Method for detecting surface defects of 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 method for detecting surface defects of an aluminum alloy plate with an epoxy coating. The method comprises the following steps: applying an epoxy coating doped with a zinc yellow pigment to an anodic oxide film to construct a coating test piece with a color difference indication function, and placing the coating test piece in a coastal atmospheric environment for exposure sampling. In the detection process, the gloss loss rate, the chromatic aberration, the contact angle, the defect area proportion and the corrosion current density are collected, a dynamic correction coefficient is calculated according to the hydrolysis degree of the zinc yellow pigment, all parameter thresholds are adjusted in a self-adaptive mode, and a threshold set is constructed. And in combination with scanning electron microscope image segmentation and Tafel extrapolation analysis, multi-source indexes are fused to judge whether the coating is invalid. According to the method, the hydrolysis behavior of the zinc yellow pigment can be tracked in real time, the judgment standards of optical, morphology and electrochemical indexes are automatically corrected, and the accuracy and reliability of failure detection of the epoxy coating aluminum alloy plate under the coastal service condition are 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 method for detecting surface defects of an aluminum alloy plate with an epoxy coating. BACKGROUND

[0002] Aluminum alloys are widely used in aviation equipment. In order to improve corrosion resistance, an anodic oxidation is first performed on the surface of the aluminum alloy, and then an epoxy system protective coating is coated. However, in the coastal atmosphere, the salt content is high, the humidity is high, and the ultraviolet radiation is strong, and the coating is prone to defects such as loss of luster, discoloration, cracking and blistering during long-term service; once the defects penetrate, the matrix pitting and even intergranular corrosion will be quickly induced. The existing defect evaluation method mainly relies on a small number of indexes (such as loss of luster or polarization current) to determine, and the criterion is fixed, which cannot reflect the performance fluctuation of the coating due to environmental changes or self-healing reaction in real time, resulting in high misjudgment rate and high risk of leakage detection. In addition, the traditional color difference monitoring ignores the chemical action of the self-passivating pigment in the coating, and cannot distinguish the influence of external discoloration and internal chemical repair. Although a multi-parameter model combining electron microscopy, image segmentation and electrochemical technology has been proposed, it lacks a dynamic updating mechanism for the threshold value coupled with the self-healing chemical process of the coating, and it is difficult to adapt to the determination needs of different aging stages. Therefore, there is an urgent need for a comprehensive detection method that can track the hydrolysis behavior of zinc yellow pigment in real time, automatically correct multiple thresholds, and integrate optical, topographic and electrochemical information, to accurately evaluate the failure risk of epoxy-coated aluminum alloy plates under coastal service conditions. SUMMARY

[0003] In view of the deficiencies in the prior art, the present application provides a method for detecting surface defects of an aluminum alloy plate with an epoxy coating, which can track the hydrolysis behavior of zinc yellow pigment in real time, automatically correct multiple thresholds, and integrate optical, topographic and electrochemical information, to accurately evaluate the failure risk of epoxy-coated aluminum alloy plates under coastal service conditions.

[0004] The method for detecting surface defects of an aluminum alloy plate with an epoxy coating provided by the present application comprises: anodizing the aluminum alloy plate substrate to form an oxide film, and coating an epoxy resin coating doped with zinc yellow pigment on the surface of the oxide film; utilizing the characteristics of the zinc yellow pigment that gradually releases chromate ions after being damp and forms a color indicating band inside the coating and at the edges of the defects, constructing a color difference indicating system that can be self-repaired with service time, to obtain a coating test piece as a subsequent detection object; The coating test piece is placed in a coastal atmospheric exposure environment, and the exposed test piece is sampled and detected at preset equal time intervals, the coating surface parameters of the exposed test piece are respectively measured, and the change curves of each parameter in the coating surface parameters with exposure time are continuously recorded; the dynamic correction coefficient is calculated in real time according to the hydrolysis degree of zinc yellow pigment, the dynamic correction coefficient updates the gloss loss rate threshold, the color difference threshold, the contact angle threshold, the defect area threshold and the corrosion current density threshold in the coating surface parameters in the last period by a unified ratio, and a threshold set matched with the sample aging degree is obtained; The same batch of exposed test pieces sampled at the same time are observed by electron microscopy scanning, the microscopic defect area is obtained by using an image segmentation algorithm, the defect area proportion is calculated and the defect boundary complexity is quantitatively characterized, and the same batch of sampled exposed test pieces are tested by using an electrochemical workstation, the corrosion current density is obtained by Tafel extrapolation method; The five measurement results of the gloss loss rate, the color difference value, the water droplet contact angle, the defect area proportion and the corrosion current density in the coating surface parameters measured in the present period are compared with the threshold set obtained by dynamic updating, when the five measurement results are all higher than the corresponding threshold in the threshold set, coating complete failure judgment information is output.

