Method for testing light aging resistance of color changing film

Abstract

The invention discloses a method for testing the light aging resistance of a color changing film, and relates to the technical field of color changing films. The method comprises the following steps: matching a plurality of performance influence factor tolerance spaces based on a key parameter set; performing test risk analysis on the plurality of performance influence factor tolerance intervals, and determining a plurality of test risk factors; calling a historical test data set of the target color change film, and determining a historical test database; on the basis of the historical test database, the application distortion probability of the performance influence factors is calculated in combination with the multiple test risk factors, and multiple application distortion probabilities are obtained; performing performance test scheme balanced identification on the plurality of performance influence factor tolerance spaces, and determining a target performance test scheme; and carrying out light aging resistance test on the target color changing film based on the target performance test scheme. The technical problem that in the prior art, the reliability of the light aging resistance test of the color changing film is poor is solved, and the technical effect of improving the reliability of the light aging resistance test of the color changing film is achieved by optimizing the performance test scheme.

Description

Technical Field

[0001] This invention relates to the field of color-changing film technology, and more specifically to a method for testing the light aging resistance of color-changing films. Background Technology

[0002] In the rapidly developing automotive aftermarket and personalization sector, color-changing films, as an important automotive exterior decoration material, are experiencing increasing market demand. Color-changing films not only provide a wide variety of visual changes for cars but also offer a degree of protection against environmental damage to the original paint. However, during long-term use, especially in outdoor environments, color-changing films face challenges from various factors such as sunlight, temperature, and humidity. These factors can affect the film's resistance to light aging, thus impacting its lifespan and decorative effect. Therefore, conducting light aging resistance tests on color-changing films is crucial to ensure their quality and reliability. However, traditional testing methods often focus on evaluating single or a few performance indicators, neglecting the interactions and complex relationships between multiple performance-influencing factors, leading to unreliable and inaccurate test results. Summary of the Invention

[0003] This application provides a method for testing the light aging resistance of color-changing films, which solves the technical problem of poor reliability in the light aging resistance test of color-changing films in the prior art.

[0004] In view of the above problems, this application provides a method for testing the light aging resistance of color-changing films.

[0005] This application provides a method for testing the light aging resistance of a color-changing film, the method comprising:

[0006] A set of key parameters for the target color-changing film is obtained. Based on this set of key parameters, multiple tolerance spaces for performance influencing factors are matched, where each tolerance space corresponds to a performance influencing factor. A test risk analyzer is used to perform test risk analysis on the tolerance spaces of the multiple performance influencing factors to determine multiple test risk factors. The historical test data set of the target color-changing film is retrieved to determine a historical test database. Based on the historical test database and the multiple test risk factors, the application distortion probability of the performance influencing factors is calculated to obtain multiple application distortion probabilities, where each application distortion probability corresponds to a performance influencing factor. Based on the multiple application distortion probabilities and the historical test database, a performance test scheme balance identification is performed on the tolerance spaces of the multiple performance influencing factors to determine a target performance test scheme. The target color-changing film is then subjected to light aging resistance performance testing based on the target performance test scheme.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] First, a set of key parameters for the target color-changing film is obtained. Based on this set, tolerance spaces for multiple performance influencing factors are matched, with each tolerance space corresponding to a specific performance influencing factor. Next, a test risk analyzer is used to analyze the test risks of each tolerance space for these factors, identifying multiple test risk factors. Simultaneously, historical test data for the target color-changing film is retrieved to establish a historical test database. Next, based on this historical database and the multiple test risk factors, the application distortion probability of each performance influencing factor is calculated, yielding multiple application distortion probabilities, each corresponding to a performance influencing factor. Then, based on these application distortion probabilities and the historical test database, a performance test scheme is balanced and identified across the tolerance spaces for each performance influencing factor, determining the target performance test scheme. Finally, the target color-changing film is subjected to light aging resistance testing based on this target performance test scheme. This approach solves the technical problem of poor reliability in light aging resistance testing of color-changing films in existing technologies. By optimizing the performance test scheme, the reliability of light aging resistance testing for color-changing films is significantly improved. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A schematic flowchart of a method for testing the light aging resistance of a color-changing film provided in an embodiment of this application;

[0011] Figure 2 This is a flowchart illustrating the process of matching tolerance spaces for multiple performance influencing factors in a method for testing the light aging resistance of a color-changing film provided in an embodiment of this application. Detailed Implementation

[0012] This application provides a method for testing the light aging resistance of color-changing films, thereby solving the technical problem of poor reliability in the existing technology for testing the light aging resistance of color-changing films.

