Anti-fouling coating aging simulation test method

Abstract

The invention provides a simulated aging test method for an antifouling coating. The simulated aging test method comprises the following steps: S1, constructing a natural aging performance model of the antifouling coating; s2, constructing an accelerated aging model of the antifouling coating and acquiring an acceleration ratio N of natural aging to accelerated aging; s3, based on an accelerated aging model, acquiring an acceleration period Mi corresponding to a critical threshold R (temporary i) of a copper ion exudation rate, wherein the predicted life Lp (temporary i) of the antifouling coating is equal to Mi * N; and S4, based on a natural aging model, obtaining a predicted copper ion exudation rate R < pre-i > corresponding to the predicted life Lp < pre->, judging whether R < pre-i >-R < critical i > / R < critical i > is less than or equal to 10%, if so, outputting a near threshold R < critical i > and the predicted life Lp < pre-i >, and if not, adjusting the critical threshold of the copper ion exudation rate to R < critical i + 1 > and returning to the step S3. According to the method, the performance failure threshold value of the antifouling coating is taken as a boundary condition, the performance of the antifouling coating is rapidly evaluated, the service life of the antifouling coating is quantitatively predicted, the prediction result is subjected to cooperative cross validation through linkage double models, and the reliability is improved.

Description

Technical Field

[0001] This invention relates to the field of marine antifouling technology, and more specifically, to a method for simulating aging tests of antifouling coatings. Background Technology

[0002] With the booming development of the global shipping industry, the problem of marine pollution is becoming increasingly serious. This not only accelerates the aging and corrosion of ship hulls and marine facilities, but also significantly increases navigation resistance and fuel consumption, which in turn exacerbates greenhouse gas emissions and environmental pollution.

[0003] Applying antifouling coatings to surfaces is currently the main method of antifouling. The film-forming resin base undergoes hydrolysis, polishing, and abrasion under the alternating effects of various marine environmental factors to release copper ions, thereby inhibiting the attachment and growth of fouling organisms. When the concentration of copper ions released on the coating surface is lower than the critical threshold for inhibiting bioattachment, it indicates that the antifouling coating has failed.

[0004] To address this, Chinese Patent Application No. 202080005863.1 discloses a rapid evaluation method for the exudation rate of antifouling agents in antifouling coatings. This method involves immersing the antifouling coating in an immersion solution, where the cuprous oxide in the coating accelerates the release of copper ions under the conditions of the immersion solution, thus quickly obtaining the copper ion exudation rate of the coating. However, because this method uses a complexing agent to accelerate the aging pathway of copper ion exudation, which is completely different from the actual aging pathway of copper ion release through resin peeling, it is only suitable for rapid screening of coating formulations in the laboratory. The simulated aging data obtained cannot provide a reliable criterion for rapid evaluation of the performance of antifouling coatings.

[0005] In view of this, the present invention is hereby proposed. Summary of the Invention

[0006] Based on the intrinsic mechanism of action of antifouling coatings, this invention develops a simulated aging test method to accelerate the aging process of coatings, providing effective guidance for the design, development and rapid evaluation of long-life, high-performance antifouling coating materials.

[0007] To address the above problems, this invention provides a method for simulating the aging of antifouling coatings, comprising the following steps:

[0008] S1. Construct a natural aging performance model for the antifouling coating;

[0009] S2. Construct an accelerated aging model for the antifouling coating and obtain the acceleration ratio N between natural aging and accelerated aging;

[0010] S3. Obtaining the critical threshold R of copper ion leaching rate based on the accelerated aging model. 临i The corresponding acceleration period M i The predicted lifespan L of the antifouling coating is... p预i =M i*N;

[0011] S4. Obtain the predicted lifespan L based on the natural aging model. p预 The corresponding predicted copper ion leaching rate R 预i Determine if |R 预i- R 临i | / R 临i If the threshold is ≤10%, then output the nearest threshold R. 临i and predicted lifespan L p预i If not, adjust the critical threshold for the copper ion leaching rate to R. 临i+1 Then return to step S3.