[0005] Compared with the prior art, the present application has the following advantages: The application provides a surface defect detection method for an aluminum alloy plate member with an epoxy coating, which comprises the following steps: an aluminum alloy plate member substrate is subjected to an anodic oxidation treatment to form an oxide film, and an epoxy resin coating doped with zinc yellow pigment is coated on the surface of the oxide film as a whole; by using the characteristic that the zinc yellow pigment gradually releases chromate ions after being damp and forms a color indicating band on the inside of the coating and the edge of the defect, a color difference indicating system capable of self-repairing with service time is constructed to obtain a coating test piece as a subsequent detection object; the coating test piece is placed in a coastal atmospheric exposure environment, and at preset time intervals, the exposed test piece is sampled and detected, the coating surface parameters of the exposed test piece are measured respectively, and the change curves of the coating surface parameters with exposure time are continuously recorded; a dynamic correction coefficient is calculated in real time according to the hydrolysis degree of the zinc yellow pigment, the dynamic correction coefficient is used to update the light loss rate threshold value, the color difference threshold value, the contact angle threshold value, the defect area threshold value and the corrosion current density threshold value in the coating surface parameters in the last period by a unified ratio to obtain a threshold value set matched with the aging degree of the sample; the exposed test pieces sampled at the same period are observed by electron microscopy, the microscopic defect regions are obtained by using an image segmentation algorithm, the defect area proportion is calculated and the defect boundary complexity is quantitatively characterized, and the sampled exposed test pieces of the same batch are tested by using an electrochemical workstation to obtain a polarization curve, and the corrosion current density is obtained by Tafel extrapolation method; the five measurement results of the light loss rate, the color difference value, the water droplet contact angle, the defect area proportion and the corrosion current density in the coating surface parameters measured in the current period are compared with the threshold value set obtained by dynamic updating, and when the five measurement results are all higher than the corresponding threshold values in the threshold value set, coating complete failure determination information is output. By the method, the hydrolysis behavior of the zinc yellow pigment can be tracked in real time, multiple threshold values can be automatically corrected, and optical, topographic and electrochemical information can be fused to accurately evaluate the failure risk of the epoxy coated aluminum alloy plate member under the coastal service condition. 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: Fig. 1 FIG. 1 is a flowchart of a surface defect detection method for an aluminum alloy plate member with an epoxy coating according to an embodiment of the application; Fig. 2 FIG. 2 is a micro-morphology comparison diagram of coating surface defects of an aluminum alloy plate member with an epoxy coating after different exposure times according to an embodiment of the application; wherein a corresponds to 7 years of exposure, b corresponds to 12 years of exposure, and c corresponds to 20 years of exposure. DETAILED DESCRIPTION

[0007] In order to make the personnel in the technical field better understand the present application, the technical solutions in the embodiments will be clearly and completely described in combination with the drawings in the embodiments. 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 other embodiments obtained by the person of ordinary skill in the art without creative labor should belong to the protection scope of the present application.

[0008] Referring to Figs. 1-2 The present embodiment provides a kind of detection method of surface defect of aluminum alloy plate with epoxy coating, comprising the following steps: S101, the aluminum alloy plate substrate is subjected to anodic oxidation treatment to form an oxide film, and the oxide film surface is coated with zinc yellow pigment doped epoxy resin coating; using the characteristics that zinc yellow pigment gradually releases chromate ions after being damp and forms color indicating band inside the coating and at the defect edge, a color difference indicating system that can self-repair with service time is constructed to obtain a coating test piece as a subsequent detection object; S102, the coating test piece is placed in a coastal atmospheric exposure environment, and at predetermined time intervals, the exposed test piece is sampled and detected, the coating surface parameters of the exposed test piece are measured, and the variation curves of each parameter in the coating surface parameters with exposure time are continuously recorded; simultaneously, a dynamic correction coefficient is calculated in real time according to the degree of hydrolysis of zinc yellow pigment, the dynamic correction coefficient updates the light loss rate threshold, color difference threshold, contact angle threshold, defect area threshold and corrosion current density threshold in the coating surface parameters of the previous period by a uniform ratio to obtain a threshold set matched with the aging degree of the sample; S103, the same period sampling exposed test piece is observed by electron microscope scanning, the micro defect area is obtained by image segmentation algorithm, the defect area proportion is calculated and the defect boundary complexity is quantitatively characterized, and the polarization curve test of the same batch of exposed test pieces is carried out by electrochemical workstation, and the corrosion current density is obtained by Tafel extrapolation method; S104, the five measurement results of light loss rate, color difference value, water droplet contact angle, defect area proportion and corrosion current density in the coating surface parameters measured in the present period are compared with the threshold set obtained by dynamic updating, when the five measurement results are all higher than the corresponding threshold in the threshold set, coating complete failure determination information is output.

