Method and system for quantifying immersion corrosion degree of coating

Abstract

The invention discloses a method and system for quantifying the immersion corrosion degree of a coating, and the method comprises the steps: controlling a light source to enable the surface brightness of the coating to be uniform and unchanged, and obtaining surface images of the coating at different immersion times before and after immersion through image collection equipment; preprocessing the surface image to obtain a grayscale image; determining a gray threshold according to the gray value of the gray image of the coating before soaking; classifying pixel points of which the gray value of the gray image of the soaked coating is lower than a gray threshold value as corrosion points, and calculating the proportion of the number of the corrosion points as a quantitative index of the uniform corrosion degree; filling the closed small holes in the grayscale image by adopting morphology; and detecting and extracting a closed region in the filled grayscale image, and calculating the ratio of the total area of the closed region to the total area of the grayscale image as a quantitative index of the spot corrosion degree. According to the method, the surface image of the coating is acquired by controlling the stability of the light source, and the quantification of uniform corrosion and spot corrosion degrees is respectively realized by utilizing gray value and morphological image processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of material corrosion evaluation, in particular to a coating immersion corrosion degree quantification method and system. BACKGROUND

[0002] With the acceleration of the world industrialization process, various metal materials, alloys and the like are widely used in infrastructure construction, petrochemical industry, energy development, electronic information and other key fields. Corrosion is the main reason for the destruction of metal materials, leading to the destruction and scrapping of various infrastructure and engineering equipment.

[0003] Marine corrosion causes serious harm to marine engineering facilities and marine equipment. It not only shortens the service life of facilities and equipment, increases maintenance and replacement costs, but also can cause structural strength to decrease, leading to safety accidents, and poses a great threat to marine ecological environment and human life and property safety. For example, after being corroded by seawater for a long period of time, key components of offshore oil platforms may crack or even break, and once an accident occurs, not only will it cause huge economic losses, but also may cause serious marine environmental pollution incidents. Corrosion of ships will reduce their navigation safety, increase fuel consumption and affect operational efficiency.

[0004] Immersion corrosion experiment, as a classic and basic method of marine corrosion research, simulates the corrosion conditions under actual working conditions by completely immersing the material sample in the corrosion medium, so as to quantitatively or qualitatively analyze the corrosion degree of the material.

[0005] Common methods for quantitatively analyzing the corrosion degree of materials include weighing method, thickness measurement method and electrochemical test method. The weighing method determines the corrosion rate by measuring the weight change of the material before and after corrosion, and the thickness measurement method evaluates the corrosion degree by measuring the thickness change of the material or component. The results of the two methods are relatively rough and not accurate. Electrochemical testing has strict requirements for the test environment and the surface state of the electrode. Factors such as roughness, cleanliness and oxide film of the electrode surface can cause instability of the test signal and deviation of the test results.

[0006] It should be noted that the information disclosed in the above background section is only for understanding the background of the present application, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0007] The purpose of the present application is to solve the technical problem of low accuracy of existing methods for analyzing the corrosion degree of materials, and to propose a coating immersion corrosion degree quantification method and system.

[0008] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions: A coating immersion corrosion degree quantification method, comprising the following steps: S10, control the light source to make the coating surface brightness uniform and always remain unchanged, and obtain the surface images of the coating before and after soaking at different soaking times through an image acquisition device; S11, pre-process each surface image to obtain a gray image; S12, determine the gray threshold of the coating according to the gray value of the gray image of the coating before soaking; S13, classify the pixel points with a gray value lower than the gray threshold of the gray image of the coating after soaking as corrosion points, and calculate the corrosion point number ratio as a quantitative index of the uniform corrosion degree.

[0009] In some embodiments, step S11 includes: using an image processing tool, using the average value method to obtain the average values of R, G and B of each surface image, so as to obtain a soft gray image.

[0010] In some embodiments, step S12 includes: traversing and sorting the gray values of the entire image of the gray image of the coating before soaking, and taking the gray value lower than 99% of the pixel points as the gray threshold of the coating.

[0011] In some embodiments, in step S13, the corrosion point number ratio is: the total number of pixel points of all corrosion points divided by the total pixel points.

[0012] The application also provides a coating soaking corrosion degree quantification method, comprising the following steps: S20, control the light source to make the coating surface brightness uniform and always remain unchanged, and obtain the surface images of the coating before and after soaking at different soaking times through an image acquisition device; S21, pre-process each surface image to obtain a gray image; S22, fill the closed small holes in the gray image by using morphological operation; S23, detect and extract the closed regions in the filled gray image, and calculate the ratio of the total area of the closed regions to the total area of the gray image as a quantitative index of the point corrosion degree.