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. 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.

[0014] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion. 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 that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0015] Examples, such as Figure 1 As shown in the embodiment of this application, a method for testing the light aging resistance of a color-changing film is provided, wherein the method includes:

[0016] Obtain the set of key parameters for the target color-changing film, and match multiple tolerance spaces for performance influencing factors based on the set of key parameters, wherein each tolerance space for performance influencing factors corresponds to one performance influencing factor.

[0017] The key parameter set of the target color-changing film includes the material of the color-changing film, the type of color dye, and the surface treatment process. By obtaining the key parameter set, multiple performance influencing factors are identified. Each performance influencing factor will affect the light aging resistance of the color-changing film. For each performance influencing factor, a performance influencing factor tolerance space is determined. The performance influencing factor tolerance space reflects the range of influence of the performance influencing factor on the light aging resistance of the color-changing film.

[0018] Furthermore, such as Figure 2 As shown, a set of key parameters for the target color-changing film is obtained, and a tolerance space for multiple performance influencing factors is matched based on the set of key parameters, including:

[0019] Based on the basic material information of the target color-changing film, a first set of key parameters is obtained, including the substrate material, type of ultraviolet absorber, concentration of ultraviolet absorber, and film thickness. Based on the pigment information of the target color-changing film, a second set of key parameters is obtained, including the pigment type, pigment stability, and color-changing film chroma. Based on the surface treatment process data of the target color-changing film, a third set of key parameters is obtained, including the coating type and coating uniformity. The first, second, and third sets of key parameters are used as the set of key parameters. Based on the first, second, and third sets of key parameters, a performance influencing factor analysis is performed to determine the tolerance space of the multiple performance influencing factors.

[0020] Specifically, based on the basic material information of the target color-changing film, a first set of key parameters is determined, including the substrate material (such as polyester, polyurethane, etc.), the type of ultraviolet absorber, the concentration of the ultraviolet absorber, and the film thickness. Based on the pigment information of the target color-changing film, a second set of key parameters is determined, including the pigment type, pigment stability (the chemical stability of the pigment, i.e., whether the pigment easily changes color or degrades under conditions such as light and temperature), and the color of the color-changing film. Based on the surface treatment process data of the target color-changing film, a third set of key parameters is determined, including the coating type (the type of coating on the surface of the color-changing film) and coating uniformity (the uniformity of the coating on the film surface). The first, second, and third sets of key parameters are integrated to form a comprehensive set of key parameters, which includes the main aspects affecting the photoaging resistance of the color-changing film. Based on this set of key parameters, the main factors affecting the photoaging resistance of the color-changing film are identified, such as color durability, gloss change, and mechanical strength. For each performance influencing factor, based on the variation range of the key parameters and factors such as industry standards and customer needs, tolerance ranges for multiple performance influencing factors are determined.

[0021] Furthermore, based on the first key parameter group, the second key parameter group, and the third key parameter group, performance influencing factor analysis is performed to determine the tolerance space of the multiple performance influencing factors, including:

[0022] Using the first, second, and third key parameter groups as indices, photoaging data of the color-changing film is retrieved to obtain a first, second, and third set of photoaging records. Edge transition identification is performed on the first, second, and third sets of photoaging records to determine the first, second, and third sets of photoaging records. The maximum and minimum values ​​of each performance influencing factor in the first, second, and third sets of photoaging records are extracted to generate a tolerance space for the multiple performance influencing factors.