[0012] Preferably, the natural aging performance model is constructed using the following method:

[0013] S11. Select antifouling coating materials and conduct shallow sea immersion experiments, regularly record environmental data, immersion time and obtain coating performance parameters;

[0014] Specifically, the environmental conditions for the shallow sea immersion experiment are: bays in the Yellow Sea, East China Sea, and South China Sea where marine life is thriving and the current is less than 2 m / s; seawater temperature of 20-30℃; seawater salinity of 30‰-34‰; and monitoring and inspection frequency of 0.5-1 month / time. The environmental data include temperature, salinity, dissolved oxygen, ammonia nitrogen, nitrate, phosphate, and nitrite. The coating performance parameters include the total copper content of the coating and the copper ion leaching rate. The specific testing methods refer to GB / T31409 and GB / T6824. The antifouling coating materials include short-term, medium-term, and long-term antifouling coatings. The immersion time for short-term antifouling coatings is 3-6 months, for medium-term antifouling coatings it is 6-12 months, and for long-term antifouling coatings it is at least 12 months.

[0015] S12. Use the feature data in the environmental data and performance parameters obtained in step S11 as feature parameters, and use principal component analysis and linear discriminant analysis to perform dimension reduction and noise reduction on the feature parameters. The feature data are the statistical values ​​of different data.

[0016] S13. Divide the multiple sets of data obtained in step S12 into a test set and a validation set. Use the environmental features and immersion time obtained after dimensionality reduction in the test set as input values, and use the performance parameters of the antifouling coating in the test set as output values. Construct a natural aging performance model using one or more of the following algorithms: support vector machine, neural network, principal component analysis, random forest, and XGBoost. Specifically, the data volume of the test set accounts for 60% to 80%, the data volume of the validation set accounts for 40% to 20%, and the total data volume is 10 to 120 sets.

[0017] S14. Input the environmental data and immersion time from the validation set into the natural aging performance model constructed in S13 to obtain the predicted values ​​of the coating performance. Compare these predicted values ​​with the measured values ​​of the coating performance in the validation set and calculate the correlation coefficient R between the two. 2 When R 2 When the accuracy is ≥70%, the prediction results are reliable.

[0018] Preferably, the accelerated aging model is constructed using the following method:

[0019] S21. Select antifouling coating materials and conduct dynamic accelerated tests, record the accelerated test conditions and parameters regularly, and obtain coating performance data;

[0020] The dynamic acceleration test was conducted in accordance with GB / T7789 and GB / T31411, using a disc-type or drum-type device installed in a real sea environment such as a floating raft, natural seawater pool, or natural seawater tank. The test conditions were: rotational linear speed of 25-35 knots, seawater temperature of 20-30℃, and seawater salinity of 30‰-34‰. Each cycle lasted 150-200 hours. The coating performance parameters included the total copper content and copper ion leaching rate of the coating. The specific testing methods were in accordance with GB / T31409 and GB / T6824.

[0021] S22. The characteristic data of the accelerated test condition parameters and performance data obtained in step S21 are used as characteristic parameters. Principal component analysis and linear discriminant analysis are used to reduce the dimension and noise of the characteristic parameters. The characteristic data are the statistical values ​​of different data.

[0022] S23. Divide the multiple sets of data obtained in step S22 into a test set and a validation set, wherein the test set is used to construct an accelerated aging model for the antifouling coating.

[0023] Specifically, the test set accounts for 70% to 80% of the data, and the validation set accounts for 30% to 20%, with a total of 100-200 sets of data. Accelerated aging models are established using the accelerated experimental parameters from the training set as input and the coating performance data from the training set as output, employing one or more machine learning algorithms such as linear regression, support vector machine, neural network, random forest, and XGBoost. As an example of this invention, the data set is 100-150 sets.

[0024] S24. Input the accelerated test parameters from the validation set into the accelerated aging model constructed in S23 to obtain the predicted values ​​of the coating performance. Compare these predicted values ​​with the measured values ​​of the coating performance in the validation set and calculate the correlation coefficient R between them. 2 When R 2 A result of ≥65% indicates that the prediction is reliable.

