Surface corrosion evaluation method for aluminum alloy plate with epoxy coating

Abstract

The invention relates to the technical field of processing, testing or inspection of aircraft parts, and provides a surface corrosion evaluation method for an aluminum alloy plate with an epoxy coating, which comprises the following steps: acquiring an aluminum alloy plate sample with an epoxy coating at different time after being exposed in a coastal atmospheric environment, collecting two-dimensional closed corrosion area image data of the surface of the sample, and calculating the surface corrosion of the aluminum alloy plate with the epoxy coating according to the two-dimensional closed corrosion area image data; processing the image to extract a closed boundary of the corrosion area; calculating the boundary length of the corrosion area and the included corrosion area, and calculating the fractal dimension of the corrosion area based on the length and the area; according to the method, the correlation model between the fractal dimension of the corrosion area and the exposure corrosion time is established, the interval distribution of the fractal dimension under different corrosion time is determined, the method is used for evaluating the corrosion state and the development trend of the corrosion state, the limitation of parameter evaluation modes such as subjective judgment and single corrosion depth is avoided, and the accuracy and objectivity of a corrosion evaluation result are effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of processing, testing or inspection of aircraft components, and in particular to a surface corrosion evaluation method for an epoxy-coated aluminum alloy plate. BACKGROUND

[0002] In the field of metal structures serving in high-salt and high-humidity environments for a long time, such as aviation, aluminum alloys are widely used due to their excellent specific strength and corrosion resistance. In order to further improve the corrosion resistance, an organic epoxy coating is often applied to the surface of the aluminum alloy in engineering. However, as the service time is prolonged and the corrosion medium in the marine atmosphere continuously erodes, the epoxy coating gradually ages and even fails, and corrosion gradually penetrates the coating into the aluminum alloy substrate, which may cause more serious structural damage such as pitting corrosion and intergranular corrosion. In order to effectively evaluate the service corrosion state of such coated structures and predict the degradation trend of their service life, a reliable and accurate corrosion evaluation method is urgently needed. In the prior art, surface corrosion detection and evaluation methods mainly rely on macroscopic observation (such as visually observable coating blistering, peeling, cracking, etc.) or physical quantity testing (such as mass loss method, corrosion depth measurement, electrochemical impedance spectroscopy, etc.). However, these methods generally have two technical limitations: (1) Most methods are mainly point-like measurement or linear parameters, which are difficult to reflect the evolution law of the corrosion area in the spatial morphology level and are not sensitive to the complexity of the corrosion morphology; (2) The evaluation results are usually static judgments, lacking quantitative expression and prediction ability for the evolution trend of the corrosion state with service time, resulting in a large lag in corrosion risk identification. Especially in the early stage when the coating has not completely peeled off or local defects have appeared, the corrosion behavior has obvious irregularity, boundary ambiguity and nonlinear expansion characteristics. The existing technology is difficult to accurately identify and quantify the outline of such corrosion areas, thus failing to provide effective monitoring basis for early corrosion. In addition, the existing corrosion evaluation relies on single-dimension parameters such as area, depth and mass, which easily ignores important information about the complexity of the corrosion process in the morphology, resulting in low sensitivity and reliability of the evaluation model to material state changes. SUMMARY

[0003] In view of the above-mentioned deficiencies in the prior art, the present application provides a surface corrosion evaluation method for an epoxy-coated aluminum alloy plate, which effectively overcomes the deficiencies of traditional corrosion evaluation in terms of sensing accuracy and evolution analysis, and realizes accurate and reliable evaluation of the surface corrosion of the epoxy-coated aluminum alloy plate.