[0009] It should be noted that in the present embodiment, the zinc-doped yellow pigment in the epoxy coating releases chromium ions, which form a color change band in the damaged area of the coating, achieving early defect visualization and improving the intuitiveness and responsiveness of defect identification. The dynamic correction coefficient is calculated using the hydrolysis behavior of zinc yellow pigment, and the threshold values are adaptively adjusted based on the aging degree of the sample, so that the detection standard is automatically updated over time, avoiding false judgments caused by fixed static thresholds. By comparing and judging five types of data including light loss rate, color difference value, water droplet contact angle, defect area ratio and corrosion current density, the robustness and accuracy of failure judgment are enhanced, and the uncertainty of single index judgment is reduced.

[0010] It should be noted that in the present embodiment, the scanning electron microscope is used in combination with an image segmentation algorithm to automatically identify microscopic defect areas without relying on human experience, thereby improving the accuracy and consistency of defect identification, especially for small cracks, corrosion points or unevenly distributed peeling areas, high-resolution detection and objective quantitative analysis can be achieved. By calculating the defect area ratio, the proportion of the damaged area in the entire sample surface is quantified, providing a numerical index of the degradation degree of the coating, which provides a basis for subsequent life prediction, grading warning and coating performance evaluation. By analyzing the defect boundary morphology (such as complexity indicators such as fractal dimension), the defect morphology is described, which helps to distinguish different types of defects (such as pitting, linear cracking, and peeling) and trace the formation mechanism, thereby improving the adaptability to complex defects. The polarization curve test is performed on the electrochemical workstation, and the corrosion current density is obtained by Tafel extrapolation method, which reflects the corrosion sensitivity of the material in the service environment, making up for the limitations of optical and morphology indicators, and providing intuitive and quantitative support for the electrochemical behavior of the material. By combining the morphology change with the electrochemical corrosion data, multi-dimensional consistency verification is achieved, effectively improving the reliability and robustness of failure judgment.

[0011] It should be noted that in the present embodiment, the anodic oxide film refers to a dense oxide layer generated on the surface of aluminum alloy by electrochemical anodic oxidation, which is used to improve corrosion resistance and adhesion. Zinc yellow pigment refers to a chromium-containing anticorrosive pigment that can release chromium ions slowly in a humid environment, and has corrosion inhibition and color indication functions. The color difference indication system refers to the visible color difference area formed by the reaction of the zinc yellow pigment exudate and the corrosion area, which is used to judge the local failure of the coating. The coating surface parameters refer to quantifiable parameters for characterizing the performance changes of the coating, including light loss rate, color difference, water droplet contact angle, etc. The dynamic correction coefficient refers to the rate calculated in real time according to the hydrolysis release degree of zinc yellow pigment, which is used to update the aging threshold to adapt to the judgment accuracy requirements of different exposure stages. The Tafel extrapolation method refers to a standard method for calculating the corrosion current density in electrochemical testing, which is obtained by extrapolating the logarithmic linear region of the polarization curve. The corrosion current density refers to a parameter representing the electrochemical corrosion degree of the coating, and the larger the value, the more serious the corrosion.

[0012] Preferably, the measurement of the gloss loss rate is carried out by a standard gloss meter, at least twenty measurement points on the surface of the test piece are detected under the condition of uniform incident angle, and the arithmetic mean value after excluding the edge effect is taken as the gloss loss rate of the period, and the threshold value of the gloss loss rate is obtained by exponential decay fitting of the gloss decay curve in the early exposure period. Among them, by setting the uniform incident angle condition, sampling at multiple points (not less than twenty) on the surface of the test piece, and excluding the abnormal value interference of the edge area, the accidental error and the influence of local unevenness of the surface caused by single point test can be reduced, so that the average value of the measured gloss loss rate is more accurate and has statistical representativeness, which ensures the repeatability and stability of the evaluation result. After excluding the edge effect, the arithmetic mean value is taken as the gloss loss rate of the period, which can eliminate the interference area of mechanical shearing, inconsistent thickness or surface inhomogeneity in the edge area of the coating, avoid the deviation of the overall measurement value caused by the abnormal optical response of the edge area, and ensure that the data truly reflects the service state of the center area of the coating from the source. The threshold value of the gloss loss rate is obtained by exponential decay fitting of the gloss decay curve in the early exposure period, which not only can set the criterion based on the decay law of the sample itself, but also can adapt to the differences of samples in different batches and different exposure environments, improve the scientificity and pertinence of the determination threshold, and provide reliable support for subsequent failure warning.

