Aviation anti-drag film weather resistance self-adaptive evaluation method and system

Abstract

The invention relates to the technical field of weather resistance evaluation, and provides an aviation anti-drag film weather resistance self-adaptive evaluation method and system, and the method comprises the steps: analyzing an application environment variable, and extracting an extreme value, a change frequency, and a duration characteristic; searching and constructing a basic environment, a mean value environment and an extreme value environment according to the characteristics; searching and matching in a preset test parameter library by using the characteristics of the environments as indexes to obtain a test evaluation value; and according to an application environment target, adaptively configuring an accumulative time sequence relationship of each environment, performing time sequence fusion evaluation on the test evaluation value, and generating a comprehensive weather resistance evaluation result. The technical problem that in the prior art, the weather resistance test result is insufficient in accuracy due to the fact that environment change characteristics of the aviation anti-drag film are difficult to accurately capture in a complex and changeable environment is solved, and the purposes of automatically adapting to changes of various application environment conditions and improving the weather resistance test accuracy by analyzing the environment variable characteristics are achieved. And the precision and applicability of the weather resistance test are improved.

Description

Technical Field

[0001] The present application relates to the technical field of weather resistance evaluation, and in particular to a method and system for adaptively evaluating the weather resistance of aviation drag reduction films. Background Art

[0002] As an important material on the surface of aircraft, aviation drag reduction film is widely used to improve the aerodynamic performance of aircraft, reduce air resistance and save fuel. However, in the long-term actual use process, aviation drag reduction film is faced with complex and changeable environmental conditions, such as extreme temperature changes, strong ultraviolet radiation, humidity fluctuations, friction and impact stress, etc. These environmental factors will accelerate the aging and performance degradation of the drag reduction film, thereby affecting its service life and drag reduction effect. Therefore, how to accurately evaluate the weather resistance of aviation drag reduction film under different environmental conditions has become one of the key issues in improving the design and use performance of drag reduction film. Most of the existing weather resistance evaluation methods rely on single environmental factor tests under laboratory conditions, and fail to fully consider the interactive effects of various environmental variables in the actual application environment, and cannot fully reflect the weather resistance performance of aviation drag reduction film in actual use. At the same time, due to the complex spatiotemporal distribution characteristics of the influence of different environmental conditions on drag reduction film, it is difficult for existing technologies to adaptively adjust test parameters to adapt to these complex changes, resulting in insufficient accuracy of the evaluation results, and it is difficult to provide an effective basis for the design optimization and material selection of drag reduction film. Summary of the invention

[0003] The present application provides an adaptive weather resistance evaluation method and system for aviation drag reduction films, aiming to solve the technical problem in the prior art that it is difficult to accurately capture environmental change characteristics of aviation drag reduction films in complex and changeable environments, resulting in insufficient accuracy of weather resistance test results.

[0004] In view of the above problems, the present application provides a method and system for adaptively evaluating the weather resistance of aviation drag reduction films.

[0005] The first aspect disclosed in the present application provides a method for adaptively evaluating the weather resistance of an aviation drag reduction film, the method comprising: parsing application environment variables, extracting environmental change characteristics, including extreme value characteristics, change frequency characteristics, and duration characteristics; performing combined search using the extreme value characteristics, change frequency characteristics, and duration characteristics of the composite application environment variables, respectively, to construct a multi-level weather resistance evaluation target, the multi-level weather resistance evaluation target comprising a basic environment, a mean environment, and an extreme environment; using the environmental change characteristics of the basic environment, the mean environment, and the extreme environment as indexes, respectively, to perform search and match in a preset test parameter library to obtain test evaluation values, the test evaluation values ​​being test evaluation results obtained for each level of weather resistance evaluation targets; according to the application environment target, adaptively configuring the cumulative time series relationship of the basic environment, the mean environment, and the extreme environment, performing time series fusion evaluation on the test evaluation values, and generating a comprehensive weather resistance evaluation result.

[0006] Another aspect disclosed in the present application provides an adaptive weather resistance evaluation system for aviation drag reduction films, the system comprising: an environmental variable parsing module: the environmental variable parsing module is used to parse application environment variables and extract environmental change characteristics, including extreme value characteristics, change frequency characteristics, and duration characteristics; a combined search module: the combined search module is used to perform combined searches with the extreme value characteristics, change frequency characteristics, and duration characteristics of the composite application environment variables, respectively, to construct a multi-level weather resistance evaluation target, the multi-level weather resistance evaluation target comprising a basic environment, a mean environment, and an extreme environment; a search and matching module: the search and matching module is used to use the environmental change characteristics of the basic environment, the mean environment, and the extreme environment as indexes, to search and match in a preset test parameter library, and obtain test evaluation values, the test evaluation values ​​being test evaluation results obtained for each level of weather resistance evaluation targets; a time series fusion evaluation module: the time series fusion evaluation module is used to adaptively configure the cumulative time series relationship of the basic environment, the mean environment, and the extreme environment according to the application environment target, perform time series fusion evaluation on the test evaluation values, and generate a comprehensive weather resistance evaluation result.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The above-mentioned adaptive weathering evaluation method for aviation drag reduction film analyzes the application environment variables and extracts environmental change characteristics, such as extreme value characteristics, change frequency characteristics and duration characteristics, to fully understand the environmental impact faced by aviation drag reduction film. Subsequently, these characteristics are combined and searched to construct multi-level weathering evaluation targets, including basic environment, mean environment and extreme environment. After that, these environmental characteristics are used as indexes to match in the preset test parameter library to obtain the test evaluation values ​​of each level to ensure that the evaluation results can reflect the actual performance under different environmental conditions. Then, according to the specific goals of the application environment, the cumulative time series relationship of the basic environment, mean environment and extreme environment is adaptively configured, and the test evaluation values ​​are evaluated by time series fusion to generate a comprehensive weathering evaluation result. Through this method, the evaluation accuracy and adaptability of the weathering resistance of aviation drag reduction film can be effectively improved, providing a more reliable basis for its practical application in complex environments and ensuring the performance stability of the drag reduction film.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 The figure is a flow chart of a method for adaptively evaluating weather resistance of an aviation drag reduction film in one embodiment.