[0023] Specifically, using substrate material, UV absorber type, UV absorber concentration, and film thickness as indexes, relevant photoaging records are retrieved from the existing color-changing film photoaging database to obtain a first set of color-changing film photoaging records; using pigment type, colorant stability, and color-changing film chromaticity as indexes, data retrieval is performed to obtain a second set of color-changing film photoaging records; using coating type and coating uniformity as indexes, corresponding photoaging records are retrieved to form a third set of color-changing film photoaging records; edge transition identification is performed on the first, second, and third sets of color-changing film photoaging records, and edge transition performance indicators (such as color change) are analyzed. Points where significant changes occur suddenly (such as decreased gloss and loss of mechanical strength) are identified through analysis. These transition points are then used to form three sets of photoaging records for color-changing films: a first set, a second set, and a third set. From these sets, the maximum and minimum values ​​of each performance influencing factor are extracted. These values ​​represent the best and worst possible states for the performance factor under different parameter combinations. Based on the extracted maximum and minimum values, a tolerance space is generated for each performance influencing factor.

[0024] Furthermore, edge transition recognition is performed on the first set of photo-aging records, the second set of photo-aging records, and the third set of photo-aging records to determine the first set of photo-aging records, the second set of photo-aging records, and the third set of photo-aging records, including:

[0025] The first color-changing film photoaging record set is input into a D-dimensional space to obtain a first edge transition recognition space. Each dimension of the D-dimensional space corresponds to a performance influencing factor. The first edge transition recognition space includes multiple particle points, each corresponding to a first color-changing film photoaging record, where D is an integer greater than or equal to 1. The spatial center point of the first edge transition recognition space is obtained. Starting from the spatial center point, edge diffusion is performed according to a preset transition bandwidth to obtain a first transition region. The first transition density of the first transition region is calculated, where the first transition density is the ratio of the number of particle points in the first transition region to the area of ​​the region. Edge diffusion is performed on the first transition region according to the preset transition bandwidth to obtain a second transition region, and the second transition density of the second transition region is calculated. It is determined whether the second transition density is greater than or equal to the first transition density. If so, diffusion continues until a preset stopping condition is met to obtain the Nth transition region. The first color-changing film photoaging records corresponding to multiple particle points in the Nth transition region are used as the first recognition set of color-changing film photoaging records.

[0026] Specifically, based on the performance influencing factors of the color-changing film, a D-dimensional space is constructed, where each dimension corresponds to an independent performance influencing factor. Each record in the first color-changing film photoaging record set is mapped to a particle point in the D-dimensional space, resulting in a first edge transition recognition space. This space includes multiple particle points, each corresponding to a first color-changing film photoaging record. The geometric center point of all particle points in the D-dimensional space is calculated as the starting point for edge diffusion. Edge diffusion occurs with the center point as the center, following a preset transition bandwidth (a fixed distance), forming a first transition region. This first transition region contains the first batch of potential edge transitions diffusing outwards from the center point. The process involves: identifying the number of particles in the first transition region; calculating the ratio of the number of particles in the first transition region to the area of ​​the first transition region to obtain the first transition density; continuing edge diffusion of the first transition region according to a preset transition bandwidth to form a second transition region, and calculating the second transition density of the second transition region; if the second transition density is greater than or equal to the first transition density, it means that the trend of performance change is increasing, so it is necessary to continue diffusion to find the true edge transition point; repeating the above diffusion and density calculation process until the preset stopping condition is met (such as the transition density no longer increasing significantly), and finally obtaining the Nth transition region. The photoaging records of the first color-changing film corresponding to multiple particles in the Nth transition region are used as the first recognition color-changing film photoaging record set.

[0027] The same method used for edge transition identification of the first color-changing film photoaging record set was employed to identify the edge transitions of the second and third color-changing film photoaging record sets, thus obtaining the second and third identification color-changing film photoaging record sets.

[0028] Furthermore, the preset stopping condition is that the transition density of the current transition region is greater than the transition density of the previous transition region, and the difference between the two transition densities is less than or equal to a preset density difference.

[0029] Preferably, the preset stopping condition is that the transition density of the current transition region is greater than the transition density of the previous transition region, but the difference between the two transition densities is less than or equal to a preset density difference, then further edge diffusion stops.

[0030] The test risk analyzer was used to analyze the tolerance range of the multiple performance influencing factors to identify multiple test risk factors.