[0004] The surface corrosion evaluation method for an epoxy-coated aluminum alloy plate provided by the present application comprises: obtaining an epoxy-coated aluminum alloy plate sample exposed to a marine atmosphere for different times, obtaining image data of a two-dimensional closed corrosion area on the surface of the sample, and processing the image data to determine the closed boundary of the corrosion area; calculate the fractal dimension of the corrosion area according to the boundary length of the corrosion area and the corrosion area; the epoxy-coated aluminum alloy plate sample has irregular cracks, corrosion pits and pitting corrosion morphology during surface corrosion process; establish a correlation model between the fractal dimension of the corrosion area and the exposure corrosion time, determine the fractal dimension interval of the corrosion area corresponding to different exposure corrosion times, and evaluate the corrosion state and corrosion development trend of the epoxy-coated aluminum alloy plate sample, so as to evaluate the surface corrosion of the epoxy-coated aluminum alloy plate.

[0005] Compared with the prior art, the present application has the following advantages: The present application provides a surface corrosion evaluation method for an epoxy-coated aluminum alloy plate, which comprises the following steps: obtaining an epoxy-coated aluminum alloy plate sample exposed to a coastal atmospheric environment for different times, obtaining image data of a two-dimensional closed corrosion area on the surface of the sample, processing the image data, determining the closed boundary of the corrosion area, calculating the boundary length of the corrosion area and the corrosion area contained by the boundary of the corrosion area, calculating the fractal dimension of the corrosion area according to the boundary length of the corrosion area and the corrosion area, establishing a correlation model between the fractal dimension of the corrosion area and the exposure corrosion time, determining the fractal dimension interval of the corrosion area corresponding to different exposure corrosion times, and evaluating the corrosion state and corrosion development trend of the epoxy-coated aluminum alloy plate sample, so as to evaluate the surface corrosion of the epoxy-coated aluminum alloy plate. Thus, the present application effectively overcomes the shortcomings of traditional corrosion evaluation in terms of sensing accuracy and evolution analysis, and realizes accurate and reliable evaluation of the surface corrosion of the epoxy-coated aluminum alloy plate. BRIEF DESCRIPTION OF DRAWINGS

[0006] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings, which are not necessarily drawn to scale, like reference numerals describe similar components throughout the several views. It should be understood that these drawings are not necessarily to scale, and in certain instances, the drawings have been simplified for the sake of clarity: Figure 1 is a flowchart of the surface corrosion evaluation method for the epoxy-coated aluminum alloy plate according to an embodiment of the present application. DETAILED DESCRIPTION

[0007] In the following, the technical solutions in the embodiments will be described clearly and completely with reference to the drawings in the embodiments so as to make the technical personnel in the technical field better understand the technical solutions. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by the ordinary skilled in the art without creative work should belong to the protection scope of the present application.

[0008] Referring to Figure 1 The present embodiment provides a surface corrosion evaluation method of an epoxy-coated aluminum alloy plate, comprising the following steps: S101, acquiring an epoxy-coated aluminum alloy plate sample exposed in a coastal atmospheric environment for different times, acquiring image data of a two-dimensional closed corrosion area on the surface of the sample, and processing the image data to determine the closed boundary of the corrosion area; the epoxy-coated aluminum alloy plate sample has irregular cracks, corrosion pits and pore corrosion spreading morphology in the surface corrosion process; S102, calculating the boundary length of the corrosion area and the corrosion area contained in the boundary of the corrosion area, and calculating the fractal dimension of the corrosion area according to the boundary length of the corrosion area and the corrosion area; S103, establishing a correlation model between the fractal dimension of the corrosion area and the exposure corrosion time, determining the fractal dimension interval of the corrosion area corresponding to different exposure corrosion times, evaluating the corrosion state and corrosion development trend of the epoxy-coated aluminum alloy plate sample, and evaluating the surface corrosion of the epoxy-coated aluminum alloy plate.