[0025] For accelerated testing, the standard for judging the failure of antifouling coatings is generally considered to be: copper ion leaching rate ≤10μg / day.cm2. Specifically, if the accelerated rotation cycle of short-term antifouling coating is ≥6 cycles, the accelerated rotation cycle of medium-term antifouling coating is ≥15 cycles, and the accelerated rotation cycle of long-term antifouling coating is ≥20 cycles, then the coating quality is considered qualified.

[0026] Preferably, the critical threshold R of the copper ion leaching rate 临i、 R 临i+1 The value range is 7-10 μg / day.cm 2 , where |R 临i+1 -R 临i |≤0.05μg / day.cm, specifically, |R 临i+1 -R 临i The value can be 0.01, 0.02, 0.03, 0.04, or 0.05 μg / day.cm. Preferably, specifically for short-term, medium-term, and long-term antifouling coatings, the critical threshold R... 临i、 R 临i+1 The values ​​range for these values ​​are 8-10 μg / day.cm and 8-9 μg / day.cm, respectively, while the long-term antifouling coating is 7-9 μg / day.cm. The definitions of short-term, medium-term, and long-term coatings are based on GB / T6822.

[0027] Preferably, the antifouling coating is any one of the following: degradable, self-polishing, or abrasive.

[0028] Compared with the prior art, the antifouling coating simulation aging test method of the present invention has the following beneficial effects: (1) The antifouling coating simulation aging test method of the present invention fills the technical gap in the research on rapid evaluation of antifouling coating performance and life prediction, and improves the accuracy and reliability of coating life and performance prediction. (2) Based on the establishment of natural aging model and accelerated aging model, the antifouling coating simulation aging test method proposed in the present invention links to construct a mapping relationship model of "simulated accelerated test conditions - coating performance evaluation - coating life prediction", conducts synergistic cross-validation, feedback iterative model optimization, and improves the reliability and accuracy of accelerated aging model. (3) The antifouling coating simulation aging test method of the present invention is applicable to self-polishing, degradation type and abrasion type antifouling coating system, can quickly judge the performance evolution trend of coating material under different service environment characteristics and accurately quantify and predict the service life of antifouling coating, quickly judge the coating performance degradation law and quantify and predict life, and significantly shorten the design and development cycle of long-life antifouling coating. (4) Compared with traditional methods, the antifouling coating simulation aging test method of the present invention has wider applicability, more obvious acceleration effect and higher reliability. Attached Figure Description

[0029] Figure 1 This is a schematic flowchart of the antifouling coating simulated aging test method according to an embodiment of the present invention;

[0030] Figure 2 This describes the predictive performance of the natural aging model described in this embodiment of the invention on the test set data.

[0031] Figure 3 This refers to the prediction performance of the accelerated aging model described in this embodiment of the invention on the test set data;

[0032] Figure 4 These are photographs of a failed sample of the antifouling coating described in this application, which was immersed in shallow sea water for 61 months.

[0033] Figure 5 This is a photograph of a failed sample of the antifouling coating described in the embodiments of this application during the fourth accelerated aging cycle. Detailed Implementation

[0034] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Without conflict, the technical features of the embodiments of the present invention can be combined with each other.

[0035] For antifouling coatings, simulated aging studies address the time, space, and economic cost challenges of verifying coating performance in real marine environments by accelerating laboratory environmental simulations. This is of great significance for marine engineering, shipbuilding, and underwater facility maintenance. Currently, only GB / T6822 "Ship Hull Antifouling and Rust-Preventing Paint System" requires antifouling coatings with short (less than 3 years of service life), medium (3-5 years of service life), and long-term (5 years and above of service life) antifouling coatings to undergo dynamic simulation tests for 3, 5, and 8 consecutive cycles, respectively. As an alternative to lifespan simulation aging tests, this approach has shortcomings such as a long overall experimental cycle and low reliability of test results.

[0036] Specifically, a typical dynamic simulation test cycle includes 10-60 days of shallow sea immersion and 3 days of dynamic rotation, resulting in an evaluation cycle of more than 15 months for long-life antifouling coatings, which seriously reduces the efficiency of rapid screening of coating materials. In addition, qualitatively assessing the lifespan range of antifouling coatings solely by the number of cycles in dynamic simulation tests cannot provide quantitative prediction values ​​and lacks cross-validation processes. In practical engineering applications, this can easily lead to an underestimation of the lifespan of antifouling coatings, which is particularly significant for long-life antifouling coatings.