[0031] The test risk analyzer is used to assess the stability or controllable risk when performance influencing factors reach a set range. It receives performance influencing factors and their tolerance ranges as input and outputs multiple test risk factors. These risk factors refer to specific variables or conditions that may affect the results during performance testing. The instability of these risk factors may lead to discrepancies between test results and actual usage. For example, in the performance testing of color-changing films, the difficulty of multiple performance influencing factors reaching the set range makes the testing process unstable, resulting in the color-changing film exhibiting aging characteristics in a short period. The test risk analyzer is a machine learning model trained based on historical data and expert experience.

[0032] Retrieve the historical test data set of the target color-changing film to determine the historical test database.

[0033] Historical test data sets of the target color-changing film are retrieved from big data to establish a historical test database.

[0034] Based on the historical test database, and combined with the multiple test risk factors, the application distortion probability of performance influencing factors is calculated to obtain multiple application distortion probabilities, wherein each application distortion probability corresponds to a performance influencing factor.

[0035] Based on historical test databases and test risk factors, the probability of distortion occurring for each performance influencing factor in practical applications is calculated, resulting in multiple application distortion probabilities.

[0036] Furthermore, based on the historical test database, and combined with the multiple test risk factors, the application distortion probability of performance influencing factors is calculated to obtain multiple application distortion probabilities, including:

[0037] Construct an application distortion probability identification formula, wherein the application distortion probability identification formula is: Where, σ i Let i be the test risk factor corresponding to the i-th performance influencing factor. Let P(σ) be the percentage coefficient corresponding to the i-th test risk factor, and n be the total number of performance influencing factors. iLet be the probability that the color-changing film will prematurely age due to the i-th performance influencing factor during historical testing. The historical test database is retrieved using aging distortion as an index to obtain a set of historical test aging distortion records. Based on the multiple performance influencing factors, the historical test aging distortion record sets are aggregated to obtain multiple aggregated historical test aging distortion record sets. Based on the multiple aggregated historical test aging distortion record sets, multiple premature aging probabilities corresponding to multiple performance influencing factors are determined. The multiple test risk factors and multiple premature aging probabilities are input into the application distortion probability identification formula for analysis to obtain the multiple application distortion probabilities, where the application distortion probability is the probability that the lightfastness aging test of the color-changing film deviates from the actual aging condition due to the control of performance influencing factors.

[0038] Specifically, constructing the application distortion probability formula Where, μ i Let σ be the distortion probability of the i-th performance influencing factor. i Let i be the test risk factor corresponding to the i-th performance influencing factor. Let P(σ) be the percentage coefficient corresponding to the i-th test risk factor, and n be the total number of performance influencing factors. i Let P(σ) represent the probability of premature aging of the color-changing film due to the i-th performance influencing factor during historical testing. Using aging distortion as an index, the historical test database is searched to filter out all records related to aging distortion of the color-changing film, forming a set of historical test aging distortion records. Based on multiple performance influencing factors, the historical test aging distortion record sets are aggregated according to the same factor, that is, all aging distortion records related to the same performance influencing factor are merged into one set, forming multiple aggregated historical test aging distortion record sets. For each aggregated historical test aging distortion record set, the premature aging probability P(σ) corresponding to that performance influencing factor is determined using statistical methods (such as frequency analysis, survival analysis, etc.). i ); Multiple test risk factors σ i and multiple premature aging probabilities P(σ) i Substituting these values ​​into the application distortion probability identification formula, the application distortion probability μ of each performance influencing factor is calculated. i The application distortion probability reflects the probability that the light aging test of the color-changing film deviates from the actual aging condition due to the control of performance-influencing factors.

[0039] Based on the distortion probabilities of the multiple applications and the historical test database, a performance test scheme balance identification is performed on the tolerance space of the multiple performance influencing factors to determine the target performance test scheme.

[0040] Taking into account the distortion probabilities of multiple applications and historical test data, multi-objective optimization and trade-off analysis can be used to optimize the performance test scheme to ensure that the test can comprehensively and accurately reflect the light aging resistance of the color-changing film, and finally obtain the target performance test scheme. The target performance test scheme can maximize the coverage of key performance influencing factors with limited test resources.