[0009] It should be noted that the image data of the two-dimensional closed corrosion area of the surface of the test sample is acquired, and the image data is processed to determine the closed boundary of the corrosion area, thereby quantitatively extracting the corrosion area profile information, avoiding relying on subjective experience or simple macro corrosion depth judgment. At the same time, the boundary length of the corrosion area and the area of the corrosion area are calculated, and the fractal dimension of the corrosion area is calculated accordingly, so that the fractal dimension is used in the corrosion state evaluation, avoiding the limitation of relying only on depth, area or mass loss index in the corrosion evaluation, which can more sensitively reflect the structural evolution trend of the corrosion area. In addition, a correlation model between the fractal dimension and the exposed corrosion time is established, thereby realizing the quantitative description of the time scale of the corrosion development process, so that the corrosion evaluation no longer stays in the qualitative analysis stage, but has the ability to predict the future corrosion trend, achieving the purpose of enhancing the traceability and prediction ability of the evaluation. In general, the overall scheme formed by image recognition, boundary area calculation and trend modeling in the embodiment builds a quantitative evaluation framework for the structural feature evolution of the corrosion behavior, avoids relying on a single physical or electrochemical quantity evaluation method, and improves the reliability and accuracy of the surface corrosion evaluation of the epoxy-coated aluminum alloy plate.

[0010] Further, the surface corrosion evaluation method of the epoxy-coated aluminum alloy plate further comprises: The electrochemical corrosion parameters of the epoxy-coated aluminum alloy plate sample after different exposed corrosion times are measured by an electrochemical test method, and the electrochemical corrosion parameters include open circuit potential, corrosion current density and polarization resistance; the change trend of the electrochemical corrosion parameters with the exposed corrosion time is analyzed, and the change trend of the electrochemical corrosion parameters is fused with the change trend of the fractal dimension of the corrosion area to obtain an evaluation model coupled with the fractal dimension and the electrochemistry, so as to comprehensively evaluate the corrosion state and corrosion development trend of the surface of the aluminum plate. It should be noted that the electrochemical corrosion parameters include open circuit potential, corrosion current density and polarization resistance, which correspond to the thermodynamic trend, kinetic rate and charge transfer resistance of the metal in the corrosion process, respectively, and are the commonly used electrochemical corrosion criteria in international standards. In the traditional method, these electrochemical parameters are used alone to quantitatively evaluate the corrosion rate, and it is difficult to identify the geometric evolution process of the corrosion area. In the embodiment, by fusing the change trend of the electrochemical corrosion parameters with the change trend of the fractal dimension of the corrosion area, the shortcomings of the single-dimensional evaluation method in some corrosion forms are made up. For example, part of the slow corrosion may not be obvious on the image but has a response on the electrochemical parameters, or vice versa. Through trend comparison and analysis, the corrosion evolution stage can be verified from multiple angles and multiple scales. By establishing the evaluation model coupled with the fractal dimension and the electrochemistry, the corrosion spatial morphology evolution and the corrosion electrochemical process are modeled synchronously, thereby providing more comprehensive and stable corrosion identification results, which is helpful to realize intelligent prediction and risk grading.

[0011] Further, the surface corrosion evaluation method of the epoxy-coated aluminum alloy plate member further comprises: modeling and training the data of the change of the fractal dimension of the corrosion area with the exposure corrosion time using a machine learning algorithm to obtain a prediction model of the fractal dimension of the corrosion area; predicting the fractal dimension of the sample that has not yet reached the exposure corrosion time node using the prediction model to evaluate the future corrosion state and corrosion trend in advance; and dynamically optimizing the prediction model using the difference between the actually measured fractal dimension of the corrosion area and the prediction result of the prediction model to achieve adaptive prediction of the corrosion trend. It should be noted that by modeling and training the data of the change of the fractal dimension with the exposure corrosion time, the machine learning model can identify the internal laws between the fractal characteristics at different time points. The fractal dimension of the sample that has not yet reached the exposure corrosion time node can be predicted before the exposure period is completed, so that the future corrosion state can be judged in advance. At the same time, the prediction model is dynamically optimized using the difference between the actual measurement value and the prediction value, so that the prediction model has the ability of continuous learning and error correction, which not only enhances the robustness and generalization ability of the model, but also adapts to the changes in corrosion evolution laws in different regions, material batches or environmental conditions, and strengthens the long-term stability and on-site adaptability of the corrosion evaluation results.