[0013] Preferably, the water droplet contact angle in the coating surface parameter of the exposed test piece is determined by a rotating drop analyzer, thirty measurement points of each sampling test piece are randomly selected for testing, and Kolmogorov-Smirnov test is used to ensure that the measurement data is normally distributed; under the condition that the significance level P>0.05 is met, the coating surface free energy is calculated by the following formula: ; in the formula is the dispersion component, is the polar component; when the coating surface free energy monotonically increases with exposure time and its first derivative is higher than the threshold derivative calculated by the zinc yellow hydrolysis rate, the contact angle parameter is set to an out-of-limit state.

[0014] It should be noted that conventional contact angle measurement usually only takes a small amount of fixed point data. In this embodiment, thirty measurement points are randomly selected from each sample, and the normal distribution is verified by Kolmogorov-Smirnov test. Skewed distribution or outliers are actively excluded to ensure the representativeness of the sample and the robustness of the data, reduce the interference of accidental factors such as coating roughness and local pollution on the results. In addition, the rotating drop shape analyzer can continuously and more accurately complete multi-point testing on the same platform, avoiding the liquid drop volume fluctuation and light path error caused by manual sample change; combined with the random point selection strategy, the uniform sampling of large sample surface is realized. In this way, this embodiment breaks through the limitation of conventional static drop single point measurement, making the contact angle result more sensitive to progressive defects such as coating light loss and cracking on large area. Moreover, this embodiment does not stop at the static comparison of the absolute value of surface free energy, but calculates the surface free energy of the coating in real time With the monotonic increase of exposure time, the threshold value derived from the hydrolysis rate of zinc yellow pigment is compared, and the hydrophilization transition point of the coating is dynamically determined, so that the key node of the imminent exhaustion of pigment corrosion inhibition ability can be identified in advance. When the surface free energy increases above the threshold, the contact angle index is automatically marked as over-limit, enhancing the overall determination sensitivity. Among them, the Kolmogorov-Smirnov test (K-S test for short) is a non-parametric statistical test method, which is used to judge whether a group of sample data conforms to a known distribution.

[0015] Preferably, when the micro-defect area is obtained by using the image segmentation algorithm, the defect area ratio is calculated, and the defect boundary complexity is quantitatively characterized, the method comprises: performing binaryzation processing on the image obtained by scanning the electron microscope, and determining the gray threshold value by using the Otsu adaptive algorithm, so that the defect pixels and the non-defect pixels are optimally separated under the condition of global variance maximization; the proportion of the defect pixels to the total pixels is counted to obtain the defect area ratio, the boundary of each defect connected domain is coordinate-sampled, the fractal dimension D is calculated by using the image fractal analysis algorithm, and the fractal dimension D is used as the only measurement index of the boundary complexity; and the natural dyeing effect of continuously releasing chromate and forming a visible chromate halo at the edge of the defect depression of the zinc yellow pigment is utilized to provide a color reference for defect boundary extraction. It should be noted that, in the embodiment, the binaryzation processing is performed on the image obtained by scanning the electron microscope, and the gray threshold value is determined by using the Otsu adaptive algorithm, so that the defect pixels and the non-defect pixels are optimally separated under the condition of global variance maximization, thereby avoiding the problem of unstable segmentation effect of the fixed threshold method under different brightness and different background textures, enhancing the robustness to the complex morphology surface, and making the defect recognition stable in high-contrast and low-contrast images. The proportion of the defect pixels to the total pixels is counted to obtain the defect area ratio, the boundary of each defect connected domain is coordinate-sampled, the fractal dimension D is calculated by using the image fractal analysis algorithm, and the fractal dimension D is used as the only measurement index of the boundary complexity, so that the originally subjective judgment of the edge roughness, the contour complexity and other boundary descriptions can be uniformly represented in digital form, which is helpful to further judge whether the defect is an erosion type, a diffusion type or a tearing type, and provides more diagnostic morphological features. The natural dyeing effect of continuously releasing chromate and forming a visible chromate halo at the edge of the defect depression of the zinc yellow pigment is utilized to provide a color reference for defect boundary extraction, so as to realize the edge blurred image caused by the unclear gray transition of the edge or the complex surface relief, and improve the physical correspondence and interpretability of the segmentation contour.

