Quantification method and system for coating immersion corrosion extent

Abstract

The application discloses a kind of coating soaking corrosion degree quantification method and system, the method comprises: controlling light source makes coating surface brightness uniform and invariable, the surface image of coating before soaking and after soaking under different soaking time is obtained by image acquisition equipment;Surface image is preprocessed, and gray image is obtained;According to the gray value of the gray image of coating before soaking, determine the gray threshold value;The pixel point of the gray value of the gray image of coating after soaking below gray threshold value is classified as corrosion point, and the number ratio of corrosion point is calculated as the quantification index of uniform corrosion degree;Closed small hole in gray image is filled using morphological filling;Closed region in filled gray image is detected and extracted, and the ratio of total area of closed region and total area of gray image is calculated as the quantification index of point corrosion degree.The surface image of coating is collected by controlling light source stability, and the quantification of uniform corrosion and point corrosion degree is realized using 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, etc. 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 scrap 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 may 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. The 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] The commonly used methods for quantitatively analyzing the corrosion degree of the material are the weighing method, the thickness measurement method and the 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 the roughness, cleanliness and oxide film of the electrode surface may 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 the existing method for analyzing the corrosion degree of the material, and to propose a coating immersion corrosion degree quantification method and system.

[0008] In order to achieve the above purpose, the present application adopts the following technical solutions:

[0009] A coating immersion corrosion degree quantification method, comprising the following steps:

[0010] 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 immersion at different immersion times through an image acquisition device;

[0011] S11, pre-process each surface image to obtain a gray image;

[0012] S12, determine the gray threshold of the coating according to the gray value of the gray image of the coating before immersion;

[0013] S13, classify the pixel points with a gray value lower than the gray threshold of the gray image of the coating after immersion as corrosion points, and calculate the corrosion point number ratio as a quantification index of uniform corrosion degree.

[0014] In some embodiments, step S11 comprises: 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.

[0015] In some embodiments, step S12 comprises: traversing and sorting the gray values of the entire image of the gray image of the coating before immersion, and taking the gray value lower than 99% of the pixel points as the gray threshold of the coating.

[0016] 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.

[0017] The application also provides a coating immersion corrosion degree quantification method, comprising the following steps:

[0018] 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 immersion at different immersion times through an image acquisition device;

[0019] S21, pre-process each surface image to obtain a gray image;

[0020] S22, fill the closed small holes in the gray image by using morphological operation;

[0021] 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 quantification index of point corrosion degree.

[0022] In some embodiments, step S21 comprises: filtering and enhancing the contrast of each surface image by using an image processing tool to obtain a pre-processed gray image.

[0023] In some embodiments, a Gaussian filter is used for filtering processing; and histogram equalization is used for enhancing contrast.

[0024] In some embodiments, step S22 comprises: performing a closing operation on the gray-scale image by using a structure element to fill closed small holes.

[0025] In some embodiments, step S23 comprises: detecting and extracting closed regions in the filled gray-scale image by using an edge detection algorithm, removing noise points, and calculating a ratio of a total area of the closed regions to a total area of the gray-scale image.

[0026] The application further provides a coating immersion corrosion degree quantification system, comprising:

[0027] A light source control module is configured to control the light source to make the coating surface brightness uniform and constant.

[0028] 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.

[0029] An image processing module is configured to pre-process each surface image and obtain a gray-scale image.

[0030] A corrosion analysis module comprises:

[0031] A uniform corrosion analysis unit is configured to determine a gray-scale threshold of the coating according to a 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 a total number of the corrosion points divided by a total pixel as a quantification index of the uniform corrosion degree.

[0032] A point corrosion analysis unit is configured to fill closed small holes in the gray-scale image by using morphological operation, detect and extract closed regions in the filled gray-scale image, and calculate a ratio of a total area of the closed regions to a total area of the gray-scale image as a quantification index of the point corrosion degree.

[0033] The application has the following beneficial effects compared with the prior art:

[0034] The coating immersion corrosion degree quantification method and system provided by the application can acquire surface images of the coating stably by controlling the light source, pre-process the surface images to obtain gray-scale images, determine corrosion points by setting a gray-scale threshold, and calculate a ratio of the number of the corrosion points as a quantification index of the uniform corrosion degree. Meanwhile, the morphological image processing is combined to fill closed small holes in the gray-scale image, detect and extract closed regions in the filled gray-scale image, and calculate a ratio of a total area of the closed regions to a total area of the gray-scale image as a quantification index of the point corrosion degree. Thus, the coating immersion corrosion degree can be quantified comprehensively and accurately.