[0012] Preferably, the acquisition of the image data specifically comprises: using a digital video microscope device to capture the surface micro-morphology of the epoxy-coated aluminum alloy plate member sample after different periods of exposure corrosion, and to derive the corresponding image data of the two-dimensional closed corrosion area. It should be noted that in the present embodiment, the digital video microscope device is used to capture the surface micro-morphology of the epoxy-coated aluminum alloy plate member sample after different periods of exposure corrosion, so as to realize quantitative and time-layered shooting, and avoid the shortcomings of relying on macroscopic visual observation or short-period electrochemical testing. On the one hand, the digital video microscope has high-resolution imaging capability, which can clearly capture the complex details such as the boundary, cracks and blistering of the corrosion area, providing high-quality basic image data for subsequent image processing and fractal dimension calculation. On the other hand, the images taken at different lengths of corrosion exposure time points ensure the coverage and contrast of the evaluation model in the time dimension, so that the correlation between the established fractal dimension and the corrosion time is more representative.

[0013] Preferably, the calculation of the fractal dimension of the corrosion region comprises: determining a measurement scale and dividing the corrosion region into an initial scale, dividing the corrosion region into a plurality of islands of different scales, and counting the number of islands at each scale, calculating the boundary length and the area of the corrosion region at each scale, and calculating the fractal dimension of the corrosion region according to the boundary length and the area of the corrosion region. It should be noted that in the embodiment, by dividing the corrosion region into a plurality of islands of different scales and counting the number, boundary and area at each scale, the fractal dimension becomes an operable, measurable and repeatable physical parameter, thereby providing a method based on geometric multi-scale structure analysis, which sensitively captures the complexity of the corrosion profile at different scales and realizes the mapping between morphological complexity and material degradation. Since the aluminum alloy surface corrosion process often has irregular cracks, corrosion pits and pitting corrosion spreading, etc. Various morphologies, the fractal dimension can uniformly describe the nonlinear morphological evolution trend, and improve the adaptability and evaluation accuracy of the corrosion evaluation method in dealing with complex morphologies.

[0014] Preferably, when calculating the fractal dimension of the corrosion region according to the boundary length and the area of the corrosion region, the algorithm formula of the fractal dimension of the corrosion region satisfies: ; The algorithm formula of the fractal dimension of the corrosion region is simplified as: ; In the formula, the fractal dimension coefficient, represents the measurement scale of the corrosion region, is the boundary length of the corrosion region, is the area of the corrosion region, is the fractal dimension of the corrosion region, represents the fractal dimension function value of the corrosion region at the measurement scale ; represents the boundary length of the corrosion region at the measurement scale ; represents the area of the corrosion region at the measurement scale .

[0015] It should be noted that in the embodiment, by constructing the nonlinear relationship between the boundary length and the area, the geometric evolution characteristics of the corrosion morphology are objectively reflected. For example, in the case where the boundary of the corrosion region becomes more complex, more jagged or more irregular, although the area may grow slowly, the boundary length will obviously grow, resulting in the value of D calculated to increase with the corrosion complexity, thereby forming a sharp response to the structural evolution of the corrosion.

[0016] ​Preferably, the surface corrosion evaluation method of the epoxy-coated aluminum alloy plate also comprises: measuring the surface roughness of the epoxy-coated aluminum alloy plate sample after different corrosion times by using an atomic force microscope, and using the surface roughness to assist in verifying the correlation between the fractal dimension of the corrosion area and the surface corrosion degree. It should be noted that in the present embodiment, the atomic force microscope (AFM) measures the surface roughness after different corrosion times to verify the correlation between the fractal dimension of the corrosion area and the surface corrosion degree, so that the corrosion evaluation method is expanded from a single image processing model to a multi-physical field coupled data source evaluation system. AFM can realize three-dimensional surface topography measurement with nanometer resolution, and obtain roughness parameters (such as Ra value) of microscopic structures such as corrosion pits and cracks. These information is highly related to corrosion propagation and coating degradation behavior. Combining it with the fractal dimension obtained by image analysis can not only verify each other, but also enhance the physical meaning of the fractal dimension. Especially when the initial corrosion is not obvious and the image boundary is difficult to extract, the roughness change of AFM can be used as a warning basis to improve the early detection sensitivity.

