Aircraft fatigue test damage early warning method based on acoustic emission technology

Abstract

The application belongs to the technical field of aviation strength test, and particularly relates to a kind of aircraft fatigue test damage early warning method based on acoustic emission technology. Including: step one, realize the time synchronization of acoustic emission monitoring data of acoustic emission monitoring system and aircraft fatigue test load spectrum of heterogeneous control loading system;Step two, the aircraft fatigue test load spectrum is divided into load spectrum block, and the acoustic emission monitoring data is cut according to the load spectrum block;Step three, acoustic emission characteristic parameters are extracted from the cut acoustic emission monitoring data;Step four, a damage early warning model is established based on acoustic emission characteristic parameters, and aircraft fatigue test damage early warning is realized according to the damage early warning model. The application can effectively overcome the interference of noise, quickly process a large amount of acoustic emission monitoring data, and perform real-time high-reliability damage early warning through the damage early warning model, effectively solving the problems of large data processing workload and low damage early warning reliability.

Description

Technical Field

[0001] This application belongs to the field of aviation strength testing technology, and specifically relates to a method for early warning of aircraft fatigue test damage based on acoustic emission technology. Background Technology

[0002] In full-scale aircraft fatigue testing, timely damage detection is crucial to the safety of the test specimen and the success of the test. Acoustic emission (AE) technology, as a passive monitoring technique, is widely used in damage monitoring in various fields (such as aerospace, bridges, and rocks) due to its sensitivity to damage initiation and propagation. However, full-scale aircraft ground fatigue testing is characterized by high structural and load spectrum complexity, long test cycles, strong background noise, large data volume, and high requirements for real-time and accuracy of damage early warning. Especially when there are multiple monitoring channels, it poses a significant challenge to damage monitoring during the test.

[0003] Therefore, it is desirable to have a technical solution to overcome or at least mitigate one of the aforementioned defects of the prior art. Summary of the Invention

[0004] The purpose of this application is to provide a method for early warning of damage in aircraft fatigue tests based on acoustic emission technology, in order to solve at least one problem existing in the prior art.

[0005] The technical solution of this application is:

[0006] A method for early warning of aircraft fatigue test damage based on acoustic emission technology, characterized in that it includes:

[0007] Step 1: Achieve temporal synchronization between the acoustic emission monitoring data of the acoustic emission monitoring system and the aircraft fatigue test load spectrum of the heterogeneous control loading system;

[0008] Step 2: Divide the aircraft fatigue test load spectrum into load spectrum blocks, and cut the acoustic emission monitoring data according to the load spectrum blocks;

[0009] Step 3: Extract acoustic emission characteristic parameters from the cut acoustic emission monitoring data;

[0010] Step 4: Establish a damage warning model based on the acoustic emission characteristic parameters, and implement damage warning for aircraft fatigue tests based on the damage warning model.

[0011] In at least one embodiment of this application, step one, which involves synchronizing the acoustic emission monitoring data of the acoustic emission monitoring system with the aircraft fatigue test load spectrum of the heterogeneous control loading system in time, specifically includes:

[0012] The acoustic emission monitoring system obtains the time of the heterogeneous control loading system in the aircraft fatigue test by reading the interface data of the heterogeneous control loading system in real time through the synchronization software of the acoustic emission monitoring system, thereby realizing the synchronization of the acoustic emission monitoring data of the acoustic emission monitoring system with the aircraft fatigue test load spectrum of the heterogeneous control loading system in time.

[0013] In at least one embodiment of this application, step two, which involves dividing the aircraft fatigue test load spectrum into load spectrum blocks and segmenting the acoustic emission monitoring data according to the load spectrum blocks, specifically includes:

[0014] The cyclic history in the load spectrum of the aircraft fatigue test is divided into different types of load spectrum blocks, and the acoustic emission monitoring data is divided into data blocks corresponding to the load spectrum blocks in time, and the data blocks are classified according to the type of the load spectrum block.

[0015] In at least one embodiment of this application, step three, which involves extracting acoustic emission characteristic parameters from the cut acoustic emission monitoring data, specifically includes:

[0016] Acoustic emission feature parameters are extracted from different types of data blocks, including counting feature parameters.