[0035] In some embodiments, the present application also has the following beneficial effects:

[0036] By closing operation to fill the closed small holes in the gray scale image, an edge detection algorithm is used to detect and extract the closed region in the filled gray scale image, and small noise points are removed, and the ratio of the total area of the closed region to the total area of the gray scale image is calculated, to further improve the quantitative accuracy of the coating immersion corrosion degree.

[0037] Other beneficial effects of the embodiments of the present application will be further described below. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 is a flowchart of a coating immersion uniform corrosion degree quantification method of the embodiments of the present application.

[0039] Figure 2 is a flowchart of a coating immersion point corrosion degree quantification method of the embodiments of the present application.

[0040] Figures 3a to 3g is a gray scale change result graph of a Q235 steel test piece in the process of immersion for 0-30 days according to the embodiments of the present application.

[0041] Figures 4a to 4g is a gray scale change result graph of a 45CT wire material coating steel test piece in the process of immersion for 0-30 days according to the embodiments of the present application.

[0042] Figures 5a to 5g is a gray scale change result graph of a ZnAl wire material coating steel test piece in the process of immersion for 0-30 days according to the embodiments of the present application.

[0043] Figure 6 is a uniform corrosion change graph of a Q235 steel test piece in the process of immersion for 0-30 days according to the embodiments of the present application.

[0044] Figure 7 is a uniform corrosion change graph of a 45CT wire material coating steel test piece in the process of immersion for 0-30 days according to the embodiments of the present application.

[0045] Figure 8 is a uniform corrosion change graph of a ZnAl wire material coating steel test piece in the process of immersion for 0-30 days according to the embodiments of the present application.

[0046] Figure 9 is a uniform corrosion result error bar graph of a Q235 steel test piece in the process of immersion for 0-30 days according to the embodiments of the present application.

[0047] Figure 10 is a uniform corrosion result error bar graph of a 45CT wire material coating steel test piece in the process of immersion for 0-30 days according to the embodiments of the present application.

[0048] Figure 11is the error bar chart of the uniform corrosion result of the sprayed ZnAl wire material coating steel test piece in the embodiment of the application during 0-30 days of immersion.

[0049] Figure 12 is the point corrosion change chart of the Q235 steel test piece in the embodiment of the application during 0-30 days of immersion.

[0050] Figure 13 is the point corrosion change chart of the sprayed 45CT wire material coating steel test piece in the embodiment of the application during 0-30 days of immersion.

[0051] Figure 14 is the potentiodynamic polarization curve chart of the Q235, 45CT and ZnAl steel test pieces in the embodiment of the application during 48h of immersion.

[0052] Figure 15 is the Bode change chart of the electrochemical impedance spectrum of the Q235 steel test piece in the embodiment of the application during 0-16 days of immersion.

[0053] Figure 16 is the Bode change chart of the electrochemical impedance spectrum of the 45CT steel test piece in the embodiment of the application during 0-16 days of immersion.

[0054] Figure 17 is the Bode change chart of the electrochemical impedance spectrum of the ZnAl steel test piece in the embodiment of the application during 0-16 days of immersion. DETAILED DESCRIPTION

[0055] The 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.

[0056] It should be noted that the left, right, up, down, top, bottom and the like in the present embodiment are relative concepts or are referenced to the normal use state of the product, and should not be considered as limiting.

[0057] As shown in Figure 1 , the embodiment of the application provides a coating immersion corrosion degree quantification method, which comprises the following steps:

[0058] S10, control the light source to make the coating surface brightness uniform and always unchanged, and acquire the surface images of the coating before and after immersion at different immersion times through an image acquisition device.

[0059] S11, pretreat each surface image to obtain a gray image. Specifically, an image processing tool is used to calculate the average values of R, G and B of each surface image by using the average value method, so as to obtain a soft gray image.