[0013] In some embodiments, step S21 includes: using an image processing tool to filter and enhance the contrast of each surface image to obtain a pre-processed gray image.

[0014] In some embodiments, a Gaussian filter is used for filtering processing, and a histogram equalization is used for enhancing contrast.

[0015] In some embodiments, step S22 includes: performing a closing operation on the gray image by using a structure element to fill the closed small holes.

[0016] In some embodiments, step S23 comprises: detecting and extracting the closed region in the filled gray-scale image by using an edge detection algorithm, removing noise points, and calculating the ratio of the total area of the closed region to the total area of the gray-scale image.

[0017] The application further provides a coating immersion corrosion degree quantification system, comprising: A light source control module is configured to control the light source to make the coating surface brightness uniform and constant. An image acquisition module comprises an image acquisition device and is configured to acquire surface images of the coating before and after immersion at different immersion times. An image processing module is configured to pre-process each surface image and obtain a gray-scale image. A corrosion analysis module comprises: A uniform corrosion analysis unit is configured to determine a gray-scale threshold of the coating according to the gray-scale value of the gray-scale image of the coating before immersion, classify pixel points with a gray-scale value lower than the gray-scale threshold of the gray-scale image of the coating after immersion as corrosion points, and calculate the total number of the pixel points divided by the total pixels as a quantification index of the uniform corrosion degree. A point corrosion analysis unit is configured to fill closed small holes in the gray-scale image by using morphological operation, detect and extract the closed region in the filled gray-scale image, and calculate the ratio of the total area of the closed region to the total area of the gray-scale image as a quantification index of the point corrosion degree.

[0018] The application has the following beneficial effects compared with the prior art: The coating immersion corrosion degree quantification method and system provided by the application can acquire the surface images of the coating stably by controlling the light source, pre-process the surface images to obtain gray-scale images, determine the corrosion points by setting the gray-scale threshold, and calculate the number ratio of the corrosion points as the quantification index of the uniform corrosion degree. Meanwhile, the morphological image processing is combined to fill the closed small holes in the gray-scale image, detect and extract the closed region in the filled gray-scale image, and calculate the ratio of the total area of the closed region to the total area of the gray-scale image as the quantification index of the point corrosion degree, so that the comprehensive and accurate quantification of the coating immersion corrosion degree is realized.

[0019] In some embodiments, the application has the following beneficial effects: The closed small holes in the gray-scale image are filled by the closing operation, the closed region in the filled gray-scale image is detected and extracted by using the edge detection algorithm, small noise points are removed, the ratio of the total area of the closed region to the total area of the gray-scale image is calculated, and the quantification accuracy of the coating immersion corrosion degree is further improved.

[0020] Other beneficial effects of the embodiments of the application will be further described below. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 is a flow chart of a coating immersion uniform corrosion degree quantification method of an embodiment of the present application.

[0022] Figure 2 is a flow chart of a coating immersion pitting corrosion degree quantification method of an embodiment of the present application.

[0023] Figures 3a to 3g is a gray scale map change result graph of a Q235 steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0024] Figures 4a to 4g is a gray scale map change result graph of a 45CT wire material coating steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0025] Figures 5a to 5g is a gray scale map change result graph of a ZnAl wire material coating steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0026] Figure 6 is a uniform corrosion change graph of a Q235 steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0027] Figure 7 is a uniform corrosion change graph of a 45CT wire material coating steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0028] Figure 8 is a uniform corrosion change graph of a ZnAl wire material coating steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0029] Figure 9 is a uniform corrosion result error bar graph of a Q235 steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0030] Figure 10 is a uniform corrosion result error bar graph of a 45CT wire material coating steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0031] Figure 11 is a uniform corrosion result error bar graph of a ZnAl wire material coating steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0032] Figure 12 is a pitting corrosion change graph of a Q235 steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0033] Figure 13 is a pitting corrosion change graph of a 45CT wire material coating steel test piece during immersion for 0-30 days of an embodiment of the present application.

[0034] Figure 14is a potentiodynamic polarization curve diagram of Q235, 45CT and ZnAl steel test pieces soaked for 48h in an embodiment of the present application.

[0035] Figure 15 is a Bode change diagram of electrochemical impedance spectroscopy of Q235 steel test pieces during soaking for 0-16 days in an embodiment of the present application.