[0011] Figure 2 The following is an architecture diagram of an adaptive weather resistance assessment system for aviation drag reduction films in one embodiment.

[0012] Explanation of the accompanying drawings: environment variable analysis module 1, combination search module 2, search and matching module 3, time series fusion evaluation module 4. DETAILED DESCRIPTION

[0013] The embodiments of the present application provide a method and system for adaptively evaluating the weather resistance of aviation drag reduction films, thereby solving the technical problem in the prior art that it is difficult to accurately capture environmental change characteristics of aviation drag reduction films in complex and changeable environments, resulting in insufficient accuracy of weather resistance test results.

[0014] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0015] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0016] Embodiment 1, as Figure 1 As shown, the present application provides a method for adaptively evaluating weather resistance of aviation drag reduction films, the method comprising: Analyze application environment variables and extract environmental change characteristics, including extreme value characteristics, change frequency characteristics, and duration characteristics.

[0017] In the embodiment of the present application, the system terminal uses the core influencing environmental characteristics as the target variable, and analyzes the change characteristics of the application environmental variables to obtain various environmental change characteristics related to the use of aviation drag reduction film. These environmental change characteristics include extreme value characteristics (such as maximum and minimum temperatures), change frequency characteristics (the frequency of environmental condition changes), and duration characteristics (the duration of these conditions over a certain period of time). By extracting these characteristics, the potential impact of the environment on the performance of the drag reduction film can be fully understood, thereby providing basic data support for subsequent weather resistance evaluation.

[0018] Further, the present application provides the analytical application environment variables, extracting environment change characteristics, including extreme value characteristics, change frequency characteristics, and duration characteristics, including: The core influencing environmental characteristics of the drag reduction film are obtained, wherein the core influencing environmental characteristics include temperature, ultraviolet intensity, friction impact stress, and humidity. The core influencing environmental characteristics are used as target variables, and the change characteristics of the application environmental variables are analyzed to obtain the change amount of each target variable and its change trend. The gradient distribution is determined according to the change amount, and the extreme value of the change amount is obtained based on the gradient distribution. The extreme value characteristics are obtained in combination with the maximum and minimum values ​​of the application environmental variables. The change frequency characteristics and the duration characteristics of the change amount are calculated according to the change amount and its change trend.

[0019] Preferably, in order to extract the characteristics of environmental changes, the system terminal first obtains the core environmental characteristics affecting the drag reduction film, which include but are not limited to temperature, ultraviolet intensity, friction impact stress, and humidity. These environmental characteristics will be used as target variables to participate in the subsequent environmental variable analysis process. Subsequently, for each target variable, the variable data corresponding to the target variable is parsed from the monitoring equipment such as sensors, and their changes in different time periods are analyzed to obtain the change amount (for example, the temperature rises from 20°C to 30°C) and the change trend (such as whether the temperature is gradually rising or falling) of each target variable. After obtaining the change amount, the system terminal determines the change speed and direction by analyzing the difference between the change amount at each time point and the previous time point, and calculates the gradient distribution of the change amount. Based on the calculated gradient distribution, the extreme value points of the change amount are identified. These extreme value points refer to the positions where the change amount reaches the maximum or minimum value, reflecting the extreme conditions of the impact of environmental factors on the performance of the drag reduction film. After that, the maximum and minimum values ​​of the application environment variables are collected, such as the highest and lowest temperatures, ultraviolet intensity, etc. These values ​​combined with the extreme values ​​of the change amount can provide a more comprehensive environmental impact assessment. The system terminal determines the extreme value characteristics by comparing the extreme value of the change with the maximum and minimum values ​​of the environmental variables. These characteristics can describe the degree of impact that the drag reduction film performance may suffer under different extreme environmental conditions. For example, if the extreme value of the change exceeds the maximum value of the environmental variable, it is marked as exceeding the limit, indicating that it may cause greater damage to the drag reduction film. In addition, the system terminal combines the timeline of the aircraft flight in the aviation application environment and the spatial line of the environmental variables to perform three-dimensional spatial fitting on the change and its change trend, calculate the change frequency characteristics of the periodic characteristics and volatility characteristics, and the duration characteristics of the change, which provides a reliable basis for evaluating the weather resistance of the drag reduction film.