[0060] S12, determine the gray threshold of the coating according to the gray value of the gray image of the coating before soaking. Specifically, the gray value of the entire image of the gray image of the coating before soaking is traversed and sorted, and the gray value lower than 99% of the pixel points is taken as the gray threshold of the coating.

[0061] S13, the pixel points with the gray value lower than the gray threshold of the gray image of the coating after soaking are classified as corrosion points, and the corrosion point number ratio is calculated as a quantitative index of uniform corrosion degree. The corrosion point number ratio is: the total number of pixel points of all corrosion points divided by the total pixel.

[0062] As shown in Figure 2 The embodiment of the application also provides a coating soaking corrosion degree quantification method, which comprises the following steps:

[0063] S20, control the light source to make the coating surface brightness uniform and always unchanged, and acquire the surface images of the coating before and after soaking at different soaking times through the image acquisition device.

[0064] S21, pre-process each surface image to obtain a gray image. Specifically, the image processing tool is used to filter and enhance the contrast of each surface image to obtain the pre-processed gray image. The Gaussian filter is used for filtering, and the histogram equalization is used to enhance the contrast.

[0065] S22, fill the closed small holes in the gray image by morphological operation. Specifically, the closed operation is performed on the gray image by the structural element to fill the closed small holes.

[0066] S23, detect and extract the closed region in the filled gray image, and calculate the ratio of the total area of the closed region to the total area of the gray image as a quantitative index of point corrosion degree. Specifically, the edge detection algorithm is used to detect and extract the closed region in the filled gray image, and the small noise points are removed, and the ratio of the total area of the closed region to the total area of the gray image is calculated.

[0067] The embodiment of the application also provides a coating soaking corrosion degree quantification system, which comprises:

[0068] A light source control module is used to control the light source to make the coating surface brightness uniform and always unchanged.

[0069] An image acquisition module comprises an image acquisition device, and is used to acquire the surface images of the coating before and after soaking at different soaking times.

[0070] An image processing module is used to pre-process each surface image and obtain a gray image.

[0071] A corrosion analysis module comprises:

[0072] The uniform corrosion analysis unit is used for determining a gray threshold of the coating according to a gray value of a gray image of the coating before soaking, and then classifying pixel points of the gray image of the coating after soaking and having a gray value lower than the gray threshold as corrosion points, and calculating a total pixel number of all the corrosion points divided by total pixels as a quantitative index of the uniform corrosion degree.

[0073] The point corrosion analysis unit is used for filling closed small holes in the gray image by using morphological operation, detecting and extracting closed regions in the gray image after filling, and calculating a ratio of a total area of the closed regions to a total area of the gray image as a quantitative index of the point corrosion degree.

[0074] The coating soaking corrosion degree quantification method provided by the embodiment of the application has the following principles:

[0075] 1. The surface brightness of the coating is kept consistent by controlling an external light source, and surface images of the coating test piece at different soaking times before and after soaking are obtained; the surface image of the coating is preprocessed to mainly quantify the uniform corrosion degree and the point corrosion degree.

[0076] 2. The uniform corrosion is a most common corrosion form, and the characteristic of the uniform corrosion is that the metal surface corrodes at a substantially same rate in a corrosion medium; the surface of the coating after uniform corrosion becomes dark. The surface image of the coating is preprocessed to obtain a gray image, and based on the characteristic of the 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 is: the corrosion causes the change of the microstructure or the composition of the material surface, and then affects the light reflection / scattering characteristics, and finally shows the change of the gray value. The metal corrosion is usually accompanied by the generation of an oxide film (such as iron rust Fe2O3·nH2O), and the thickness, compactness 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 slowly decreases, and the change of the gray value enters a platform period. Therefore, compared with the gray value of the initial coating which has not been subjected to soaking corrosion, if the gray value of the same pixel point of the coating subjected to soaking corrosion decreases, the point can be defined as being subjected to uniform corrosion.

[0077] 3. The point corrosion is a highly localized corrosion form, and for the coating subjected to point corrosion, needle-shaped or pit-shaped corrosion holes are formed on the surface, and the corrosion image presents a closed small hole shape. By using the dilation, erosion, opening operation and closing operation of mathematical morphology, the metal surface image is processed, the deep pits of the point corrosion are highlighted, and thus the point corrosion degree is effectively quantified.