[0036] Figure 16 is a Bode change diagram of electrochemical impedance spectroscopy of 45CT steel test pieces during soaking for 0-16 days in an embodiment of the present application.

[0037] Figure 17 is a Bode change diagram of electrochemical impedance spectroscopy of ZnAl steel test pieces during soaking for 0-16 days in an embodiment of the present application. DETAILED DESCRIPTION

[0038] The present application will be further described below with reference to the drawings and in conjunction with preferred embodiments. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0039] It should be noted that the left, right, up, down, top, bottom and other orientation terms in the embodiments are only relative concepts or are referenced to the normal use state of the product, and should not be considered as limiting.

[0040] As shown in Figure 1 , the present embodiment provides a method for quantifying the corrosion degree of a coating, comprising the following steps: S10, controlling the light source to make the surface brightness of the coating uniform and always unchanged, and acquiring the surface images of the coating before and after soaking at different soaking times through an image acquisition device.

[0041] S11, pre-processing each surface image to obtain a gray image. Specifically, using an image processing tool, the average value method is used to obtain the average values of R, G and B of each surface image, thereby obtaining a soft gray image.

[0042] S12, determining the gray threshold value of the coating according to the gray value of the gray image of the coating before soaking. Specifically, traversing and sorting the gray values of the entire image of the gray image of the coating before soaking, and taking the gray value lower than 99% of the pixel points as the gray threshold value of the coating.

[0043] S13, classifying the pixel points with a gray value lower than the gray threshold value of the gray image of the coating after soaking as corrosion points, and calculating the corrosion point number ratio as a quantitative index of the uniform corrosion degree. The corrosion point number ratio is: the total number of pixel points of all corrosion points divided by the total pixels.

[0044] As shown in Figure 2As shown, the embodiment of the present application also provides a coating immersion corrosion degree quantification method, comprising the following steps: S20, controlling the light source to make the coating surface brightness uniform and always remain unchanged, and acquiring the surface images of the coating before and after immersion at different immersion times through the image acquisition device.

[0045] S21, pre-processing each surface image to obtain a gray image. Specifically, filtering, contrast enhancement processing of each surface image is performed using an image processing tool to obtain a pre-processed gray image. Wherein, the filtering processing is performed using a Gaussian filter, and the contrast enhancement is performed using histogram equalization.

[0046] S22, filling the closed small holes in the gray image using morphological operation. Specifically, the closed small holes are filled by performing a closing operation on the gray image using a structure element.

[0047] S23, detecting and extracting the closed regions in the filled gray image, and calculating the ratio of the total area of the closed regions to the total area of the gray image as a point corrosion degree quantification index. Specifically, the closed regions in the filled gray image are detected and extracted using an edge detection algorithm, and small noise points are removed, and the ratio of the total area of the closed regions to the total area of the gray image is calculated.

[0048] The embodiment of the present application also provides a coating immersion corrosion degree quantification system, comprising: A light source control module for controlling the light source to make the coating surface brightness uniform and always remain unchanged; An image acquisition module comprising an image acquisition device for acquiring the surface images of the coating before and after immersion at different immersion times; An image processing module for pre-processing each surface image and obtaining a gray image; A corrosion analysis module comprising: A uniform corrosion analysis unit for determining the gray threshold of the coating according to the gray value of the gray image of the coating before immersion, and classifying the pixel points of the gray image of the coating after immersion whose gray value is lower than the gray threshold as corrosion points, and calculating the total number of all corrosion points divided by the total pixels as a uniform corrosion degree quantification index; A point corrosion analysis unit for filling the closed small holes in the gray image using morphological operation, detecting and extracting the closed regions in the filled gray image, and calculating the ratio of the total area of the closed regions to the total area of the gray image as a point corrosion degree quantification index.

[0049] The coating immersion corrosion degree quantification method provided by the embodiment of the present application has the following principles: 1. The surface brightness of the coating is kept consistent by controlling the external light source to obtain the surface images of the coating samples before and after immersion at different immersion times; the surface images of the coating are preprocessed to quantify the uniform corrosion degree and the pitting corrosion degree.