[0017] In at least one embodiment of this application, step four, which involves establishing a damage warning model based on the acoustic emission characteristic parameters and implementing damage warning for aircraft fatigue tests based on the damage warning model, specifically includes:

[0018] S41. Based on the acoustic emission characteristic parameters, determine the baseline values ​​of the counting characteristic parameters of each sensor in the acoustic emission monitoring system under different types of load spectral blocks at the beginning of the experiment.

[0019] S42. Determine the damage warning threshold based on the benchmark value;

[0020] S43. Perform damage monitoring measurements and calculate the relative error between the measured values ​​of each sensor and the reference value;

[0021] S44. Perform a statistical test based on the damage warning threshold and the relative error.

[0022] In at least one embodiment of this application, in S41, the reference value includes the arithmetic mean of the counting feature parameters. and standard deviation i = 1, 2, 3... represents the sensor number, and j = A, B, C... represents the load spectral block type.

[0023] In at least one embodiment of this application, in S42, the damage warning threshold is:

[0024] In at least one embodiment of this application, in step S43, the arithmetic mean of the measured values ​​of each sensor and the counting characteristic parameters is calculated. relative error

[0025] In at least one embodiment of this application, in S44, when It is believed that the acoustic emission monitoring data of the sensor under the corresponding load spectrum block is abnormal.

[0026] In at least one embodiment of this application, step five is also included.

[0027] S51. For sensors that exceed the damage warning threshold in the statistical test, check the test records to confirm whether there is human interference in the monitoring area of ​​the abnormal sensor during the test. If not, proceed to S52.

[0028] S52. Suspend the test and notify the testing personnel to inspect the monitoring area of ​​the abnormal sensor;

[0029] S53. Confirm whether the aircraft status has changed. If yes, return to step S41 to recalculate the baseline value. If no, return to step S43 to continue damage monitoring and measurement.

[0030] The invention has at least the following beneficial technical effects:

[0031] The aircraft fatigue test damage early warning method based on acoustic emission technology proposed in this application can effectively overcome noise interference, rapidly process a large amount of acoustic emission monitoring data, and provide real-time, highly reliable damage early warning through a damage early warning model. This effectively solves the problems of large workload in manual data processing and low reliability of damage early warning. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of load synchronization and data segmentation according to one embodiment of this application;

[0033] Figure 2 This is a flowchart of an aircraft fatigue test damage early warning method based on acoustic emission technology according to one embodiment of this application. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below with reference to the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, embodiments of this application. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0035] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting the scope of protection of this application.

[0036] The following is in conjunction with the appendix Figures 1 to 2 This application will be described in further detail.

[0037] This application provides a method for early warning of aircraft fatigue test damage based on acoustic emission technology, including the following steps:

[0038] Step 1: Achieve temporal synchronization between the acoustic emission monitoring data of the acoustic emission monitoring system and the aircraft fatigue test load spectrum of the heterogeneous control loading system;

[0039] Step 2: Divide the aircraft fatigue test load spectrum into load spectrum blocks, and then cut the acoustic emission monitoring data according to the load spectrum blocks;

[0040] Step 3: Extract acoustic emission characteristic parameters from the acoustic emission monitoring data after cutting;

[0041] Step 4: Establish a damage early warning model based on acoustic emission characteristic parameters, and implement damage early warning for aircraft fatigue tests based on the damage early warning model.

[0042] This application's aircraft fatigue test damage early warning method based on acoustic emission technology first achieves time synchronization between acoustic emission monitoring data and the aircraft fatigue test load spectrum. Aircraft fatigue tests typically involve multiple heterogeneous control and loading systems. By abstracting an intermediate layer independent of these heterogeneous control and loading systems and implementing time synchronization encoding based on this abstract intermediate layer, the differences between the underlying heterogeneous control and loading systems are hidden through this intermediate layer. A unified interface is exposed to the acoustic emission monitoring system. The synchronization software of the acoustic emission monitoring system reads the interface data of the heterogeneous control and loading systems in real time to obtain the time of each system, thereby achieving time synchronization between the acoustic emission monitoring data of the acoustic emission monitoring system and the aircraft fatigue test load spectrum of the heterogeneous control and loading systems.