[0016] Preferably, the numerical value of the fractal dimension D is obtained by linear fitting of the double logarithmic scale of the perimeter L of the defect area boundary and the corresponding area A, the mathematical model of the fitting is: logL=k·logA+b, D=2(k + 1); for the same defect connected domain, if the growth rate ΔD / Δt of the fractal dimension obtained in the adjacent two exposure samplings exceeds the critical growth rate curve mapped by the zinc yellow pigment hydrolysis rate r through the empirical function, it is determined that the defect has entered the rapid out-of-control stage from the slow expansion stage; k is the slope of the fitting straight line, indicating the response degree of the defect boundary complexity to the area change; b is the intercept of the fitting straight line, reflecting the initial value of the boundary growth at the starting scale. It should be noted that in the embodiment, the calculation model of the fractal dimension is established through the double logarithmic fitting relationship between the perimeter of the defect area boundary and the area, so that the complexity of the defect boundary can be accurately quantified by a mathematical formula, solving the limitations of relying only on area or subjective judgment of morphology. At the same time, the embodiment not only focuses on the static value of the fractal dimension, but also provides the growth rate of the fractal dimension as a dynamic criterion between continuous samplings, and further compares it with the critical growth rate curve constructed by the zinc yellow pigment hydrolysis rate. When it is detected that the complexity growth rate of the defect boundary exceeds the critical value, it is determined that the defect has entered the rapid out-of-control stage, thereby triggering the early warning. Compared with the method of only focusing on static geometric parameters or relying on a single corrosion index, the embodiment realizes the deep coupling of image morphology evolution and pigment chemical reaction behavior, and has stronger predictability and foresight.

[0017] Preferably, the specific steps of the polarization curve test of the same batch of exposure test pieces by the electrochemical workstation include: connecting the exposure test pieces to a standard electrochemical test system, the standard electrochemical test system including a three-electrode configuration of a working electrode, a reference electrode and an auxiliary electrode, wherein the working electrode is the coating test piece; placing the test piece in a set electrolyte before testing, and starting testing after stabilization treatment; applying a continuously changing potential to the working electrode by the electrochemical workstation, and synchronously recording the response current to obtain the curve data of the potential-current relationship; selecting the stable region from the obtained potential-current relationship curve, and analyzing the anodic and cathodic trend parts of the stable region to determine the position of the corrosion potential according to the curve slope change trend, and deducing the corresponding corrosion current density. It should be noted that in the embodiment, the polarization curve test of the same batch of exposure test pieces is carried out in a three-electrode system, and the slope analysis is carried out on the linear sections of the anode and the cathode, so as to accurately position the corrosion potential and deduce the corrosion current density, thereby utilizing continuous potential scanning and whole section trend fitting to filter out transient noise and polarization fluctuations, and giving more stable and repeatable corrosion current density results. According to the curve slope change trend, the position of the corrosion potential is determined, and the corresponding corrosion current density is deduced, thereby improving the accuracy of coating corrosion state quantification.

[0018] Preferably, the specific steps for determining the location of the corrosion potential based on the trend of the curve slope and deriving the corresponding corrosion current density include: organizing and preprocessing the potential and current response data collected during the electrochemical test to remove interference segments and unstable segments; identifying the linear trend regions of the anodic and cathodic regions in the preprocessed potential-current relationship curve; performing fitting analysis on the potential and logarithmic current data of the two regions respectively; determining the corrosion potential reflecting the electrochemical stable state of the test piece by the intersection of the fitted curves; and extrapolating the corrosion current density at the corrosion potential location based on the fitted trend. It should be noted that in this embodiment, the polarization curve data is structured through the linear trend identification of the anodic and cathodic regions and the logarithmic current-potential data fitting strategy, significantly improving the scientific rigor and reliability of corrosion current density extraction. It no longer relies on manual point selection or single-interval slopes, but systematically identifies the most representative linear response region in the curve. By fitting the slopes of the anodic and cathodic regions respectively and determining their intersection locations, the corrosion potential is accurately defined and the corrosion current density is extrapolated, thereby avoiding the problems of noise interference and strong subjectivity in data selection in the traditional Tafel method. In addition, this embodiment also removes unstable and interfering segments through data preprocessing, which effectively enhances the consistency and representativeness of the fitting interval and improves the robustness of corrosion rate judgment.

[0019] Preferably, the specific steps for organizing and preprocessing the potential and current response data collected during the electrochemical testing process to remove interference and unstable regions include: completely exporting the raw test data output from the electrochemical workstation and constructing a data sequence according to the correspondence between potential and current; performing preliminary screening on the constructed data sequence to eliminate obvious abrupt changes caused by electrode polarization instability or contact noise at the beginning of the test, and identifying and removing nonlinear convergence or distorted data caused by the end of the scan; and smoothing the remaining data region to remove local current fluctuation interference. It should be noted that in this embodiment, by implementing systematic preprocessing of the raw polarization curve data, higher accuracy and repeatability are achieved in the electrochemical analysis. Specifically, the complete data is first exported and a sequence is constructed according to the potential and current order to ensure that no sampling information is lost in subsequent processing. Then, a regular screening process is used to automatically remove unstable polarization of the starting electrode, sudden changes in contact noise, and nonlinear distortion sections at the end of the scan, effectively avoiding subjective errors caused by manual truncation. Finally, a smoothing operation is performed on the remaining sequence to eliminate local current jitter and make the data show a regular monotonic trend, which is convenient for accurate fitting of the linear regions of the anode and cathode.