[0020] Furthermore, the present application provides a method for calculating the change frequency feature and the duration feature of the change amount according to the change amount and its change trend, including: Collect the data of the change of the target variable over time and construct the change trend; obtain the time line of the aircraft flight in the aviation application environment and the space line of the environmental variable, construct three-dimensional space coordinates, fit the change and its change trend to the three-dimensional space coordinates, and analyze the timeline periodic change and space height periodic change of the target variable; calculate the change frequency characteristics of the periodic characteristics and the duration characteristics of the change according to the timeline periodic change and space height periodic change; set the fluctuation characteristics except the timeline periodic change and space height periodic change as the fluctuation characteristics, and calculate the change frequency characteristics and the duration characteristics of the change.

[0021] Optionally, during the flight of the aircraft, the system terminal collects data on the change of the target variable over time. These data need to be recorded at different time points and flight altitudes to obtain comprehensive environmental information. Then, the change of the target variable is arranged in chronological order to construct the change trend of the target variable to show the trend of the target variable over time. Subsequently, the system terminal obtains the time line of the aircraft flight in the aviation application environment and the spatial line of the environmental variable, and constructs a three-dimensional space coordinate. The X-axis of this three-dimensional space coordinate represents the time line, reflecting the time evolution during the aircraft flight. The Y-axis represents the altitude, recording the altitude change of the aircraft in different flight stages. The Z-axis represents the change of environmental variables, such as temperature, humidity, etc. After that, the data points in the change trend of the obtained target variable are mapped to this three-dimensional coordinate system, and each data point corresponds to a specific time, altitude and environmental variable value. Then, the mapped data points are fitted by interpolation to generate a smooth surface, reflecting the change trend of the target variable over time and altitude. Among them, the value inserted by the interpolation method is the average value of multiple adjacent data points. Then, spectrum analysis (such as fast Fourier transform) or autocorrelation analysis is used to identify the periodic changes of the change on the time axis. Observe the periodic trend of the change over time and determine the length and amplitude of the cycle. Similarly, analyze the changes on the altitude axis, check the periodic changes of the target variable under different altitude conditions, and identify the periodic characteristics at different flight altitudes. Then, according to the cycles identified on the timeline and altitude axis, calculate the change frequency characteristics, which represent the number of periodic changes per unit time, and calculate the duration of each cycle, that is, the length of time the cycle takes from the beginning to the end, to determine the duration characteristics of the change. Taking the fast Fourier transform (FFT) as an example, the system terminal performs detrending processing on the change data of each target variable fitting, that is, subtracting the mean of the change of the target variable from each data point to eliminate the influence of the long-term trend and focus on the periodic change. Then apply the fast Fourier transform to the detrended time series data, convert it to the frequency domain, and obtain the spectrum. Subsequently, identify the main frequency of the timeline periodic change in the spectrum, that is, the frequency with the largest amplitude, and then invert this main frequency to obtain the main period corresponding to this main frequency. After that, use the same method to analyze the periodic change of the spatial height to obtain the main frequency and main period of the periodic change of the spatial height. Then, the main frequency of the timeline periodic change and the main frequency of the space height periodic change are added to the change frequency feature to obtain the change frequency feature of the periodic feature, and then the main period of the timeline periodic change and the main period of the space height periodic change are added to the duration feature to obtain the duration feature of the change. In addition to the periodic feature, the system terminal also identifies other random fluctuations and sets them as fluctuation features, such as the frequency and amplitude of sudden events, which may include instantaneous sharp rise or fall in temperature, rapid changes in humidity, etc.The system terminal calculates the change frequency characteristics of the volatility characteristics and the duration characteristics of the change amount by using the same method as above to quantify the random changes of the environmental variables.

[0022] The extreme value characteristics, change frequency characteristics, and duration characteristics of the composite application environment variables are respectively combined and searched to construct a multi-level weather resistance evaluation target, which includes a basic environment, a mean environment, and an extreme value environment.

[0023] In one embodiment, the system terminal uses the extreme value characteristics, change frequency characteristics, and duration characteristics of the composite application environment variables to perform multiple feature segmentations on the data interval determined according to the maximum and minimum values ​​of the application environment variables, and constructs a multi-level weather resistance evaluation target. This evaluation target is divided into three levels, namely, the basic environment, the mean environment, and the extreme environment. Among them, the basic environment focuses on the weather resistance performance under normal conditions and evaluates the basic adaptability of the drag reduction film under standard conditions. The mean environment comprehensively considers the average state of multiple environmental factors and evaluates the weather resistance performance under typical or common environmental conditions. Extreme environment: Analyze the weather resistance under extreme environmental conditions, such as the performance of the drag reduction film under high temperature, low temperature, or strong ultraviolet radiation. Through this hierarchical evaluation target construction method, the weather resistance of aviation drag reduction films in different application environments can be evaluated more comprehensively and accurately, providing detailed data support for subsequent evaluation results.

[0024] Furthermore, the present application provides a method for constructing a multi-level weather resistance evaluation target by combining and searching the extreme value features, change frequency features, and duration features of the composite application environment variables, including: According to the extreme value features, the maximum and minimum values ​​of the application environment variables, as well as the maximum and minimum values ​​of the variation, are obtained; according to the maximum and minimum values ​​of the application environment variables, the data interval is obtained, and according to the maximum value of the variation, and the segmentation and proportion relationship of the difference between the maximum and minimum values, the segmentation thresholds of the basic environment, the mean environment, and the extreme environment are determined; according to the proportion relationship of the change frequency feature and the duration feature, mean segmentation is performed to determine the segmentation relationship of the change frequency feature and the segmentation relationship of the duration feature.