[0078] There are few methods for quantifying the corrosion degree at present, 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 uniform corrosion degree and point corrosion degree, the surface images of the coating before and after immersion corrosion are acquired through a high-precision image acquisition device, and the image processing function is used to realize comprehensive and accurate quantification of the coating corrosion degree in immersion corrosion.

[0079] The specific embodiments and experimental verification of the present application are further described below.

[0080] The coating immersion corrosion degree quantification method provided in the embodiment can be realized by using tools such as MATLAB, Python and the like, but is not limited thereto. 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 controlling consistent brightness, and a new method for quantifying the corrosion degree is proposed. Specifically, the method comprises the following steps.

[0081] 1. The external light source providing brightness for the high-precision image acquisition device (FT-U3630 optical microscope) is kept stable by controlling the external light source, and the external environment is isolated from the external light source. The light source parameters are modified and fixed after one-time automatic exposure and automatic white balance of the light source to make the photos close to the real object. The exposure gain is 1.190, the exposure time is 114.273 ms, the saturation is 100, the cold and warm color is 6500, the red gain is 2.130, the green gain is 1.000, and the blue gain is 1.946. The light intensity is monitored and fed back (an uncorroded test sample is placed in the field of view before each shooting, and the gray value of the corrected image is kept unchanged by adjusting the parameters of the image to eliminate the influence of light source drift), so that the brightness of the coating surface is always consistent. The surface images of the coating at different immersion times before and after immersion are acquired, and the exposure, red, blue and green gains, and the saturation and cold and warm color of the color of the device are adjusted to prevent interference with the gray value of the image.

[0082] 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, the following steps are performed.

[0083] (1) For quantification of the uniform corrosion degree, the pre-processing of the coating surface image comprises the following steps: based on MATLAB, the average value method is used to calculate the average values of R, G and B (representing the colors of the red, green and blue channels) of each surface image, R=G=B=(R+G+B) / 3, and the average value method forms a softer gray image, thereby obtaining a gray image.

[0084] (2) For the quantification of the degree of point corrosion, the preprocessing of the coating surface image includes: filtering and enhancing the contrast of the coating surface image based on MATLAB to obtain the preprocessed gray image. Among them, the Gaussian filter is used for filtering: a [5 5] Gaussian kernel is generated, and the Gaussian kernel is convolved with the image I to smooth the image and suppress high-frequency noise. Enhance contrast: use histogram equalization to enhance contrast, the corrosion area may present low gray value due to low light reflectivity, histogram equalization enhances the contrast of these areas by redistributing the gray level, which is convenient for subsequent edge detection or threshold segmentation.

[0085] 3. For the initial coating gray image that has not been subjected to immersion corrosion, find the gray value below 99% of the pixel points and take it as the gray threshold 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 threshold close to 100%, but it cannot be 100% because the gray threshold of 100% is actually the lowest gray value of the entire gray image, which is easy to cause errors, so the gray threshold of 99% is selected); for the gray image of the coating subjected to immersion corrosion, the pixel points with a gray value lower than the above-mentioned gray threshold are classified as corrosion points, and the total number of pixel points of all corrosion points is divided by the total pixel points to obtain an index for quantifying the uniform corrosion degree. The uniform corrosion degree of the initial coating is 1% by default.

[0086] 4. At the same time, the morphological operation of closing is used to fill the closed small holes in the gray 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 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. After removing small noise points, the total closed area is divided by the total image area to obtain an index for quantifying the degree of point corrosion.

[0087] Experimental Example 1: Quantification of uniform corrosion of small steel test pieces

[0088] 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 coated with 45CT wire and steel test pieces coated with ZnAl wire.

[0089] Test the light using the blank test piece that has 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 value based on MATLAB. The observation results show that the surface gray value of the same test piece remains unchanged at different times, indicating that the external light source is stable.

[0090] Three kinds of coating samples were placed in a 3.5wt% NaCl (sodium chloride) solution, each piece of the sample was marked in different regions, and the total immersion time at room temperature 25℃ was 30 days. The corrosion morphology of the coating surface was recorded by an industrial camera at 0, 5, 10, 15, 20, 25, 30 days.