[0037] Example 1

[0038] A simulated aging test was conducted on a certain brand of self-polishing antifouling coating. The total copper content of the coating was determined to be 42.3 wt% according to GB / T31409. A 10-month natural aging shallow sea immersion test was carried out in the East China Sea, and a 30-cycle dynamic rotation acceleration test was carried out in the corresponding seawater pool.

[0039] During the natural aging test, the seawater environmental conditions, including seawater temperature, salinity, and dissolved oxygen, were measured monthly. Coated samples were taken out and photographed to check the surface contamination of the samples. The copper ion leaching rate of the coated samples was determined in accordance with GB / T6824.

[0040] Eighty percent of the natural aging data was used to train the XGBoost machine learning model. Principal component analysis was used to preprocess the training data for dimensionality reduction. Environmental parameters, immersion time, and total copper content in the coating were used as input parameters, and the copper ion leaching rate in the coating was used as the output parameter to establish a natural aging model for the coating. The remaining 20% ​​of the natural aging data was used to test the model, and the model was compared with the test set data to validate the model. The correlation coefficient R between the two models was measured. 2 It is 0.977, such as Figure 2 As shown.

[0041] During the dynamic accelerated aging test, the rotational linear speed was 30 knots, and one rotation cycle was 200 hours. After each cycle, the copper ion leaching rate of the coating sample was determined according to GB / T6824. 85% of the accelerated aging data was used to train the XGBoost machine learning model. Principal component analysis was used to preprocess the training data for dimensionality reduction. The model was established using the number of dynamic rotation cycles and the total copper content of the coating as input parameters, and the copper ion leaching rate of the coating as the output parameter. 15% of the accelerated aging data was used to test the model, and the model was compared with the test set data to validate the model. The correlation coefficient R between the two models was measured. 2 It is 0.975, such as Figure 3 As shown.

[0042] With a critical copper ion leaching rate of 8–9 μg / day. 2 Using these as boundary conditions, the accelerated aging model of the coating was calculated in reverse, yielding a calculated accelerated test cycle number of 22 corresponding to the coating's lifetime endpoint; at a concentration of 15 μg / day. 2 The copper ion leaching rate of the coating was determined by using a natural aging model and an accelerated aging model to obtain the corresponding natural aging time T and accelerated aging period M, respectively. The aging acceleration ratio n = T / M = 0.23 was calculated, and the predicted lifespan of the coating was 22 × 0.23 = 5.1 years.

[0043] This predicted value was then input into the natural aging model, which outputs a copper ion leaching rate of 8.31 μg / day at the end of the lifespan, i.e., failure. 2 The sample size falls within the boundary condition range of 8~9 μg / day.cm2 selected for accelerated aging analysis, which meets the requirements. The accelerated aging simulation test period is 6 months.

[0044] Meanwhile, the antifouling coating of this grade was subjected to a 65-month shallow-sea immersion test in the East China Sea, in accordance with GB / T5370. After 61 months of immersion, the surface of the coating samples was covered with fouling organisms, indicating antifouling failure. Figure 4 As shown; referring to GB / T6824, the actual copper ion leaching rate at failure was determined to be 8.53 μg / day. 2 It maintains a good correspondence with the predicted failure performance values ​​and threshold boundary conditions involved in the simulated aging test.

[0045] Comparative Example 1

[0046] Dynamic simulation tests were conducted on the above-mentioned self-polishing antifouling coatings according to GB / T6822 and GB / T7789. The coating samples were first immersed in a real sea-based floating raft for two months, and the surface fouling was recorded. Then, they were transferred to a dynamic testing device and rotated continuously at a linear speed of 20 knots for three days, constituting one test cycle. The experiment revealed that the antifouling coating sample failed in the fourth test cycle. Figure 5 As shown.

[0047] The results indicate that the lifespan of this type of self-polishing antifouling paint, as evaluated according to GB / T 6822, should be less than 5 years. The dynamic simulation test lasted for more than 8 months, but the evaluation results obtained deviated significantly from the actual sea immersion results (failure after 61 months of immersion in the East China Sea), indicating poor predictive reliability.