[0025] Optionally, the system terminal uses the maximum and minimum values ​​of the application environment variables and the maximum and minimum values ​​of the change amount to be extracted from the extreme value features. These extreme values ​​provide an important reference benchmark for subsequent evaluation. Subsequently, a data interval is determined based on the maximum and minimum values ​​of the application environment variables, which reflects the range of possible changes in the environmental variables. At the same time, by analyzing the maximum value of the change amount and the difference between its maximum and minimum values, the segmentation ratio relationship of different environmental states is calculated, thereby determining the segmentation thresholds of the basic environment, the mean environment, and the extreme environment. These thresholds provide specific boundaries for subsequent multi-level weather resistance evaluation. After that, the system terminal calculates the mean (μ) and standard deviation (σ) of the data in the change frequency feature and the duration feature, and uses the calculated mean and standard deviation as the ratio relationship of the change frequency feature and the duration feature. Then, segmentation is performed based on the mean and standard deviation in this ratio relationship, that is, μ-kσ to μ+kσ is used as the basic interval, μ+kσ to μ+2kσ is used as the mean interval, and greater than μ+2kσ is used as the extreme interval. Then, the system terminal determines the segmentation relationship of the change frequency characteristics according to the three intervals divided by the change frequency characteristics, and determines the segmentation relationship of the change frequency characteristics according to the three intervals divided by the duration characteristics. This analysis process helps to understand the dynamics of changes under different environmental conditions in more detail and provide support for the accuracy of weather resistance evaluation.

[0026] The segmentation threshold, the feature segmentation relationship of the change frequency, and the segmentation relationship of the duration feature are normalized to determine the normalized segmentation condition; the stratified weights of the extreme value feature, the change frequency feature, and the duration feature are configured, and the normalized segmentation condition is integrated using the stratified weights to determine the hierarchical division threshold, which includes the basic environment, the mean environment, and the extreme environment division thresholds respectively; the hierarchical division threshold is used to perform composite variable feature segmentation on the application environment variables to construct the multi-level weather resistance evaluation target.

[0027] Optionally, the system terminal uses the maximum-minimum method to normalize the obtained segmentation threshold, the segmentation relationship of the change frequency feature, and the segmentation relationship of the duration feature, standardizes the data of different features so that their numerical ranges are all within [0,1], and determines the normalized segmentation conditions for subsequent processing and comparison. The purpose of normalization is to eliminate the numerical differences between different features so that they can be analyzed on the same dimension. Subsequently, different weights are configured for extreme value features, change frequency features, and duration features according to the evaluation requirements. The hierarchical weight represents the importance of each feature in the weather resistance evaluation. For some application scenarios, extreme value features (such as extreme temperatures in the environment) may be more important than change frequency or duration features, so they are given a higher weight. The configured hierarchical weights are then used to fuse the segmentation conditions after normalization. Through this fusion operation, the final hierarchical division thresholds are calculated, including the basic environment, mean environment, and extreme environment division thresholds, which determine the basis for dividing the evaluation target into different levels. Afterwards, the system terminal performs composite feature extraction on the collected application environment variables. Each variable involves multi-dimensional features, including extreme value features, change frequency features, duration features, etc. Composite feature extraction refers to combining these different dimensional features together for subsequent hierarchical division. Then use the determined hierarchical division threshold to segment the data of the application environment variables by level. Each composite feature will be classified according to its performance at different levels (basic environment, mean environment or extreme environment). Through this segmentation method, each application environment variable can be assigned its corresponding environmental level. According to the above segmentation results, all application environment variables are integrated to construct multi-level weather resistance evaluation targets. Each evaluation target will cover basic weather resistance evaluation targets, mean weather resistance evaluation targets, and extreme weather resistance evaluation targets. The weather resistance evaluation targets at each level can help comprehensively evaluate the performance of the drag reduction film in different environments and ensure the reliability of the drag reduction film under various conditions.

[0028] Furthermore, the present application provides for adjusting and resetting the stratification weights, including: Establish an influence relationship between the periodic characteristics and the multi-level weather resistance evaluation target, and configure the influence weight of the periodic characteristics in the multi-level weather resistance evaluation target; search for the periodic characteristics in the multi-level weather resistance evaluation target, fit the influence weight to the hierarchical weight, and adjust and reset the hierarchical weight.