[0041] Furthermore, based on the distortion probabilities of the multiple applications and the tolerance space of the multiple performance influencing factors in the historical test database, a performance test scheme balancing identification is performed to determine the target performance test scheme, including:

[0042] Extract successful test data from the historical test database to construct a comparison test database; assign values ​​to the tolerance spaces of the multiple performance influencing factors to form a first initial performance test scheme; calculate the test similarity between the first initial performance test scheme and the comparison test database, and use multiple application distortion probabilities to weight the calculation process to determine the first test similarity, wherein the first test similarity is the maximum similarity between the first initial performance test scheme and the historical test data in the comparison test database; determine whether the first test similarity meets the requirements, and if so, continue to assign values ​​to the tolerance spaces of the multiple performance influencing factors to form a second initial performance test scheme, and calculate the second test similarity; when the second test similarity is greater than or equal to the first test similarity, the second initial performance test scheme is used as the stage performance test scheme; perform balanced identification based on the stage performance test scheme until a preset number of identifications is met, and use the stage performance test scheme corresponding to the maximum test similarity as the target performance test scheme.

[0043] Preferably, all successfully tested test data are selected from the historical test database to construct a comparison test database; preliminary values ​​are assigned to the tolerance space of multiple performance influencing factors, and these are combined to form a first initial performance test plan; the first initial performance test plan is compared with the historical test data in the comparison test database, and their similarity is calculated. The similarity calculation can be based on multiple dimensions such as test conditions, test data, and test results. Simultaneously, multiple application distortion probabilities are used to weight the similarity calculation process. Through weighted calculation, the maximum similarity between the first initial performance test plan and the historical test data in the comparison test database is determined, i.e., the first test similarity; if the first test similarity meets the preset threshold requirement, the iterative process continues, and multiple performance influencing factors are evaluated again. Factor values ​​are selected within a tolerance space to form a second initial performance test scheme, and the second test similarity is calculated. If the second test similarity is greater than or equal to the first test similarity, it indicates that the new test scheme has improved in similarity, and therefore the second initial performance test scheme is used as the stage performance test scheme. The above iterative process is repeated to generate more stage performance test schemes, and their test similarity is calculated. During the iteration process, in addition to focusing on test similarity, it is also necessary to perform balanced identification, that is, to ensure that the test scheme can fully cover all performance influencing factors, while avoiding over-testing or ignoring certain factors. When the number of iterations reaches the preset number of identifications, the iteration process is stopped. The scheme with the maximum test similarity among all stage performance test schemes is selected as the target performance test scheme.

[0044] Furthermore, it also includes:

[0045] When the second test similarity is less than the first test similarity, the values ​​of multiple performance influencing factors of the second initial performance test scheme are added to the taboo table, and the first initial performance test scheme is used as the stage performance test scheme. The values ​​of the performance influencing factors in the taboo table are prohibited from being selected in the balanced recognition of the preset number of recognitions.

[0046] If the similarity of the second test is less than that of the first test, the values ​​of multiple performance influencing factors of the second initial performance test scheme are added to the taboo table, and the first initial performance test scheme is retained as the stage performance test scheme. The taboo table is used to record the values ​​of performance influencing factors that perform poorly in the current iteration (i.e., cause a decrease in test similarity). These values ​​are prohibited from being used in the subsequent balanced recognition process with a preset number of recognitions.

[0047] The target color-changing film was subjected to light aging resistance test based on the target performance test scheme.

[0048] By conducting light aging resistance tests on the target color-changing film according to the established target performance test plan, more reliable and accurate test results can be obtained.