[0050] 2. Uniform corrosion is the most common form of corrosion, characterized by the fact that the metal surface corrodes at a substantially same rate in the corrosion medium, and the coating surface after uniform corrosion becomes dark. The preprocessed coating surface image obtains a gray image, based on the characteristics of uniform corrosion, the size change of the gray value reflects the corrosion degree, and the closer the gray value is to 0, the greater the corrosion degree: Corrosion will cause changes in the microstructure or composition of the material surface, thereby affecting the light reflection / scattering characteristics, and finally showing changes in the gray value. Metal corrosion is usually accompanied by the generation of an oxide film (such as rust Fe2O3·nH2O), and the thickness, density and surface roughness of the oxide film directly affect the light reflection characteristics: In the initial growth stage of the oxide film (thickness < critical value), the reflectivity approximately linearly decays with the film thickness d, and when the film thickness exceeds the critical value, the reflectivity decreases slowly, and the gray value change enters a plateau period. Therefore, compared with the gray value of the initial coating that has not been immersed and corroded, if the gray value of the same pixel point of the coating that has been immersed and corroded decreases, it can be defined that the point has been uniformly corroded.

[0051] 3. Pitting corrosion is a highly localized form of corrosion, and for the coating that has undergone pitting corrosion, needle-shaped or pit-shaped corrosion holes will be formed on the surface, and the corrosion image presents as a closed small hole. By mathematical morphology operations such as dilation, erosion, opening and closing, the metal surface image can be processed to highlight the pits of pitting corrosion, thereby effectively quantifying the degree of pitting corrosion.

[0052] Currently, there are few methods to quantify the corrosion degree, and the commonly used weighing method is not accurate enough. The coating immersion corrosion degree quantification method and system provided in the embodiment of the present application simultaneously includes the uniform corrosion degree and the pitting corrosion degree, the surface images of the coating before and after immersion corrosion are obtained by using high-precision image acquisition equipment, and the image processing function can be used to realize comprehensive and accurate quantification of the corrosion degree of the coating in the immersion corrosion.

[0053] The specific embodiments and experimental verification of the present application are further described below.

[0054] The embodiment provides a coating immersion corrosion degree quantification method, which can be realized by using but not limited to MATLAB, Python and the like. The method quantifies the corrosion degree of the coating at different immersion times by using the gray value and image processing under the condition of consistent brightness, and proposes a new method for quantifying the corrosion degree. Specifically, the method comprises the following steps:

[0055] 1. By controlling the external light source to provide the brightness for the high-precision image acquisition device (FT-U3630 optical microscope) to remain stable, while isolating the external environment of the clutter light source, quantifying the light source parameters (after the first automatic exposure and automatic white balance of the light source, modifying and fixing the parameters to make the photo close to the real object, by comparing and selecting the exposure gain as 1.190, the exposure time as 114.273 ms, the saturation as 100, the warm color as 6500, the red gain as 2.130, the green gain as 1.000, and the blue gain as 1.946), and implementing the monitoring and feedback of the light intensity (placing the un-etched test piece in the field of view before each shooting, keeping the gray value unchanged by correcting the image parameters, and eliminating the influence of light source drift), the coating surface brightness is always kept consistent, the surface images of the coating before and after immersion under different immersion times are obtained, and the exposure, red, blue and green gain, and the saturation and warm color of the color of the device are adjusted to prevent interference with the gray value of the image.

[0056] 2. The image processing and analysis function of MATLAB is used to pre-process the coating surface images before and after immersion corrosion to obtain a gray image. Specifically as follows:

[0057] (1) For the quantification of uniform corrosion degree, the pre-processing of the coating surface image includes: based on MATLAB, using the average method to calculate the average value of R, G and B (representing the colors of the three channels of red, green and blue) of each surface image, R=G=B=(R+G+B) / 3, and the average method will form a softer gray image, thereby obtaining a gray image.

[0058] (2) For the quantification of point corrosion degree, the pre-processing of the coating surface image includes: based on MATLAB, the surface image of the coating is filtered, the contrast is enhanced, and the like to obtain a pre-processed gray image. Among them, a Gaussian filter is used for filtering: a [5 5] Gaussian kernel is generated, the Gaussian kernel is convolved with the image I, thereby smoothing the image and suppressing high-frequency noise. The contrast is enhanced by using histogram equalization: the corrosion area may present low gray value due to low light reflectivity, and the histogram equalization enhances the contrast of these areas by redistributing the gray level, which is convenient for subsequent edge detection or threshold segmentation.