[0029] Optionally, the system terminal first clarifies the degree of influence of the periodic characteristics on the weather resistance evaluation targets at different levels. The key to this step is to define the influence weights of each level. Under the basic environment, the environmental fluctuations are small, and the periodic changes have little effect on the weather resistance of the drag reduction film, so the influence weight of the periodic characteristics is also relatively low. Generally, this means that the periodic changes in the base layer account for a small proportion. The mean environment is a medium fluctuation state between the normal and extreme environments. The periodic changes have a relatively moderate impact in the mean environment, so the weight of the periodic characteristics will be correspondingly higher than the base layer, but lower than the extreme layer. In extreme environments (such as extremely high or low temperature conditions), the periodic changes have a very significant impact on the weather resistance of the drag reduction film. Therefore, the influence weight of the periodic characteristics at this level will be very large, and the influence ratio will be the highest. The system terminal adds the periodic change characteristics to the weather resistance evaluation of different levels respectively, and assigns corresponding influence weights to each level. For example, the influence weight of the basic environmental periodic characteristics is 0.2, the influence weight of the mean environmental periodic characteristics is 0.4, and the influence weight of the extreme environmental periodic characteristics is 0.8. The configuration of these weights should be adjusted according to the actual application scenario to ensure that the influence of the periodic characteristics on the weather resistance of the drag reduction film is reasonably distributed at each level. Subsequently, the system terminal searches for the periodic characteristics in the multi-level weather resistance evaluation targets to find the periodic characteristics in each weather resistance target and its corresponding hierarchical weights. The newly obtained influence weights are then used to fit and replace the corresponding hierarchical weights, and the aforementioned multi-level weather resistance evaluation targets are reconstructed based on these adjusted hierarchical weights, so that the weather resistance evaluation process is more accurate and can reflect the periodic influences in different environmental levels.

[0030] Furthermore, the present application provides a method for determining the segmentation thresholds of the basic environment, the average environment, and the extreme environment according to the maximum value of the variation and the segmentation ratio relationship between the maximum value and the minimum value, including: The maximum value of the variation is used as the segmentation threshold of the extreme environment; the median of the variation is calculated according to the difference between the maximum and minimum values ​​of the variation; the median of the variation is used as the segmentation node of the basic environment and the mean environment to determine the segmentation threshold of the basic environment and the mean environment.

[0031] Optionally, the system terminal directly uses the maximum value of the change in the environmental variable as the segmentation threshold of the extreme environment. This means that when the change in the environmental variable reaches or exceeds this maximum value, the environment is considered to be under extreme environmental conditions, which will be used to evaluate the weather resistance performance of the drag reduction film under extreme conditions. Subsequently, the overall range of change is obtained by calculating the difference between the maximum and minimum values ​​of the change. In order to further divide the basic environment and the mean environment, the midpoint of this difference, that is, the median of change, is used. The median of change reflects a natural dividing point of the change between the basic environment and the mean environment. Afterwards, the calculated median of change is used as the segmentation node between the basic environment and the mean environment. The segmentation threshold of the basic environment will be defined as a range of changes less than or equal to the median, indicating a more conventional environmental fluctuation. The segmentation threshold of the mean environment is between the median and the maximum value, representing a fluctuation that is larger than the basic environment but does not reach the extreme value. In this way, the environmental conditions can be effectively divided into the basic environment, the mean environment, and the extreme environment. Each level corresponds to a different range of changes, ensuring that the weather resistance evaluation target can accurately reflect the performance of the material under various environmental conditions.

[0032] The environmental change characteristics of the basic environment, the average environment, and the extreme environment are respectively used as indexes to search and match in a preset test parameter library to obtain test evaluation values, which are test evaluation results obtained for each level of weather resistance evaluation targets.

[0033] In one embodiment, the system terminal constructs a preset test parameter library based on a large amount of experimental data. The database contains characteristic data (such as temperature, humidity, ultraviolet intensity, friction stress, etc.) under different environmental conditions and performance evaluation results of aviation drag reduction films corresponding to these environmental characteristics. These evaluation results may include durability and anti-aging ability of drag reduction films. Among them, the structure example of the parameter library is: environmental feature 1 (temperature, humidity, etc.) → performance evaluation result A; environmental feature 2 (temperature, humidity, etc.) → performance evaluation result B. Subsequently, the environmental change characteristics of the basic environment, mean environment and extreme environment obtained by analysis are used as search indexes and matched in the preset test parameter library. The search process can be similar to the database query method, comparing each environmental feature with the corresponding experimental results in the database to find matching test data. After each search, the system terminal will obtain the corresponding test evaluation value from the test parameter library. These test evaluation values ​​are obtained based on the data in the preset test parameter library, and each evaluation value reflects the weather resistance performance of the drag reduction film under specific environmental conditions. After searching and matching, the system terminal obtains the test evaluation values ​​corresponding to the basic environment, mean environment and extreme environment respectively. These evaluation values ​​represent the weather resistance of the drag-reducing film under different environmental conditions, helping system terminals to comprehensively evaluate the performance of the drag-reducing film in multi-level environments.

[0034] According to the application environment target, the cumulative time series relationship of the basic environment, the average environment, and the extreme environment is adaptively configured, and the test evaluation values ​​are evaluated by time series fusion to generate a comprehensive weather resistance evaluation result.

[0035] In one embodiment, the system terminal performs time-series configuration and splicing of the characteristics of the basic environment, the average environment, and the extreme environment according to the actual application environment target. Subsequently, the cumulative function is used to perform test evaluation value fusion calculation on the spliced ​​environment to generate a comprehensive weather resistance evaluation result. This result provides a global evaluation of the overall weather resistance and reflects the performance of the drag reduction film during long-term use.