[0020] Preferably, the specific steps for synchronously calculating the dynamic correction coefficient in real time based on the degree of hydrolysis of zinc yellow pigment include: in each sampling cycle, collecting hydrolysis-related signals of zinc yellow pigment in real time. These signals are obtained by detecting changes in the absorbance of chromate in the coating exudate or reading the color difference value of the coating color indicator band, and recording the difference between the hydrolysis-related signals and the reference signal of the previous cycle; inputting the collected hydrolysis-related signals into a pre-established mapping model, which converts the hydrolysis signals into a hydrolysis process index to characterize the relative degree of zinc yellow pigment hydrolysis in the current cycle; and retrieving the corresponding dynamic correction coefficient based on the hydrolysis process index. The dynamic correction coefficient maintains a monotonic relationship with the degree of hydrolysis, reflecting the magnitude of the impact of pigment-released chromate on the attenuation of coating protective performance. It should be noted that in this embodiment, by tracking the amount of chromate exudation in real time through absorbance or color difference, the pigment corrosion inhibition activity can be continuously quantified without damaging the coating, improving monitoring frequency and on-site applicability. In addition, in this embodiment, the hydrolysis signal is converted into a hydrolysis process index to characterize the relative degree of hydrolysis of zinc yellow pigment in the current period. The corresponding dynamic correction coefficient is retrieved according to the hydrolysis process index. The dynamic correction coefficient maintains a monotonic relationship with the degree of hydrolysis to reflect the influence of pigment slow-release chromate on the attenuation of coating protective performance, thereby avoiding early false alarms or late omissions due to chemical slow-release effect of fixed threshold.

[0021] Preferably, the specific steps for updating the threshold values ​​of gloss loss rate, color difference, contact angle, defect area, and corrosion current density in the coating surface parameters of the previous cycle with the dynamic correction coefficient at a uniform multiple to obtain a threshold set matching the aging degree of the sample include: after obtaining the dynamic correction coefficient for the current cycle, calling the basic threshold set stored in the previous cycle, which contains the original judgment reference values ​​for the five coating surface parameters; judging the change trend of the degree of zinc yellow pigment hydrolysis in the current cycle compared to the previous cycle, and confirming whether the direction of the dynamic correction coefficient is to relax or tighten; applying the dynamic correction coefficient to the basic threshold set to uniformly adjust the threshold values ​​of the five coating surface parameters, with the adjustment rules applied to the threshold values ​​of gloss loss rate, color difference, contact angle, defect area, and corrosion current density according to the set weight factors; performing boundary verification on the adjusted threshold values ​​to ensure that the updated results are not lower than the set minimum reference safety threshold, nor exceed the allowed maximum stable threshold range; updating the verified adjustment results to the effective threshold set for the current cycle, and using it for failure comparison of the measurement results in this cycle, while storing this threshold set as the basic threshold set for the next cycle. It should be noted that in this embodiment, the basic threshold of the previous cycle is first called, and then the threshold should be tightened or loosened automatically based on the changes in pigment hydrolysis. The five parameters are adjusted uniformly according to the preset weight to ensure that each index remains relatively balanced under the same decay scale. Then, upper and lower boundaries are set to prevent the threshold from being infinitely amplified or reduced due to short-term fluctuations, and to maintain the safe and effective range of the judgment standard. Finally, the new threshold set that has been verified is immediately put into the comparison of the current cycle and used as the benchmark for the next cycle to realize closed-loop recursive update. This achieves multi-parameter synchronous, adaptive, and controlled threshold management, which can continuously track the chemical self-healing decay and physical damage accumulation in the coating aging process and improve the accuracy and timeliness of failure warning.