[0049] In summary, the embodiments of this application have at least the following technical effects:

[0050] First, a set of key parameters for the target color-changing film is obtained. Based on this set, tolerance spaces for multiple performance influencing factors are matched, with each tolerance space corresponding to a specific performance influencing factor. Next, a test risk analyzer is used to analyze the test risks of each tolerance space for these factors, identifying multiple test risk factors. Simultaneously, historical test data for the target color-changing film is retrieved to establish a historical test database. Next, based on this historical database and the multiple test risk factors, the application distortion probability of each performance influencing factor is calculated, yielding multiple application distortion probabilities, each corresponding to a performance influencing factor. Then, based on these application distortion probabilities and the historical test database, a performance test scheme is balanced and identified across the tolerance spaces for each performance influencing factor, determining the target performance test scheme. Finally, the target color-changing film is subjected to light aging resistance testing based on this target performance test scheme. This approach solves the technical problem of poor reliability in light aging resistance testing of color-changing films in existing technologies. By optimizing the performance test scheme, the reliability of light aging resistance testing for color-changing films is significantly improved.

[0051] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0052] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0053] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope.

[0054] Thus, if these modifications and variations of this application fall within the scope of this application and its equivalents...

[0055] Within this scope, this application intends to include these modifications and variations.

Claims

1. A method for testing the light aging resistance of a color-changing film, characterized in that, The method includes: Obtain the set of key parameters for the target color-changing film, and match multiple tolerance spaces for performance influencing factors based on the set of key parameters, wherein each tolerance space for performance influencing factors corresponds to one performance influencing factor; The test risk analyzer was used to analyze the tolerance range of the multiple performance influencing factors to determine multiple test risk factors. Retrieve the historical test data set of the target color-changing film to determine the historical test database; Based on the historical test database, and combined with the multiple test risk factors, the application distortion probability of performance influencing factors is calculated to obtain multiple application distortion probabilities, wherein each application distortion probability corresponds to a performance influencing factor. Based on the distortion probabilities of the multiple applications and the historical test database, the tolerance space of the multiple performance influencing factors is used to identify a balanced performance test scheme and determine the target performance test scheme. The target color-changing film was subjected to light aging resistance test based on the target performance test scheme.

2. The method for testing the light aging resistance of a color-changing film as described in claim 1, characterized in that, Obtain the set of key parameters for the target color-changing film, and match the tolerance space of multiple performance influencing factors based on the set of key parameters, including: Based on the basic material information of the target color-changing film, a first set of key parameters is obtained, wherein the first set of key parameters includes the substrate material, the type of ultraviolet absorber, the concentration of ultraviolet absorber, and the film thickness. Based on the pigment information of the target color-changing film, a second key parameter group is obtained, wherein the second key parameter group includes pigment type, pigment stability and color-changing film chromaticity; Based on the surface treatment process data of the target color-changing film, a third set of key parameters is obtained, wherein the third set of key parameters includes coating type and coating uniformity; The first key parameter group, the second key parameter group, and the third key parameter group are used as the key parameter set; Based on the first key parameter group, the second key parameter group, and the third key parameter group, a performance influencing factor analysis is performed to determine the tolerance space of the multiple performance influencing factors.

3. The method for testing the light aging resistance of a color-changing film as described in claim 2, characterized in that, Based on the first key parameter group, the second key parameter group, and the third key parameter group, a performance influencing factor analysis is performed to determine the tolerance space of the multiple performance influencing factors, including: Using the first key parameter group, the second key parameter group, and the third key parameter group as indexes, the photoaging data of the color-changing film is retrieved to obtain the first photoaging record set, the second photoaging record set, and the third photoaging record set. Edge transition identification is performed on the first color-changing film photoaging record set, the second color-changing film photoaging record set, and the third color-changing film photoaging record set to determine the first identification color-changing film photoaging record set, the second identification color-changing film photoaging record set, and the third identification color-changing film photoaging record set. Extract the maximum and minimum values ​​of each performance influencing factor from the first set of light aging records for color-changing films, the second set of light aging records for color-changing films, and the third set of light aging records for color-changing films, and generate the tolerance space for the multiple performance influencing factors.