[0048] Example 2

[0049] A simulated aging test was conducted on a certain brand of self-polishing antifouling coating. The total copper content of the coating was determined to be 51.9 wt% according to GB / T 31409. An 18-month natural aging shallow-sea immersion test was carried out in the South China Sea. Seawater environmental conditions, including temperature (°C) and salinity, were measured monthly. Coating samples were also photographed monthly to check for surface contamination. The copper ion leaching rate of the coating samples was determined according to GB / T 6824. 70% of the natural aging data was used to train an XGBoost machine learning model. Principal component analysis was used to preprocess the training data for dimensionality reduction. A natural aging model was established using natural aging environmental parameters, immersion time, and total copper content of the coating as input parameters, and the copper ion leaching rate of the coating as the output parameter. 30% of the natural aging data was used to test the model, and the correlation coefficient R between the two models was compared to the test set data. 2 It is 0.852.

[0050] A 30-cycle dynamic rotational acceleration test was conducted in a natural seawater pool in the corresponding sea area. The rotational linear velocity was 35 knots, and each rotational cycle lasted 150 hours. After each cycle, the copper ion leaching rate of the coating sample was determined according to GB / T 6824. 80% of the accelerated aging data was used to train an XGBoost machine learning model. Principal component analysis was used to preprocess the training data for dimensionality reduction. The model was established using the number of dynamic rotational cycles and the total copper content of the coating as input parameters, and the copper ion leaching rate of the coating as the output parameter. 20% of the accelerated aging data was used to test the model, and the model was compared with the test set data to validate the model. The correlation coefficient R between the two models was measured. 2 It is 0.901.

[0051] With a critical copper ion leaching rate of 7~8 μg / day·cm 2 Using the boundary conditions, the accelerated aging model of the coating was reverse-engineered, yielding 25 accelerated test cycles corresponding to the end of the coating's lifespan. The natural aging time T and accelerated aging cycles M, corresponding to equal copper ion exudation performance of the coatings, were obtained using both the natural aging model and the accelerated aging model. The aging acceleration ratio n = T / M = 0.28 was calculated, and based on this, the predicted lifespan of the coating was 25 × 0.28 = 7 years. This predicted value was then input into the natural aging model, outputting a copper ion exudation rate of 10.31 μg / day·cm at the end of the lifespan. 2The boundary condition range selected for accelerated aging analysis was exceeded, indicating an overestimation of the boundary condition value. Feedback was then provided to reselect the copper ion exudation boundary condition, resulting in an accelerated test cycle number of 28 corresponding to the end of the lifespan. Therefore, the predicted lifespan of the coating was recalculated as 28 × 0.28 = 7.84 years. This predicted value was then input into the first-stage natural aging model, outputting a copper ion exudation rate of 7.86 μg / day·cm at the end of the lifespan. 2 The results meet the boundary condition range selected for accelerated aging analysis, and the accelerated aging simulation test period is 6 months.

[0052] Comparative Example 2

[0053] Referring to GB / T 6822 and GB / T 7789, dynamic simulation tests were conducted on the aforementioned self-polishing antifouling coatings. The coating samples were first immersed in a floating raft at sea for 1.5 months, and the surface fouling was recorded. They were then transferred to a dynamic testing device and rotated continuously at a linear speed of 20 knots for 3 days, constituting one test cycle. After the 8th test cycle, the antifouling score of the antifouling coating sample was 85, and the physical condition of the coating film was good. These results indicate that the lifespan of this type of self-polishing antifouling paint, as evaluated according to GB / T 6822, should be no less than 8 years, but a quantitative lifespan prediction value cannot be provided. Furthermore, although the dynamic simulation test cycle was longer than 12 months, a quantitative prediction result still could not be obtained, indicating low evaluation efficiency and accuracy.