[0022] Furthermore, the specific steps for calculating the dynamic correction coefficient in real time include: measuring the concentration of chromate ions generated by the hydrolysis of zinc yellow pigment on the surface of the coated test piece in real time, and establishing a chromate concentration curve characterizing the degree of hydrolysis of zinc yellow pigment based on the rate of change of chromate ion concentration at different exposure stages; calculating the real-time slope of the chromate concentration curve using a sliding window time series analysis method to determine the dynamic trend of the hydrolysis rate of zinc yellow pigment with exposure time, and identifying the trend inflection point based on a preset slope change threshold; automatically adjusting the update ratio of the dynamic correction coefficient according to the trend inflection point identification result, wherein the correction coefficient ratio is increased when the hydrolysis rate accelerates beyond the threshold, and decreased when the hydrolysis rate slows down below the threshold. It should be noted that in this embodiment, by monitoring the chromate ion release rate in real time and automatically adjusting the dynamic correction coefficient ratio based on the trend inflection point, the problem of threshold update lag caused by the nonlinear change of the zinc yellow pigment hydrolysis rate is effectively solved, improving the threshold adaptation accuracy and the real-time performance and reliability of coating failure determination.

[0023] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting surface defects in epoxy-coated aluminum alloy plates, characterized in that, include: Anodizing is performed on the aluminum alloy plate substrate to form an oxide film, and an epoxy resin coating containing zinc yellow pigment is applied to the surface of the oxide film. Taking advantage of the characteristic that zinc yellow pigment gradually releases chromate ions after being exposed to moisture and forms color indicator bands inside the coating and at the edge of defects, a color difference indicator system that can self-heal over service time is constructed to obtain a coating test piece as the object of subsequent testing. The coated test specimens were placed in a coastal atmospheric exposure environment, and samples were taken and tested at preset time intervals. The surface parameters of the coating on the exposed test specimens were measured, and the change curves of each parameter on the surface of the coating with the exposure time were continuously recorded. Simultaneously, a dynamic correction coefficient was calculated in real time based on the degree of hydrolysis of zinc yellow pigment. The dynamic correction coefficient was updated at a uniform ratio to the gloss loss rate threshold, color difference threshold, contact angle threshold, defect area threshold, and corrosion current density threshold of the coating surface parameters in the previous cycle, so as to obtain a set of thresholds that match the aging degree of the sample. Electron microscopy was used to observe the exposed test specimens sampled at the same time. The micro-defect region was obtained by image segmentation algorithm, the defect area ratio was calculated and the defect boundary complexity was quantitatively characterized. The polarization curve of the same batch of exposed test specimens was tested by electrochemical workstation, and the corrosion current density was obtained by Tafel extrapolation method. The five measurement results of the coating surface parameters measured in this cycle—gloss loss rate, color difference value, water droplet contact angle, defect area ratio, and corrosion current density—are compared with the dynamically updated threshold set. When all five measurement results are higher than the corresponding threshold in the threshold set, the coating complete failure judgment information is output.

2. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 1, characterized in that, The gloss loss rate was measured using a standard gloss meter. At least twenty measuring points on the surface of the test piece were tested under a uniform incident angle. After excluding edge effects, the arithmetic mean was taken as the gloss loss rate for the current period. The threshold for the gloss loss rate was obtained by fitting the gloss decay curve of the early exposure period with an exponential decay.

3. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 1, characterized in that, The water droplet contact angle in the surface parameters of the coating on the exposed test specimens was determined using a rotating droplet analyzer. Thirty measurement points were randomly selected for each sampled specimen, and the Kolmogorov-Smirnov test was used to ensure that the measurement data were normally distributed. Under the condition that the significance level P>0.05 was met, the surface free energy of the coating was calculated using the following formula: In the formula For the dispersion component, It is a polar component; when the surface free energy of the coating is... When the contact angle parameter exhibits a monotonically increasing trend with exposure time and its first derivative exceeds the threshold derivative calculated from the zinc yellow hydrolysis yield, the contact angle parameter is set to an out-of-limit state.

4. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 1, characterized in that, When using image segmentation algorithms to obtain microscopic defect regions, calculate the defect area ratio, and quantitatively characterize the defect boundary complexity, the process includes: performing binarization processing on the images obtained from electron microscopy scanning; determining the grayscale threshold using the Otsu adaptive algorithm to achieve optimal separation between defective and non-defective pixels under the condition of maximizing global variance; statistically analyzing the ratio of defective pixels to total pixels to obtain the defect area ratio; sampling the coordinates of the boundaries of each defect connected region; calculating the fractal dimension D using an image fractal analysis algorithm; and using the fractal dimension D as the sole metric for boundary complexity. Finally, utilizing the natural staining effect of zinc yellow pigment continuously releasing chromate ions at the edge of the defect depression and forming a visible chromate halo provides a color reference for defect boundary extraction.

5. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 4, characterized in that, The fractal dimension D is obtained by linearly fitting the perimeter L of the defect region boundary to the corresponding area A on a double logarithmic scale. The mathematical model for fitting is: logL=k·logA+b, D=2(k+1). For the same defect connected region, if the growth rate ΔD / Δt of the fractal dimension obtained in two adjacent exposure samplings exceeds the critical growth rate curve obtained by mapping the zinc yellow pigment hydrolysis rate r through an empirical function, then the defect is determined to have entered the rapid runaway stage from the slow expansion stage. k is the slope of the fitted line, which represents the degree of response of the defect boundary complexity to the area change. b is the intercept of the fitted line, which reflects the initial value of the boundary growth at the initial scale.

6. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 1, characterized in that, The specific steps for using an electrochemical workstation to test polarization curves of the same batch of exposed test specimens and obtaining the corrosion current density using the Tafel extrapolation method include: The exposed test specimen is connected to a standard electrochemical testing system, which includes a three-electrode configuration of a working electrode, a reference electrode, and an auxiliary electrode, wherein the working electrode is the coated test specimen; before testing, the test specimen is placed in a set electrolytic medium and tested after stabilization treatment; By applying a continuously varying potential to the working electrode using an electrochemical workstation and simultaneously recording the response current, a potential-current relationship curve is obtained. A stable region is selected from the obtained potential-current relationship curve, and the anodic and cathodic trends of the stable region are analyzed. Based on the trend of the curve slope, the location of the corrosion potential is determined, and the corresponding corrosion current density is derived.

7. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 6, characterized in that, The specific steps for determining the location of the corrosion potential based on the trend of the curve slope and deriving the corresponding corrosion current density include: organizing and preprocessing the potential and current response data collected during the electrochemical test to remove interference segments and unstable segments; identifying the linear trend regions of the anodic and cathodic regions in the preprocessed potential-current relationship curve; performing fitting analysis on the potential and logarithmic current data of the two regions respectively; determining the corrosion potential reflecting the electrochemical stable state of the test piece by the intersection of the fitted curves; and extrapolating the corrosion current density at the corrosion potential location based on the fitted trend.

8. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 7, characterized in that, The specific steps for organizing and preprocessing the potential and current response data collected during the electrochemical test to remove interference and unstable regions include: exporting the original test data output from the electrochemical workstation in its entirety and constructing a data sequence according to the correspondence between potential and current; performing preliminary screening on the constructed data sequence to remove obvious abrupt changes caused by electrode polarization instability or contact noise at the beginning of the test, and identifying and removing nonlinear convergence or distorted data caused by the end of the scan at the end; and smoothing the remaining data region to remove local current fluctuation interference.

9. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 1, characterized in that, The specific steps for synchronously calculating the dynamic correction coefficient in real time based on the degree of hydrolysis of zinc yellow pigment include: Within each sampling period, the hydrolysis-related signals of zinc yellow pigment are collected in real time. The hydrolysis-related signals are obtained by detecting the change in absorbance of chromate in the coating exudate or by reading the color difference value of the coating color indicator band, and the difference between the hydrolysis-related signals and the reference signals of the previous period is recorded. The collected hydrolysis-related signals are input into a pre-established mapping model, which converts the hydrolysis signals into hydrolysis process indicators to characterize the relative degree of hydrolysis of zinc yellow pigment in the current period. The corresponding dynamic correction coefficient is retrieved based on the hydrolysis process indicator. The dynamic correction coefficient maintains a monotonic relationship with the degree of hydrolysis and is used to reflect the magnitude of the effect of pigment slow-release chromate on the attenuation of coating protective performance.

10. The method for detecting surface defects in epoxy-coated aluminum alloy plates according to claim 1, characterized in that, The specific steps for updating the gloss loss rate threshold, color difference threshold, contact angle threshold, defect area threshold, and corrosion current density threshold of the coating surface parameters in the previous cycle according to a uniform multiple, to obtain a threshold set that matches the aging degree of the sample, include: After obtaining the dynamic correction coefficient for the current period, the basic threshold set stored in the previous period is called. The basic threshold set contains the original judgment reference values ​​for the five coating surface parameters. Determine the trend of the degree of hydrolysis of zinc yellow pigment in the current cycle compared to the previous cycle, and confirm whether the dynamic correction coefficient is to be relaxed or tightened. Apply the dynamic correction coefficient to the basic threshold set and uniformly adjust the thresholds of the five coating surface parameters. The adjustment rules are applied to the thresholds of gloss loss rate, color difference, contact angle, defect area and corrosion current density according to the set weight factors. Boundary verification is performed on the adjusted thresholds to ensure that the updated results are not lower than the set minimum reference safety threshold and do not exceed the allowed maximum stable threshold range. The verified adjustment results are updated as the effective threshold set for the current period and used for failure comparison of the measurement results in this period. At the same time, this threshold set is stored as the basic threshold set for the next period.

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