[0091] The corrosion condition was evaluated by using the MATLAB-based coating immersion corrosion degree quantification method. The gray scale change results of Q235 steel test piece, sprayed 45CT wire material coating (corrosion product is black) and sprayed ZnAl wire material coating (corrosion product is bright white) steel test piece are shown in Figures 3a to 3g , Figures 4a to 4g , Figures 5a to 5g respectively. The uniform corrosion quantification results are shown in Figures 6 to 8 , Figures 9 to 11 respectively. It can be seen that the surface image of 45CT before and after immersion changes little, the corrosion resistance is higher, the surface metal bright color remains good, and the gray value of the three materials tends to 0 with the increase of immersion time, which represents the greater the corrosion degree.

[0092] The cross-validation experiment was adopted, and the results of the method were compared with those of the electrochemical method (potentiodynamic polarization curve and electrochemical impedance spectrum):

[0093] Figure 14 The potentiodynamic polarization curves of the two are shown in the figure. It can be seen that the self-corrosion potential (mV) of 45CT is -863.34 mV, the self-corrosion potential of Q235 is -915.96 mV, the self-corrosion potential 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, the corrosion current of Q235 is 5.01418 μA, the corrosion current of ZnAl is 58.6408 μA, 45CT< Q235< ZnAl (the smaller the corrosion current, the lower the corrosion rate).

[0094] Figure 15 , Figure 16 , Figure 17 The Bode plots of the electrochemical impedance spectrum of the three are shown in the figure. It can be seen that the impedance values of Q235 and ZnAl decrease obviously with the increase of immersion time, while the impedance values of 45CT change little before and after immersion.

[0095] Therefore, the electrochemical method is consistent with the conclusion obtained by the method.

[0096] Experimental example 2: point corrosion quantification of small steel test piece

[0097] The corrosion test pieces with the size of 50mm*50mm*5mm are prepared, including Q235 steel test pieces as blank control group and steel test pieces with 45CT wire spraying coating, three kinds of coating test samples are placed in 3.5wt% NaCl solution, each piece of test sample is marked in different regions, the total immersion time is 30 days at room temperature 25℃, the corrosion morphology of coating surface at 0, 5, 10, 15, 20, 25, 30 days is recorded by industrial camera;

[0098] The corrosion condition is evaluated by using the quantification method of coating immersion corrosion degree based on MATLAB, the point corrosion quantification results of Q235 steel test piece and 45CT wire spraying coating steel test piece are shown in Figures 12 to 13 It can be seen that 45CT mainly occurs point corrosion, and Q235 mainly occurs uniform corrosion.

[0099] The above content is further detailed description of the present application combined with specific preferred embodiments, and cannot be regarded as limitation of the specific implementation of the present application to these descriptions. For the skilled in the art to which the present application belongs, without departing from the concept of the present application, a number of equivalent alternatives or obvious variations can be made, and the performance or use is the same, which should be regarded as belonging to the protection scope of the present application.

Claims

1. A method for quantifying the degree of corrosion during coating immersion, characterized in that, Includes the following steps: S10. Control the light source to ensure uniform and constant brightness on the coating surface. Acquire surface images of the coating before and after immersion at different immersion times using an image acquisition device. Specifically, after performing one automatic exposure and automatic white balance of the light source, modify and fix the parameters to make the photo approximate the real object. Compare and select an exposure gain of 1.190, an exposure time of 114.273ms, a saturation of 100, a warm / cool color of 6500, a red gain of 2.130, a green gain of 1.000, and a blue gain of 1.

946. Before each shot, place an uncorroded test piece in the field of view and correct the various parameters of the image to keep the grayscale value constant, eliminating the influence of light source drift. S11. Preprocess each surface image to obtain a grayscale image. Specifically, this includes using image processing tools and the averaging method to calculate the average values ​​of R, G, and B for each surface image, thereby obtaining a smooth grayscale image. S12. Determine the grayscale threshold of the coating based on the grayscale value of the grayscale image of the coating before immersion. Specifically, this includes: traversing and sorting the grayscale values ​​of the entire image of the grayscale image of the coating before immersion, and taking the grayscale values ​​of pixels below 99% as the grayscale threshold of the coating. S13. Pixels with gray values ​​lower than the gray threshold in the grayscale image of the coating after immersion are classified as corrosion points, and the proportion of corrosion points is calculated as a quantitative indicator of the degree of uniform corrosion.