[0017] Preferably, the roughness parameter obtained during the atomic force microscope measurement process is surface roughness, and the change trend of the surface roughness with corrosion time is analyzed as a supplementary basis for corrosion evaluation. It should be noted that the roughness parameter obtained during the atomic force microscope measurement process is surface roughness, and the change trend of the surface roughness with corrosion time is analyzed, so as to construct a roughness evolution curve in the time dimension, strengthen the time dynamics of the corrosion quantitative evaluation method, and reflect the trend of coating degradation or corrosion intensification by continuously sampling Ra values at different corrosion time points. For example, the change in the rising rate of Ra value can indicate the corrosion transformation stage or the critical failure point. In the present embodiment, not only the dynamic tracking of the corrosion degree is realized, but also the change curve of the fractal dimension obtained by image calculation is compared and cross-verified, which greatly improves the stability and prediction ability of the evaluation model, effectively avoids misjudgment caused by local distortion or accidental defects, and strengthens the time continuity and evolution trend judgment ability of the corrosion evaluation.

[0018] Preferably, the processing of the image data to determine the closed boundary of the corrosion region specifically comprises automatic recognition and extraction of the image data by digital image processing technology, including edge detection and contour tracking. It should be noted that the automatic recognition and extraction of the closed boundary of the corrosion region by digital image processing technology can effectively solve the problems of strong subjectivity, low precision and poor repeatability of manual recognition of the boundary. By using an edge detection algorithm (such as Canny, Sobel, etc.) combined with a contour tracking algorithm, the complete closed contour of the corrosion region can be automatically extracted in the image, which not only greatly improves the data processing efficiency, but also enhances the consistency and reproducibility of the extraction results. In particular, for the case of early corrosion morphology being fuzzy or the coating being slightly damaged, the edge position can be accurately identified in the image gray scale variation, and the complex irregular corrosion contour information can be extracted.

[0019] Further, when the image data is automatically recognized and extracted by using edge detection and contour tracking to determine the closed boundary of the corrosion region, it comprises: performing image enhancement processing on the image of the corrosion region to improve the contrast between the edge of the corrosion region and the background; using an edge detection operator to calculate the gradient amplitude and direction of each pixel point, wherein the gradient calculation formula of the edge detection operator is: ; is the gradient amplitude of the pixel point, is the gray value of the pixel point, is a direction-sensitive weight matrix, is the coordinate offset of the element in the matrix relative to the pixel point . According to the gradient amplitude, an initial edge is determined, and morphological operations are used to refine and smooth the initial edge; a contour tracking algorithm is used to extract the closed boundary of the smoothed edge, wherein the closed boundary judgment algorithm of the contour tracking algorithm is: ; wherein, is a closed boundary set, is a current contour track, is a specific two-dimensional coordinate of a pixel point in the current processing image, used to describe the position of a point on the contour track, is an image gray gradient, is a contour normal vector, is a boundary closure threshold.

[0020] It should be noted that in the embodiment, the gradient calculation formula of the direction-sensitive weight matrix and the closed boundary determination algorithm of the contour tracking algorithm can more effectively process actual images with complex, irregular and more noise corrosion regions, and reduce the defects of high sensitivity to noise and easy failure of closed boundary extraction of traditional edge detection methods. The closed boundary determination adopts the gradient vector integral method, fully utilizes the direction and continuity characteristics of the edge gradient, effectively overcomes the shortcomings of the conventional closed determination which only relies on the pixel adjacency judgment, and greatly improves the robustness, accuracy and stability of the closed boundary extraction of the corrosion region.