4. The method for testing the light aging resistance of a color-changing film as described in claim 3, characterized in that, Edge transition identification is performed on the first set of photo-aging records, the second set of photo-aging records, and the third set of photo-aging records for the color-changing film, respectively, to determine the first set of photo-aging records, the second set of photo-aging records, and the third set of photo-aging records for the color-changing film, including: The first color-changing film photoaging record set is input into a D-dimensional space to obtain a first edge transition recognition space. Each dimension in the D-dimensional space corresponds to a performance influencing factor. The first edge transition recognition space includes multiple particle points, each particle point corresponds to a first color-changing film photoaging record, and D is an integer greater than or equal to 1. Obtain the spatial center point of the first edge transition recognition space, and use the spatial center point as the starting point to perform edge diffusion according to the preset transition bandwidth to obtain the first transition region. Calculate the first transition density of the first transition region, wherein the first transition density is the ratio of the number of particle points in the first transition region to the area of ​​the region. The first transition region is edge-diffused according to a preset transition bandwidth to obtain a second transition region, and the second transition density of the second transition region is calculated. Determine whether the second transition density is greater than or equal to the first transition density. If so, continue diffusion until a preset stopping condition is met to obtain the Nth transition region. The first color-changing film photoaging records corresponding to multiple particle points in the Nth transition region are used as the first identification color-changing film photoaging record set.

5. The method for testing the light aging resistance of a color-changing film as described in claim 4, characterized in that, The preset stopping condition is that the transition density of the current transition region is greater than the transition density of the previous transition region, and the difference between the two transition densities is less than or equal to the preset density difference.

6. The method for testing the light aging resistance of a color-changing film as described in claim 1, characterized in that, Based on the historical test database, and combined with the multiple test risk factors, the application distortion probability of performance influencing factors is calculated to obtain multiple application distortion probabilities, including: Construct an application distortion probability identification formula, wherein the application distortion probability identification formula is: Where, σ i Let i be the test risk factor corresponding to the i-th performance influencing factor. Let P(σ) be the percentage coefficient corresponding to the i-th test risk factor, and n be the total number of performance influencing factors. i ) represents the probability that the color-changing film will age prematurely due to the i-th performance influencing factor during historical testing. The historical test database is retrieved using aging distortion as an index to obtain a set of historical test aging distortion records; Based on the multiple performance influencing factors, the historical test aging distortion record set is aggregated with the same factor to obtain multiple aggregated historical test aging distortion record sets. Based on the aforementioned collection of aggregated historical test aging distortion records, multiple premature aging probabilities corresponding to multiple performance influencing factors are determined. The multiple test risk factors and multiple premature aging probabilities are input into the application distortion probability identification formula for analysis to obtain the multiple application distortion probabilities. The application distortion probability is the probability that the light aging test of the color-changing film deviates from the actual aging condition due to the control of performance influencing factors.

7. The method for testing the light aging resistance of a color-changing film as described in claim 1, characterized in that, Based on the distortion probabilities of the multiple applications and the historical test database, a performance test scheme balancing identification is performed on the tolerance space of the multiple performance influencing factors to determine the target performance test scheme, including: Extract successfully tested data from the historical test database and construct a comparison test database; Each of the multiple performance influencing factors is assigned a value within its tolerance space to form a first initial performance test scheme. Calculate the test similarity between the first initial performance test scheme and the comparison test database, and use multiple application distortion probabilities to weight the calculation process to determine the first test similarity, wherein the first test similarity is the maximum similarity between the first initial performance test scheme and the historical test data in the comparison test database; Determine whether the first test similarity meets the requirements. If so, continue to take factor values ​​for the tolerance space of the multiple performance influencing factors to form a second initial performance test scheme, and calculate the second test similarity. When the second test similarity is greater than or equal to the first test similarity, the second initial performance test scheme will be used as the stage performance test scheme. Based on the aforementioned stage performance test scheme, balanced identification is performed until a preset number of identifications is met, and the stage performance test scheme corresponding to the maximum test similarity is taken as the target performance test scheme.

8. The method for testing the light aging resistance of a color-changing film as described in claim 7, characterized in that, include: When the second test similarity is less than the first test similarity, the values ​​of multiple performance influencing factors of the second initial performance test scheme are added to the taboo table, and the first initial performance test scheme is used as the stage performance test scheme. The values ​​of the performance influencing factors in the taboo table are prohibited from being selected in the balanced recognition of the preset number of recognitions.

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