2. The method for quantifying the degree of coating immersion corrosion as described in claim 1, characterized in that, In step S13, the percentage of the number of etched points is: the sum of the number of pixels of all etched points divided by the total number of pixels.

3. A method for quantifying the degree of corrosion during coating immersion, characterized in that, Includes the following steps: S20. Control the light source to ensure uniform and constant brightness on the coating surface. Acquire surface images of the coating before and after immersion at different immersion times using an image acquisition device. Specifically, this includes: performing an automatic exposure and automatic white balance of the light source, modifying and fixing parameters to make the photo approximate the real object, and comparing and selecting an exposure gain of 1.190, an exposure time of 114.273ms, a saturation of 100, a warm / cool color of 6500, a red gain of 2.130, a green gain of 1.000, and a blue gain of 1.

946. Before each shot, place an uncorroded test piece in the field of view and correct the various parameters of the image to keep the grayscale value constant, thus eliminating the influence of light source drift. S21. Preprocess each surface image to obtain a grayscale image. Specifically, this includes using image processing tools and the averaging method to calculate the average values ​​of R, G, and B for each surface image, thereby obtaining a smooth grayscale image. S22. Use morphological operations to fill closed holes in a grayscale image; S23. Detect and extract closed regions in the filled grayscale image, and calculate the ratio of the total area of ​​the closed regions to the total area of ​​the grayscale image as a quantitative indicator of the degree of point erosion.

4. The method for quantifying the degree of coating immersion corrosion as described in claim 3, characterized in that, Step S21 includes: using image processing tools to filter and enhance the contrast of each surface image to obtain a preprocessed grayscale image.

5. The method for quantifying the degree of coating immersion corrosion as described in claim 4, characterized in that, A Gaussian filter is used for filtering; histogram equalization is used to enhance contrast.

6. The method for quantifying the degree of coating immersion corrosion as described in claim 4, characterized in that, Step S22 includes: performing a closing operation on the grayscale image using a structuring element to fill the closed hole.

7. The method for quantifying the degree of coating immersion corrosion as described in claim 3, characterized in that, Step S23 includes: using an edge detection algorithm to detect and extract closed regions in the filled grayscale image, removing noise points, and calculating the ratio of the total area of ​​the closed regions to the total area of ​​the grayscale image.

8. A system for quantifying the degree of corrosion during coating immersion, characterized in that, include: The light source control module is used to control the light source to ensure that the brightness of the coating surface is uniform and remains constant. The image acquisition module, including an image acquisition device, is used to acquire surface images of the coating at different immersion times before and after immersion. Specifically, it includes: performing an automatic exposure and automatic white balance of the light source, modifying and fixing parameters to make the photo approximate the real object, and comparing and selecting an exposure gain of 1.190, an exposure time of 114.273ms, a saturation of 100, a warm / cool color of 6500, a red gain of 2.130, a green gain of 1.000, and a blue gain of 1.

946. Before each shot, an uncorroded test piece is placed in the field of view, and the grayscale values ​​of the image are kept constant by correcting the various parameters of the image to eliminate the influence of light source drift. The image processing module is used to preprocess the images of each surface to obtain grayscale images. Specifically, it includes: using image processing tools and the averaging method to calculate the average values ​​of R, G, and B of each surface image, thereby obtaining a smooth grayscale image. The corrosion analysis module includes: The uniform corrosion analysis unit is used to determine the grayscale threshold of the coating based on the grayscale value of the grayscale image of the coating before immersion. Specifically, it includes: traversing and sorting the grayscale values ​​of the entire image of the grayscale image of the coating before immersion, taking the grayscale values ​​of pixels below 99% as the grayscale threshold of the coating, classifying the pixels with grayscale values ​​below the grayscale threshold in the grayscale image of the coating after immersion as corrosion points, and calculating the total number of pixels of all corrosion points divided by the total number of pixels as a quantitative index of the degree of uniform corrosion. The pitting corrosion analysis unit is used to fill closed holes in a grayscale image using morphological operations, detect and extract closed areas in the filled grayscale image, and calculate the ratio of the total area of ​​the closed area to the total area of ​​the grayscale image as a quantitative indicator of the degree of pitting corrosion.

Images