[0036] Furthermore, the present application provides the method of adaptively configuring the cumulative time series relationship of the basic environment, the average environment, and the extreme environment according to the application environment target, performing time series fusion evaluation on the test evaluation value, and generating a comprehensive weather resistance evaluation result, including: According to the application environment target, matching is performed according to the basic environment, mean environment, and extreme environment to obtain a matching environment, where the matching environment is one or more of the basic environment, mean environment, and extreme environment; the matching environments are spliced ​​in time series according to the target time series relationship, and a cumulative function is used to perform a fusion calculation of the test evaluation values ​​to obtain the comprehensive weather resistance evaluation result, wherein when the matching environment is the basic environment or the mean environment, a weighted average algorithm is used for fusion calculation, and when the matching environment is the extreme environment, an exponential decay model is used for fusion calculation.

[0037] Preferably, the system terminal matches according to the application environment target (such as a specific flight mission or long-term use conditions), divides the environment into a basic environment, a mean environment and an extreme environment, and selects the combination that best matches the actual environment, which may be one or more of the basic environment, the mean environment and the extreme environment. For example, if the flight environment is in normal conditions most of the time, it will be matched to the basic environment; if extreme high temperatures occur in certain time periods, the extreme environment will also be included in the matching range. Subsequently, the matched environment types are spliced ​​according to the target timing relationship in the actual application, that is, they are spliced ​​in the order in which various environments appear, so as to reflect the environmental fluctuations of the drag reduction film in actual use. Afterwards, different cumulative functions are used for fusion calculation according to the matched environment type, wherein the cumulative function includes a weighted average algorithm and an exponential decay model. When the matching environment is a basic environment or a mean environment, a weighted average algorithm is used for fusion calculation. The weighted average algorithm can perform weighted calculation on the test evaluation values ​​under each environmental condition according to the time series weight of the environment, and fuse the test evaluation values ​​of the basic environment, the mean environment and the extreme environment together to generate a comprehensive evaluation result of weather resistance. When the matching environment is an extreme environment, the exponential decay model will be used for fusion calculation to generate a comprehensive evaluation result of weather resistance. This model is a mathematical model with a built-in exponential decay function, which can reflect the degree of accelerated impact of the environment on weather resistance under extreme conditions. The exponential decay function is as follows: ;in, represents the test evaluation value at time t, is the initial test evaluation value, k is the exponential decay coefficient, which reflects the speed of the extreme environment's impact on weather resistance, and t is time, which represents the duration of the extreme environment. By matching the basic environment, average environment, and extreme environment, and using different cumulative functions (weighted average algorithm and exponential decay model) for fusion calculation according to their time series relationship, the system terminal can more accurately evaluate the weather resistance performance of the drag reduction film under various environmental conditions.

[0038] In summary, the embodiments of the present application have at least the following technical effects: The embodiment of the present application extracts extreme value features, change frequency features and duration features by parsing the application environment variables, and constructs a multi-level weather resistance evaluation target based on these features, including the basic environment, the mean environment and the extreme environment. Subsequently, the preset test parameter library is used to match the environmental features of different levels to obtain the corresponding test evaluation values. According to the actual goals of the application environment, the cumulative time series relationship of each level of environment is dynamically configured, and the test evaluation values ​​are fused and calculated by weighted average or exponential decay model to obtain the comprehensive evaluation results of weather resistance. In addition, by configuring the weights of periodic features, adjusting the stratification weights, and finally performing a detailed evaluation based on the segmentation threshold of environmental features to ensure the accuracy of the weather resistance evaluation. These technical effects jointly solve the technical problem that it is difficult to accurately capture the environmental change characteristics of aviation drag reduction films in complex and changeable environments in the prior art, resulting in insufficient accuracy of weather resistance test results, and realize the effect of automatically adapting to the changes in various application environment conditions by parsing the characteristics of environmental variables, and improving the accuracy and applicability of weather resistance tests.

[0039] Embodiment 2, based on the same inventive concept as the method for adaptively evaluating weather resistance of aviation drag reduction film in the above embodiment, Figure 2 As shown, the present application provides an adaptive weather resistance evaluation system for aviation drag reduction film, and the system includes: an environmental variable parsing module 1: the environmental variable parsing module 1 is used to parse the application environment variables and extract environmental change characteristics, including extreme value characteristics, change frequency characteristics, and duration characteristics; a combined search module 2: the combined search module 2 is used to perform combined searches with the extreme value characteristics, change frequency characteristics, and duration characteristics of the composite application environment variables, respectively, to construct a multi-level weather resistance evaluation target, and the multi-level weather resistance evaluation target includes a basic environment, a mean environment, and an extreme environment; a search matching module 3: the search matching module 3 is used to use the environmental change characteristics of the basic environment, the mean environment, and the extreme environment as indexes, search and match in a preset test parameter library, and obtain a test evaluation value, and the test evaluation value is a test evaluation result obtained for each level of weather resistance evaluation target; a time series fusion evaluation module 4: the time series fusion evaluation module 4 is used to adaptively configure the cumulative time series relationship of the basic environment, the mean environment, and the extreme environment according to the application environment target, perform time series fusion evaluation on the test evaluation value, and generate a comprehensive weather resistance evaluation result.