[0059] 3、For the initial coating gray scale image that has not been subjected to immersion corrosion, find the gray scale value below 99% of the pixel points and take it as the gray scale threshold value of the coating (in order to make the uniform corrosion degree of the initial uncorroded coating as low as possible, it is necessary to select a gray scale threshold value close to 100%, but it cannot be 100% because a gray scale threshold value of 100% is actually the lowest gray scale value of the entire gray scale image, which is prone to errors, so a gray scale threshold value of 99% is selected); for the gray scale image of the coating subjected to immersion corrosion, classify the pixel points with a gray scale value below the above-mentioned gray scale threshold value as corrosion points, and take the total number of pixel points of all corrosion points divided by the total pixels as an index for quantifying the uniform corrosion degree. The uniform corrosion degree of the initial coating is by default 1%.

[0060] 4、At the same time, the morphological operation of closing is used to fill the closed small holes in the gray scale image (the closing operation is a morphological operation used to fill the closed small holes (i.e. bright spots in dark areas or dark spots in bright areas) in the gray scale image or binary image, while smoothing the object boundary and removing small noise points), and then the edge detection algorithm is used to detect the closed holes (closed regions) in the image, and after removing small noise points, the total closed region area is divided by the total image area to obtain an index for quantifying the point corrosion degree.

[0061] Experimental Example 1: Quantification of uniform corrosion of small steel test pieces Prepare corrosion test pieces with a size of 50mm x 50mm x 5mm, including Q235 steel test pieces as a blank control group, steel test pieces with a 45CT wire coating and steel test pieces with a ZnAl wire coating.

[0062] Test the light using the blank test pieces that have not been subjected to immersion corrosion, record the coating image of the same test piece on the 0th, 5th and 10th days, and obtain the gray scale value based on MATLAB. The observation results show that the surface gray scale value of the same test piece remains unchanged at different times, indicating that the external light source is stable.

[0063] Place the three kinds of coating test samples in a 3.5wt% NaCl (sodium chloride) solution, mark each test piece by region, and immerse them in a room temperature of 25℃ for a total time of 30 days. Record the corrosion morphology of the coating surface on the 0th, 5th, 10th, 15th, 20th, 25th and 30th days using an industrial camera.

[0064] Use the quantification method of coating immersion corrosion degree based on MATLAB to evaluate the corrosion condition. The gray scale change results of the Q235 steel test pieces, the 45CT wire coating (the corrosion product is black) and the ZnAl wire coating (the corrosion product is bright white) steel test pieces are shown in Figures 3a to 3g , Figures 4a to 4g , Figures 5a to 5g respectively, and the uniform corrosion quantification results are shown in Figures 6 to 8As shown, the uniform corrosion error bar results are in turn as Figures 9 to 11 As shown, it can be seen that the surface image of 45CT before and after soaking changes little, the corrosion resistance is higher, the surface metal color remains good, and the gray value of the three materials tends to 0 as the soaking time increases, representing a greater degree of corrosion.

[0065] The results of the method and the electrochemical method (potentiodynamic polarization curve and electrochemical impedance spectroscopy) are compared by cross-validation experiment: Figure 14 The potentiodynamic polarization curves of the two are shown, it can be seen that the self-corrosion potential (mV) of 45CT is-863.34 mV, that of Q235 is-915.96 mV, and that of ZnAl is-1.1814 mV, 45CT>Q235>ZnAl (the lower the self-corrosion potential, the greater the corrosion tendency); the corrosion current (μA) of 45CT is 1.50904 μA, that of Q235 is 5.01418 μA, and that of ZnAl is 58.6408 μA, 45CT<Q235<ZnAl (the smaller the corrosion current, the lower the corrosion rate).

[0066] Figure 15 , Figure 16 , Figure 17 The Bode plots of the electrochemical impedance spectroscopy of the three are shown, it can be seen that the impedance values of Q235 and ZnAl decrease significantly with the increase of soaking time, while the impedance values of 45CT change little before and after soaking.

[0067] Therefore, the electrochemical method is consistent with the conclusion obtained by the method.

[0068] Experimental Example 2: Quantification of Pitting Corrosion of Small Steel Test Pieces Corrosion test pieces of 50 mm x 50 mm x 5 mm size were prepared, including Q235 steel test pieces as a blank control group and steel test pieces sprayed with 45CT wire coating, and the three coating samples were placed in 3.5wt% NaCl solution. Each piece of the test sample was labeled in different regions, and the corrosion morphology of the coating surface was recorded by an industrial camera at 0, 5, 10, 15, 20, 25, and 30 days at room temperature 25℃ for a total of 30 days; The quantification method of coating soaking corrosion degree based on MATLAB was used to evaluate the corrosion condition, and the pitting corrosion quantification results of Q235 steel test pieces and 45CT wire coating steel test pieces are in turn as Figures 12 to 13 As shown, it can be seen that 45CT mainly undergoes pitting corrosion, while Q235 mainly undergoes uniform corrosion.