[0054] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A method for simulating the ageing of an antifouling coating, characterised in that, The application relates to a method for constructing a natural aging performance model of an antifouling coating. The method comprises the following steps: S1, constructing a natural aging performance model of an antifouling coating; S3, obtaining the critical threshold value R of the copper ion exuding rate based on the accelerated aging model 临i The corresponding acceleration period M i Then the predicted service life L of the anti-fouling coating p预i =M i *N; S4, obtaining the predicted service life L based on the natural aging model p预 corresponding predicted copper ion penetration rate R 预i , determining whether |R 预i- R 临i | / R 临i ≤ 10%, if yes, outputting the near threshold R 临i and the predicted service life L p预i , if no, adjusting the critical threshold of the copper ion penetration rate to R 临i+1 and returning to step S3.

2. The method for simulating the weathering test of antifouling coating according to claim 1, characterized in that, S2, constructing an accelerated aging model of the antifouling coating and calculating an acceleration ratio N of the two models; Step S1 comprises the following steps: S11, selecting an antifouling coating material to carry out a shallow sea immersion experiment, regularly recording environmental data, immersion time and obtaining coating performance parameters; S12, using principal component analysis and linear discriminant analysis to reduce dimension and remove noise of the characteristic data in the environmental data and performance parameters in step S11, wherein the characteristic data is a statistical value of different data; S14, input the environmental data and soaking time in the verification set into the natural aging performance model of S13 to obtain the predicted value of coating performance, compare it with the measured value of coating performance in the verification set, and calculate the correlation coefficient R between them 2 When R 2 ≥ 70%, the prediction result is reliable.

3. The method for simulating the weathering test of antifouling coating according to claim 2, characterized in that, S13, grouping the data obtained in step S12 into a test set and a validation set, taking the environmental characteristics and immersion time obtained after dimension reduction in the test set as input values and taking the performance parameters of the antifouling coating as output values, and using one or more of support vector machines, neural networks, principal component analysis, random forests and XGBoost algorithms to construct a natural aging performance model; 4. The accelerated weathering test method for antifouling coating according to claim 2, characterized in that, The environmental conditions of the shallow sea immersion experiment in step S11 are as follows: a gulf in the Yellow Sea, the East China Sea and the South China Sea where marine organisms grow vigorously and the seawater tidal current is less than 2 m / s, the seawater temperature is 20-30 DEG C, the seawater salinity is 30-34 ‰, and the monitoring and inspection frequency is 0.5-1 month / time.

5. The accelerated weathering test method for antifouling coatings according to claim 2, characterized in that, The antifouling coating material comprises short-term, medium-term and long-term antifouling coatings.

6. The method of accelerated weathering testing of antifouling coatings according to claim 1, characterized in that, The coating performance parameters comprise total copper content and copper ion leaching rate of the coating. Step S2 comprises the following steps: S21, selecting an antifouling coating material to carry out a dynamic acceleration experiment, regularly recording acceleration test condition parameters and obtaining coating performance data; S22, using principal component analysis and linear discriminant analysis to reduce dimension and remove noise of the characteristic data of the acceleration test condition parameters and performance data obtained in step S21, wherein the characteristic data is a statistical value of different data; S24, input the accelerated test parameters in the verification set into the accelerated aging model constructed in S23 to obtain the predicted value of the coating performance, compare the predicted value with the measured value of the coating performance in the verification set, and calculate the correlation coefficient R between the two 2 When R 2 ≥ 65%, the prediction result is reliable.

7. The method of simulating the weathering of an antifouling coating according to claim 6, characterized in that, S23, grouping the data obtained in step S22 into a test set and a validation set, taking the acceleration test parameters in the test set as input and taking the coating performance data in the training set as output, and using one or more of linear regression, support vector machines, neural networks, random forests and XGBoost algorithms to construct an accelerated aging model; 8. The method of accelerated weathering testing of antifouling coatings according to claim 1, characterized in that, the critical threshold R of the copper ion leaching rate in steps S3, S4 临i、 R 临i+1 is in the range 7-10 μg / day.cm 2 where |R 临i+1 - R 临i |≤0.05 μg / day.cm.

9. The method of accelerated weathering testing of antifouling coatings according to claim 1, characterized in that, The experimental conditions of the dynamic acceleration experiment are as follows: a rotating linear speed of 25-35 knots, a seawater temperature of 20-30 DEG C, a seawater salinity of 30-34 ‰, and a period of 150-200 hours per rotation. The antifouling coating is any one of a degradable type, a self-polishing type and an abrasive type.

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