure data judgment includes: judging whether the current measurement point has been marked as a failure measurement point. If so, the next measurement point is judged according to the preset judgment parameters. The preset judgment parameters include the upper limit of the measured value, the lower limit of the measured value, the starting load, the upper limit of the load, the number of fitting blocks, the first inspection coefficient, and the lower limit of the coefficient. The starting load is set to the load after the test tare is completed, the upper limit of the load is set to the maximum load of the linear change of the aircraft structure, the number of fitting blocks is set to the number of measurement data in the sliding window, the first inspection coefficient is set to the correlation coefficient threshold value when the measurement point is judged for the first time when the condition is met, and the lower limit of the coefficient is set to the correlation coefficient threshold value when the measurement point is not judged for the first time when the condition is met.

[0032] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned methods for judging the failure measurement data of static strength tests of aircraft structures, thereby solving the technical problem in the prior art where failure data and abnormal test data are mixed in static strength tests of aircraft structures, resulting in a large workload and low efficiency for measurement personnel in real-time data analysis.

[0033] This invention also provides a computer-readable storage medium storing a computer program that executes any of the above-described methods for judging the failure measurement data of static test of aircraft structures. This addresses the technical problem in the prior art where failure data and abnormal test data are mixed in static strength tests of aircraft structures, resulting in a large workload and low efficiency for measurement personnel in real-time data analysis.

[0034] The embodiments provided by this invention realize the automatic identification and intelligent marking of failure data in the static strength test of aircraft structure, which significantly improves the accuracy and processing efficiency of failure measurement data in the judgment process, provides a solid data foundation and technical support for the in-depth analysis of subsequent measurement data, real-time monitoring and early warning of the test process, and further promotes the improvement of the level of intelligent testing.

[0035] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for judging the failure measurement data of an aircraft structure in a static test, characterized in that, The method includes: Before the test begins, mark the failure measurement points that have been identified by the data acquisition system's self-test or other methods; During the experiment, for each set of data collected, a sliding window method was used to cyclically judge each data point in the set as a failed data point. The failed data judgment includes: judging whether the current measurement point has been marked as a failed measurement point. If so, the next measurement point is judged according to the preset judgment parameters. The preset judgment parameters include the upper limit of the measured value, the lower limit of the measured value, the starting load, the upper limit of the load, the number of fitting blocks, the first inspection coefficient, and the lower limit of the coefficient. The starting load is set to the load after the test tare is completed, the upper limit of the load is set to the maximum load of the linear change of the aircraft structure, the number of fitting blocks is set to the number of measurement data in the sliding window, the first inspection coefficient is set to the correlation coefficient threshold value when the measurement point is judged for the first time when the condition is met, and the lower limit of the coefficient is set to the correlation coefficient threshold value when the measurement point is not judged for the first time when the condition is met.

2. The method for judging the failure measurement data of static test of aircraft structure according to claim 1, characterized in that, The correlation coefficient is used to represent the correlation between the measured data and the applied load on the test piece. The expression for the correlation coefficient is: ， Where r is the correlation coefficient, x i For the percentage of load measured step by step, y i For x i The corresponding measured value, where n is the measured value y i The total number.

3. The method for judging the failure measurement data of static test of aircraft structure according to claim 1, characterized in that, The step of determining the next measurement point based on preset judgment parameters includes: Determine whether the measured value of the current measurement point exceeds the set upper limit of the measurement value. If so, mark it as invalid and then determine the next measurement point. Determine if the current load is not less than the starting load and not greater than the upper limit of the load; if not, determine the next measurement point. Determine if the number of data points within the sliding window meets the set number of fitting blocks; if not, proceed to the next measurement point. Determine whether the measured value of the current measurement point is not less than the set lower limit of the measured value; if not, determine the next measurement point. Calculate the correlation coefficient between the measured values ​​and the load within the sliding window; Whether a measurement point is being used for the first time is determined based on the correlation coefficient, and the failure measurement point is determined based on the initial inspection coefficient and the lower limit of the coefficient. Once all measurement points have been evaluated, wait for the next set of data and repeat the process of evaluating failed data.

4. The method for judging the failure measurement data of static test of aircraft structure according to claim 3, characterized in that, The method of determining failure measurement points based on the initial inspection coefficient and the lower limit of the coefficient includes: If the measurement point is being judged for the first time based on the correlation coefficient, then it is determined whether the correlation coefficient is greater than the set initial inspection coefficient. If not, it is marked as a failed measurement point, and then the next measurement point is judged. If the measurement point is not being judged based on the correlation coefficient for the first time, then it is determined whether the correlation coefficient is greater than the set lower limit. If not, it is marked as a failed measurement point, and then the next measurement point is judged.

5. A device for judging failure measurement data in static tests of aircraft structures, used to execute the method for judging failure measurement data in static tests of aircraft structures as described in any one of claims 1-4, characterized in that, The device includes: The marking module is used to mark the failed measurement points that have been identified by the data acquisition system's self-test or other methods before the test begins. The judgment module is used during the test to perform failure data judgment on each data in the data set in a sliding window manner after each set of data is collected. The failure data judgment includes: judging whether the current measurement point has been marked as a failure measurement point. If so, the next measurement point is judged according to the preset judgment parameters. The preset judgment parameters include the upper limit of the measured value, the lower limit of the measured value, the starting load, the upper limit of the load, the number of fitting blocks, the first inspection coefficient, and the lower limit of the coefficient. The starting load is set to the load after the test tare is completed, the upper limit of the load is set to the maximum load of the linear change of the aircraft structure, the number of fitting blocks is set to the number of measurement data in the sliding window, the first inspection coefficient is set to the correlation coefficient threshold value when the measurement point is judged for the first time when the condition is met, and the lower limit of the coefficient is set to the correlation coefficient threshold value when the measurement point is not judged for the first time when the condition is met.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for judging the failure measurement data of the static test of the aircraft structure as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that executes the method for judging the failure measurement data of the aircraft structure static test as described in any one of claims 1 to 4.

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