[0021] Preferably, the surface corrosion evaluation method of the epoxy-coated aluminum alloy plate also includes: analyzing the cross section of the coating sample exposed to corrosion by using a scanning electron microscope and an energy spectrometer, and evaluating the specific situation of corrosion penetrating the coating and invading the aluminum alloy substrate according to the cross section of the coating sample. It should be noted that the scanning electron microscope (SEM) and the energy spectrometer (EDS) analyze the cross section of the coating sample exposed to corrosion to evaluate whether the corrosion has penetrated the coating and invaded the aluminum alloy substrate, thereby forming a cross-sectional verification mechanism, effectively combining surface corrosion morphology evaluation with material internal corrosion mechanism verification. The SEM has the ability to observe the microstructure of the material cross section at the nanoscale, can detect coating blistering, peeling and microcrack channels, and the EDS can identify the distribution of corrosion product elements such as Cl, O, Al, etc., and further judge the corrosion path and depth. By comparing the cross-sectional state of samples with different corrosion times, the embodiment provides longitudinal deep data in addition to macroscopic morphology data, enhances the depth information support of corrosion evaluation, and has important significance for verifying the actual corrosion penetration state corresponding to the fractal dimension trend, avoiding misjudgment or underestimation caused by surface image analysis alone.

[0022] Preferably, in the process of evaluating the specific situation that the corrosion has penetrated the coating and invaded the aluminum alloy substrate, the aluminum alloy substrate is first evaluated for intergranular corrosion according to the coating sample cross section, and then the element distribution of the coating after intergranular corrosion and the composition of the corrosion product are analyzed by electron probe microanalysis. It should be noted that the element distribution and corrosion product composition are analyzed by electron probe microanalysis (EPMA) after evaluating intergranular corrosion (IGC), thereby achieving in-depth identification at the level of fine structure failure mechanism. Intergranular corrosion is a typical form of localized corrosion, which often causes a significant decrease in structural strength due to the preferential invasion of corrosion medium along the grain boundaries. It is difficult to accurately determine it only by surface morphology. EPMA technology can analyze the element distribution and migration path in the corrosion area at a spatial resolution of microns, which can assist in judging the corrosion cause and development trend, such as determining whether the interface is activated by Cl ion erosion. Through this embodiment, the corrosion mechanism tracing ability and the physical verification accuracy of the fractal trend result can be significantly improved, so that the corrosion dimension is not only limited to the geometric scale, but also related to the microstructure evolution of the material. Through the fusion with the image dimension, a more physically meaningful corrosion fractal model can be established, and the objectivity and reliability of the overall evaluation system can be improved.

[0023] Preferably, the process of establishing the correlation model between the fractal dimension of the corrosion area and the exposure corrosion time comprises: obtaining the fractal dimension of the corrosion area of samples at different corrosion times, constructing a statistical relationship graph of the fractal dimension changing with the corrosion time, performing least squares linear regression fitting on the statistical relationship graph, extracting the slope and intercept parameters in the fitting equation, and obtaining the quantitative relationship between the corrosion time and the fractal dimension; and establishing the correlation model between the fractal dimension of the corrosion area and the exposure corrosion time according to the obtained quantitative relationship between the corrosion time and the fractal dimension. It should be noted that the statistical graph is constructed and least squares linear regression fitting is performed to extract the slope and intercept, and the correlation model between the fractal dimension and the corrosion time is established, thereby realizing the extraction of the fractal dimension index with physical meaning from multiple time point samples, and establishing a quantitative evolution model by means of statistical fitting tools, achieving high timeliness, stability and replicability.