[0040] Furthermore, the environment variable parsing module 1 is also used to execute the following method: The core influencing environmental characteristics of the drag reduction film are obtained, wherein the core influencing environmental characteristics include temperature, ultraviolet intensity, friction impact stress, and humidity. The core influencing environmental characteristics are used as target variables, and the change characteristics of the application environmental variables are analyzed to obtain the change amount of each target variable and its change trend. The gradient distribution is determined according to the change amount, and the extreme value of the change amount is obtained based on the gradient distribution. The extreme value characteristics are obtained in combination with the maximum and minimum values ​​of the application environmental variables. The change frequency characteristics and the duration characteristics of the change amount are calculated according to the change amount and its change trend.

[0041] Furthermore, the environment variable parsing module 1 is also used to execute the following method: Collect the data of the change of the target variable over time and construct the change trend; obtain the time line of the aircraft flight in the aviation application environment and the space line of the environmental variable, construct three-dimensional space coordinates, fit the change and its change trend to the three-dimensional space coordinates, and analyze the timeline periodic change and space height periodic change of the target variable; calculate the change frequency characteristics of the periodic characteristics and the duration characteristics of the change according to the timeline periodic change and space height periodic change; set the fluctuation characteristics except the timeline periodic change and space height periodic change as the fluctuation characteristics, and calculate the change frequency characteristics and the duration characteristics of the change.

[0042] Furthermore, the combined search module 2 is also used to perform the following method: According to the extreme value features, the maximum and minimum values ​​of the application environment variables, as well as the maximum and minimum values ​​of the variation, are obtained; according to the maximum and minimum values ​​of the application environment variables, the data interval is obtained, and the segmentation thresholds of the basic environment, the mean environment, and the extreme environment are determined according to the maximum value of the variation and the segmentation ratio relationship of the difference between the maximum and the minimum values; according to the ratio relationship of the change frequency feature and the duration feature, mean segmentation is performed to determine the segmentation relationship of the change frequency feature and the segmentation relationship of the duration feature; the segmentation threshold, the segmentation relationship of the change frequency feature, and the segmentation relationship of the duration feature are normalized to determine the normalized segmentation condition; the stratified weights of the extreme value feature, the change frequency feature, and the duration feature are configured, and the normalized segmentation conditions are integrated using the stratified weights to determine the hierarchical division thresholds, which include the basic environment, the mean environment, and the extreme environment division thresholds respectively; the hierarchical division thresholds are used to perform composite variable feature segmentation on the application environment variables to construct the multi-level weather resistance evaluation target.

[0043] Furthermore, the combined search module 2 is also used to perform the following method: Establish an influence relationship between the periodic characteristics and the multi-level weather resistance evaluation target, and configure the influence weight of the periodic characteristics in the multi-level weather resistance evaluation target; search for the periodic characteristics in the multi-level weather resistance evaluation target, fit the influence weight to the hierarchical weight, and adjust and reset the hierarchical weight.

[0044] Furthermore, the combined search module 2 is also used to perform the following method: The maximum value of the variation is used as the segmentation threshold of the extreme environment; the median of the variation is calculated according to the difference between the maximum and minimum values ​​of the variation; the median of the variation is used as the segmentation node of the basic environment and the mean environment to determine the segmentation threshold of the basic environment and the mean environment.

[0045] Furthermore, the time series fusion evaluation module 4 is also used to perform the following method: According to the application environment target, matching is performed according to the basic environment, mean environment, and extreme environment to obtain a matching environment, where the matching environment is one or more of the basic environment, mean environment, and extreme environment; the matching environments are spliced ​​in time series according to the target time series relationship, and a cumulative function is used to perform a fusion calculation of the test evaluation values ​​to obtain the comprehensive weather resistance evaluation result, wherein when the matching environment is the basic environment or the mean environment, a weighted average algorithm is used for fusion calculation, and when the matching environment is the extreme environment, an exponential decay model is used for fusion calculation.

[0046] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0047] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0048] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A method for adaptively evaluating the weather resistance of aviation drag reduction films, characterized in that: include: Analyze application environment variables and extract environmental change characteristics, including extreme value characteristics, change frequency characteristics, and duration characteristics; The extreme value feature, the change frequency feature, and the duration feature of the composite application environment variable are respectively combined and searched to construct a multi-level weather resistance evaluation target, wherein the multi-level weather resistance evaluation target includes a basic environment, a mean environment, and an extreme value environment; Using the environmental change characteristics of the basic environment, the average environment, and the extreme environment as indexes, respectively, searching and matching are performed in a preset test parameter library to obtain a test evaluation value, wherein the test evaluation value is a test evaluation result obtained for each level of weather resistance evaluation target; According to the application environment target, the cumulative time series relationship of the basic environment, the average environment, and the extreme environment is adaptively configured, and the test evaluation values ​​are evaluated by time series fusion to generate a comprehensive weather resistance evaluation result.

2. The method for adaptively evaluating weather resistance of aviation drag reduction film according to claim 1, characterized in that: The analysis of application environment variables and extraction of environment change characteristics, including extreme value characteristics, change frequency characteristics, and duration characteristics, include: Obtain the core influencing environmental characteristics of the drag-reducing film, which include temperature, ultraviolet intensity, friction impact stress, and humidity. Take the core influencing environmental characteristics as target variables, analyze the change characteristics of the application environmental variables, and obtain the change amount and change trend of each target variable; Determine a gradient distribution according to the variation, obtain an extreme value of the variation based on the gradient distribution, and obtain the extreme value feature in combination with a maximum value and a minimum value of an application environment variable; According to the change amount and its change trend, the change frequency characteristic and the duration characteristic of the change amount are calculated.