[0043] This application discloses a damage early warning method for aircraft fatigue tests based on acoustic emission technology, which involves determining load spectrum blocks and data segmentation. The cyclic history in the aircraft fatigue test load spectrum is divided into different types of load spectrum blocks, and the acoustic emission monitoring data is segmented temporally into data blocks corresponding to these load spectrum blocks. These data blocks are then classified according to the type of load spectrum block. Based on the different cyclic histories in the aircraft fatigue test load spectrum, the severity of these histories is assessed, and they are divided into different types of comparison units (load spectrum blocks), ensuring comparability of cyclic types within each major category in the acoustic emission monitoring data. The method for determining the comparison units varies depending on the test and load spectrum; it can be different takeoffs and landings, or even a single loading condition. The principle for segmentation is that the comparison units should not be too large, and the complexity of the comparison unit types should not be too high. After determining the comparison units, the acoustic emission monitoring data is segmented into data blocks corresponding to different types of comparison units, such as... Figure 1 As shown, the segmented data is then categorized according to the type of comparison unit.

[0044] Furthermore, through analysis and research on the data storage structure of acoustic emission detection, the acoustic emission detection data file is quickly read, and then the data is filtered using a structured database. Acoustic emission characteristic parameters are extracted from different types of data blocks after segmentation, including counting characteristic parameters.

[0045] The aircraft fatigue test damage early warning method based on acoustic emission technology of this application, when experiencing the same load spectrum block in aircraft fatigue testing, considers that the monitoring data may be subject to errors due to multiple unknown small independent factors. Therefore, the monitoring data can be assumed to follow a normal distribution, and a damage early warning model can be established based on the statistical distribution of the monitoring data. In the preferred embodiment of this application, step four, establishing a damage early warning model based on acoustic emission characteristic parameters, and implementing aircraft fatigue test damage early warning based on the damage early warning model, specifically involves:

[0046] S41. Based on acoustic emission characteristic parameters, determine the baseline values ​​of the counting characteristic parameters of each sensor in the acoustic emission monitoring system under different types of load spectral blocks at the beginning of the experiment.

[0047] S42. Determine the damage warning threshold based on the benchmark value;

[0048] S43. Perform damage monitoring measurements and calculate the relative error between the measured values ​​of each sensor and the reference values;

[0049] S44. Perform statistical tests based on the damage warning threshold and relative error.

[0050] This application discloses a damage early warning method for aircraft fatigue testing based on acoustic emission technology. The method determines the baseline values ​​of each sensor under different load spectrum blocks. Monitoring and measurement are performed at the initial stage of the test to obtain monitoring data for each sensor under various load spectrum blocks. It is necessary to ensure that each sensor has at least 30 data samples for each load spectrum block. Then, acoustic emission characteristic parameters are extracted from each data block, and the arithmetic mean of the acoustic emission characteristic parameters accumulated by each sensor under the corresponding load spectrum block is calculated sequentially. and standard deviation (i = 1, 2, 3..., representing sensor numbers; j = A, B, C..., representing load spectral block types), serving as the reference value for the sensor under the corresponding load spectral block. In this embodiment, based on application experience and statistical distribution confidence probability, the following values ​​are used: This serves as a damage warning threshold. Furthermore, immediately after completing a full load spectrum block, data segmentation is performed to extract the cumulative count acoustic emission characteristic parameters of each sensor within that load spectrum block, and the arithmetic mean of the measured values ​​and count characteristic parameters of each sensor is calculated. relative error In statistical tests, if This indicates that the acoustic emission monitoring data of the sensor under the corresponding load spectrum block is abnormal.

[0051] In a preferred embodiment of this application, step five is also included.

[0052] S51. For sensors that exceed the damage warning threshold in the statistical test, check the test records to confirm whether there is human interference in the monitoring area of ​​the abnormal sensor during the test. If not, proceed to S52.

[0053] S52. Suspend the test and notify the testing personnel to inspect the monitoring area of ​​the abnormal sensor;

[0054] S53. Confirm whether the aircraft status has changed. If yes, return to step S41 to recalculate the baseline value. If no, return to step S43 to continue damage monitoring and measurement.