[0024] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for surface corrosion evaluation of an aluminum alloy panel with an epoxy coating, characterized by, The method comprises the following steps: obtaining an epoxy-coated aluminum alloy plate sample exposed to a coastal atmospheric environment for different periods of time, obtaining image data of a two-dimensional closed corrosion area on the surface of the sample, and processing the image data to determine the closed boundary of the corrosion area; the epoxy-coated aluminum alloy plate sample has irregular cracks, corrosion pits and pitting corrosion morphology during surface corrosion; calculating the boundary length of the corrosion area and the area of the corrosion area contained in the boundary of the corrosion area, and calculating the fractal dimension of the corrosion area according to the boundary length of the corrosion area and the area of the corrosion area; establishing a correlation model between the fractal dimension of the corrosion area and the exposure corrosion time, determining the fractal dimension interval of the corrosion area corresponding to different exposure corrosion times, and evaluating the corrosion state and corrosion development trend of the epoxy-coated aluminum alloy plate sample to evaluate the surface corrosion of the epoxy-coated aluminum alloy plate.

2. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to claim 1, wherein, The image data acquisition specifically includes: using a digital video microscope device to capture the surface micro-morphology of the epoxy-coated aluminum alloy plate sample after being exposed to corrosion for different periods of time, and exporting the corresponding image data of the two-dimensional closed corrosion area.

3. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to claim 1, wherein, The calculation of the fractal dimension of the corrosion area includes: determining the measurement scale and dividing the corrosion area into multiple small islands of different scales with the initial scale, counting the number of small islands at each scale, calculating the boundary length and area of the corrosion area at each scale, and calculating the fractal dimension of the corrosion area according to the boundary length and area of the corrosion area.

4. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to claim 3, wherein When calculating the fractal dimension of the corrosion area according to the boundary length of the corrosion area and the corrosion area area, the algorithm formula of the fractal dimension of the corrosion area is satisfied: ; The algorithmic formula of the fractal dimension of the corrosion region is simplified as: ; In the formula, fractal dimension coefficient, a measurement scale of the corrosion area, a boundary length of the corrosion area, an area of the corrosion area, a fractal dimension of the corrosion area, a fractal dimension function value of the corrosion area at a measurement scale ; a boundary length of the corrosion area at a measurement scale ; an area of the corrosion area at a measurement scale .

5. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to claim 1, wherein Further comprising: Using an atomic force microscope to measure the surface roughness of the epoxy-coated aluminum alloy plate sample after different corrosion times, and using the surface roughness to assist in verifying the correlation between the fractal dimension of the corrosion area and the surface corrosion degree.

6. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to claim 5, wherein The roughness parameter obtained during the atomic force microscope measurement is the surface roughness, and the change trend of the surface roughness with the corrosion time is analyzed as a supplementary basis for corrosion evaluation.

7. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to claim 1, wherein The processing of the image data to determine the closed boundary of the corrosion area specifically includes: automatically identifying and extracting the image data through digital image processing technology, which includes edge detection and contour tracking.

8. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to claim 1, wherein Further comprising: Using a scanning electron microscope and an energy spectrometer to analyze the cross section of the coating sample after exposure to corrosion, and evaluating the specific situation of corrosion penetrating the coating and invading the aluminum alloy matrix according to the cross section of the coating sample.

9. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to claim 8, wherein, During the process of evaluating the specific situation of corrosion penetrating the coating and invading the aluminum alloy matrix, first evaluate the intergranular corrosion of the aluminum alloy matrix according to the cross section of the coating sample, and then analyze the element distribution of the coating and the composition of the corrosion product through electron probe microanalysis.

10. The method of surface corrosion evaluation of an epoxy-coated aluminum alloy panel according to any one of claims 1-9, characterized in that, The method for establishing the correlation model between the fractal dimension of the corrosion area and the exposed corrosion time specifically comprises: obtaining the fractal dimensions of the corrosion areas of samples with different corrosion times, constructing a statistical relationship graph of the fractal dimension changing with the corrosion time, performing least square linear regression fitting on the statistical relationship graph, extracting the slope and intercept parameters in the fitting equation, and obtaining the quantitative relationship between the corrosion time and the fractal dimension; and establishing the correlation model between the fractal dimension of the corrosion area and the exposed corrosion time according to the obtained quantitative relationship between the corrosion time and the fractal dimension.

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