3. The method for adaptively evaluating weather resistance of aviation drag reduction film according to claim 2, characterized in that: According to the change amount and its change trend, the change frequency characteristics and the change duration characteristics are calculated, including: Collecting data on the change of the target variable over time and constructing a change trend; Obtain the timeline of aircraft flight and the space line of environmental variables in the aviation application environment, construct three-dimensional space coordinates, fit the change amount and its change trend to the three-dimensional space coordinates, and analyze the timeline periodic changes and space height periodic changes of the target variable; According to the periodic changes of the timeline and the periodic changes of the spatial height, the change frequency characteristics and the duration characteristics of the change amount of the periodic characteristics are calculated; In addition to the periodic changes in the timeline and the periodic changes in the spatial height, they are set as fluctuation characteristics, and the change frequency characteristics and the duration characteristics of the change amount of the fluctuation characteristics are calculated.

4. The method for adaptively evaluating weather resistance of aviation drag reduction film according to claim 3, characterized in that: The extreme value feature, change frequency feature, and duration feature of the composite application environment variable are respectively combined and searched to construct a multi-level weather resistance evaluation target, including: Obtaining the maximum value and minimum value of the application environment variable, as well as the maximum value and minimum value of the variation according to the extreme value feature; According to the maximum and minimum values ​​of the application environment variables, a data interval is obtained, and according to the maximum value of the variation and the segmentation ratio relationship of the difference between the maximum and minimum values, the segmentation thresholds of the basic environment, the average environment, and the extreme environment are determined; According to the proportion relationship of the change frequency feature and the duration feature, mean segmentation is performed to determine the segmentation relationship of the change frequency feature and the segmentation relationship of the duration feature; Normalizing the segmentation threshold, the segmentation relationship of the change frequency feature, and the segmentation relationship of the duration feature to determine a normalized segmentation condition; Configuring hierarchical weights of the extreme value feature, the change frequency feature, and the duration feature, using the hierarchical weights to fuse the normalized segmentation conditions, and determining hierarchical division thresholds, including basic environment, mean environment, and extreme value environment division thresholds; The hierarchical division threshold is used to perform composite variable feature segmentation on the application environment variables to construct the multi-level weather resistance evaluation target.

5. The method for adaptively evaluating weather resistance of aviation drag reduction film according to claim 4, characterized in that: Also includes: Establishing the influence relationship between the periodic characteristics and the multi-level weather resistance evaluation target, and configuring the influence weight of the periodic characteristics on the multi-level weather resistance evaluation target; The periodic features in the multi-level weather resistance evaluation target are searched, the impact weights are fitted to the hierarchical weights, and the hierarchical weights are adjusted and reset.

6. The method for adaptively evaluating weather resistance of aviation drag reduction film according to claim 4, characterized in that: According to the maximum value of the variation and the segmentation ratio relationship between the maximum value and the minimum value, the segmentation thresholds of the basic environment, the average environment, and the extreme environment are determined, including: Using the maximum value of the variation as the segmentation threshold of the extreme environment; Calculate the median of the change according to the difference between the maximum and minimum values ​​of the change; The median of the change is used as a segmentation node for a basic environment and a mean environment, and a segmentation threshold for the basic environment and the mean environment is determined.

7. The method for adaptively evaluating weather resistance of aviation drag reduction film according to claim 1, characterized in that: According to the application environment target, the cumulative time series relationship of the basic environment, the average environment, and the extreme environment is adaptively configured, and the test evaluation value is evaluated in time series to generate a comprehensive evaluation result of weather resistance, including: According to the application environment target, matching is performed according to the basic environment, the average environment, and the extreme environment to obtain a matching environment, where the matching environment is one or more of the basic environment, the average environment, and the extreme environment; The matching environments are spliced ​​in time sequence according to the target time sequence relationship, and the test evaluation values ​​are fused and calculated using a cumulative function to obtain the comprehensive weather resistance evaluation result. When the matching environment is a basic environment or a mean environment, a weighted average algorithm is used for fusion calculation, and when the matching environment is an extreme environment, an exponential decay model is used for fusion calculation.

8. An adaptive weather resistance evaluation system for aviation drag reduction films, characterized in that: The steps for implementing the method for adaptively evaluating weather resistance of an aviation drag reduction film according to any one of claims 1 to 7 include: Environmental variable parsing module: parses application environment variables and extracts environmental change characteristics, including extreme value characteristics, change frequency characteristics, and duration characteristics; Combined search module: Combined search is performed with the extreme value feature, change frequency feature, and duration feature of the composite application environment variable to construct a multi-level weather resistance evaluation target, wherein the multi-level weather resistance evaluation target includes a basic environment, a mean environment, and an extreme value environment; Search and match module: using the environmental change characteristics of the basic environment, the average environment, and the extreme environment as indexes, searching and matching in the preset test parameter library to obtain test evaluation values, which are test evaluation results obtained for each level of weather resistance evaluation target; Time series fusion evaluation module: According to the application environment objectives, the cumulative time series relationship of the basic environment, the average environment, and the extreme environment is adaptively configured, and the test evaluation values ​​are evaluated by time series fusion to generate a comprehensive evaluation result of weather resistance.

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