[0069] The above is further detailed description of the present application in combination with specific preferred embodiments, and cannot be deemed as limitation of the specific implementation of the present application to these descriptions. For those skilled in the art to which the present application belongs, without departing from the concept of the present application, a number of equivalent substitutions or obvious variations can be made, and the performance or use is the same, which should be deemed as falling within the protection scope of the present application.

Claims

1. A method for quantifying the degree of immersion corrosion of a coating, characterized in that: The following steps are involved: S10, controlling the light source so that the brightness of the coating surface is uniform and remains constant, and obtaining surface images of the coating at different immersion times before and after immersion by an image acquisition device; S11, preprocessing each surface image to obtain a grayscale image; S12, determining a grayscale threshold of the coating according to the grayscale value of the grayscale image of the coating before immersion; S13. Classify the pixels of the grayscale image of the coating after immersion whose grayscale values ​​are lower than the grayscale threshold as corrosion points, and calculate the ratio of the number of corrosion points as a quantitative indicator of the degree of uniform corrosion.

2. The method for quantifying the degree of coating immersion corrosion according to claim 1, wherein: Step S11 includes: using an image processing tool and an average method to calculate the average values ​​of R, G, and B of each surface image, thereby obtaining a soft grayscale image.

3. The method for quantifying the degree of coating immersion corrosion according to claim 1, wherein: Step S12 includes: for the grayscale image of the coating before immersion, traversing and sorting the grayscale values ​​of the entire image, and taking the grayscale value of the pixel points below 99% as the grayscale threshold of the coating.

4. The method for quantifying the degree of coating immersion corrosion according to claim 1, wherein: In step S13, the percentage of the number of corrosion points is calculated as follows: the sum of the number of pixels of all corrosion points divided by the total number of pixels.

5. A method for quantifying the degree of immersion corrosion of a coating, characterized in that: The following steps are involved: S20, controlling the light source so that the brightness of the coating surface is uniform and remains constant, and obtaining surface images of the coating at different immersion times before and after immersion by an image acquisition device; S21, preprocessing each surface image to obtain a grayscale image; S22, using morphological operations to fill closed holes in the grayscale image; S23, detecting and extracting closed areas in the filled grayscale image, and calculating the ratio of the total area of ​​the closed areas to the total area of ​​the grayscale image as a quantitative indicator of the degree of pitting corrosion.

6. The method for quantifying the degree of coating immersion corrosion according to claim 5, characterized in that: Step S21 includes: using image processing tools to filter and enhance contrast of each surface image to obtain a pre-processed grayscale image.

7. The method for quantifying the degree of coating immersion corrosion according to claim 6, wherein: Gaussian filter is used for filtering; histogram equalization is used to enhance contrast.

8. The method for quantifying the degree of coating immersion corrosion according to claim 5, wherein: Step S22 includes performing a closing operation on the grayscale image using the structure element to fill the closed holes.

9. The method for quantifying the degree of coating immersion corrosion according to claim 5, wherein: Step S23 includes: using an edge detection algorithm to detect and extract closed areas in the filled grayscale image, removing noise points, and calculating the ratio of the total area of ​​the closed areas to the total area of ​​the grayscale image.

10. A system for quantifying the degree of immersion corrosion of a coating, characterized in that: include: Light source control module, used to control the light source so that the brightness of the coating surface is uniform and remains constant; An image acquisition module, including an image acquisition device, is used to acquire surface images of the coating before and after immersion at different immersion times; An image processing module, used for preprocessing each surface image and obtaining a grayscale image; Corrosion analysis module, including: a uniform corrosion analysis unit, configured to determine a grayscale threshold of the coating based on the grayscale value of the grayscale image of the coating before immersion, classify pixels in the grayscale image of the coating after immersion whose grayscale value is lower than the grayscale threshold as corrosion points, and calculate the sum of the number of pixels of all corrosion points divided by the total number of pixels as a quantitative indicator of the degree of uniform corrosion; The pitting corrosion analysis unit is used to fill the closed small holes in the grayscale image using morphological operations, detect and extract the closed areas in the filled grayscale image, and calculate the ratio of the total area of ​​the closed areas to the total area of ​​the grayscale image as a quantitative indicator of the pitting corrosion degree.

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