[0055] This application presents a damage early warning method for aircraft fatigue testing based on acoustic emission technology. This method correlates acoustic emission monitoring data with the loaded load spectrum, making acoustic emission monitoring data under the same spectral block comparable and effectively overcoming the problem of strong noise interference in aircraft fatigue testing. It also significantly reduces the workload of technical personnel. Furthermore, this application establishes a damage early warning model based on the statistical distribution of acoustic emission characteristic parameters. By obtaining baseline values ​​and damage early warning thresholds from data samples at the beginning of the test, it provides a theoretical basis for damage early warning during the test, thereby greatly improving the reliability of damage early warning.

[0056] 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 early warning of aircraft fatigue test damage based on acoustic emission technology, characterized in that, include: Step 1: Achieve temporal synchronization between the acoustic emission monitoring data of the acoustic emission monitoring system and the aircraft fatigue test load spectrum of the heterogeneous control loading system; Step 2: Divide the aircraft fatigue test load spectrum into load spectrum blocks, and segment the acoustic emission monitoring data according to the load spectrum blocks, specifically as follows: The cyclic history in the load spectrum of the aircraft fatigue test is divided into different types of load spectrum blocks, and the acoustic emission monitoring data is divided into data blocks corresponding to the load spectrum blocks in time, and the data blocks are classified according to the type of the load spectrum block; Step 3: Extract acoustic emission characteristic parameters from the cut acoustic emission monitoring data, specifically as follows: Acoustic emission feature parameters are extracted from different types of data blocks, including counting feature parameters; Step 4: Establish a damage early warning model based on the acoustic emission characteristic parameters, and implement damage early warning for aircraft fatigue tests based on the damage early warning model, specifically as follows: S41. Based on the acoustic emission characteristic parameters, determine the baseline values ​​of the counting characteristic parameters of each sensor in the acoustic emission monitoring system under different types of load spectral blocks at the beginning of the experiment. S42. Determine the damage warning threshold based on the benchmark value; S43. Perform damage monitoring measurements and calculate the relative error between the measured values ​​of each sensor and the reference value; S44. Perform a statistical test based on the damage warning threshold and the relative error.

2. The aircraft fatigue test damage early warning method based on acoustic emission technology according to claim 1, characterized in that, In step one, the synchronization of acoustic emission monitoring data from the acoustic emission monitoring system with the aircraft fatigue test load spectrum from the heterogeneous control loading system in time is specifically achieved as follows: The acoustic emission monitoring system obtains the time of the heterogeneous control loading system in the aircraft fatigue test by reading the interface data of the heterogeneous control loading system in real time through the synchronization software of the acoustic emission monitoring system, thereby realizing the synchronization of the acoustic emission monitoring data of the acoustic emission monitoring system with the aircraft fatigue test load spectrum of the heterogeneous control loading system in time.

3. The aircraft fatigue test damage early warning method based on acoustic emission technology according to claim 2, characterized in that, In S41, the reference value includes the arithmetic mean of the counting feature parameters. and standard deviation , Indicates the sensor number, Indicates the load spectral block type.

4. The aircraft fatigue test damage early warning method based on acoustic emission technology according to claim 3, characterized in that, In S42, the damage warning threshold is 3. .

5. The aircraft fatigue test damage early warning method based on acoustic emission technology according to claim 4, characterized in that, In S43, the arithmetic mean of the measured values ​​of each sensor and the counting characteristic parameters is calculated. relative error .

6. The aircraft fatigue test damage early warning method based on acoustic emission technology according to claim 5, characterized in that, In S44, when It is believed that the acoustic emission monitoring data of the sensor under the corresponding load spectrum block is abnormal.

7. The aircraft fatigue test damage early warning method based on acoustic emission technology according to claim 6, characterized in that, It also includes step five, S51. For sensors that exceed the damage warning threshold in the statistical test, check the test records to confirm whether there is human interference in the monitoring area of ​​the abnormal sensor during the test. If not, proceed to S52. S52. Suspend the test and notify the testing personnel to inspect the monitoring area of ​​the abnormal sensor; S53. Confirm whether the aircraft status has changed. If yes, return to step S41 to recalculate the baseline value. If no, return to step S43 to continue damage monitoring and measurement.

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