Method for establishing fatigue life probability model of metal structure with coating under corrosion influence

Abstract

The invention relates to a method for establishing a fatigue life probability model of a metal structure with a coating under corrosion influence, which comprises the following steps of: based on a maximum likelihood estimation method, taking corrosion time as an influence factor, and finding corresponding fatigue life of a material under different corrosion time and load levels by utilizing an established C-S-N curved surface and a P-S-N curve, namely a predicted value of the fatigue life. The obtained C-S-N curve and the P-S-N curve both come from the analysis of least square fitting and maximum likelihood estimation of test data, and the error between the material life change rule described by the curve and the material life change condition under the action of the actual environment is small, so that the error of the life prediction result is smaller than that of the actual life. According to the deduced model, a fatigue test result after corrosion is fitted, a three-dimensional curved surface model is obtained, and a fatigue life degradation rule is analyzed. And projecting the C-S-N curved surface to a YOZ plane to obtain P-S-N curves under different survival rates, so as to evaluate the fatigue life and predict and analyze the residual life of the structure by means of the fatigue life S-N curve.

Description

Technical Field

[0001] The present invention relates to the technical field of metal structure life assessment, and in particular to a method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion, including a method for establishing and applying a fatigue life CSN surface and a PSN curve of a coated aluminum alloy structure under the influence of corrosion. Background Art

[0002] Aviation structures, especially military aviation structures, are parked on the ground most of the time. During use, they are very susceptible to corrosion and aging in the external environment. Especially in high temperature, high humidity, high salt and strong ultraviolet light environments, aviation organic coatings will age severely, leading to corrosion of the metal matrix, thus causing serious degradation of the fatigue life of the structure. At present, similar research methods mainly involve the determination method of the structural SN curve without taking into account the corrosion influencing factors and the establishment method of the three-parameter Weibull model of uncoated metal structures.

[0003] Organic coatings applied on the surface of aviation structures can effectively improve the corrosion resistance, and therefore have become one of the important measures for surface corrosion protection. However, when aircraft serve for a long time in coastal atmosphere and other environments, organic coatings will age due to various environmental factors such as high temperature, high humidity, high salt, and strong ultraviolet rays, thereby losing protection for the metal substrate, causing corrosion damage to the substrate, and greatly reducing the fatigue performance of the structure. Especially in the current reality of the increasingly harsh service environment of aviation equipment, there is a lack of effective methods to evaluate the fatigue life of coated metal structures, and it is impossible to predict the remaining life of the structure. Most of the existing fatigue life probability models do not consider the role of corrosion influencing factors and protection systems.

[0004] In the invention with application number 201410213681.X, a single-point method for determining the fatigue SN curve performance of materials and components is proposed. This method is aimed at fatigue tests with a small number of test pieces. It first proposed a fatigue probability model based on the maximum likelihood estimation method, but did not consider the corrosion influence factor. Its basic steps are as follows: Step 1: Combine the fatigue test results to establish a median SN curve model; Step 2: According to the normal distribution law, establish the probability density function of the logarithmic fatigue life; Step 3: Based on the maximum likelihood principle, establish the maximum likelihood equation group and solve the PSN curve.

[0005] Zhang (Long-term atmospheric pre-corrosion fatigue properties of epoxyprimer-coated 7075-T6 aluminum alloy structures [J]. International Journal of Fatigue, 2019, 129) fitted and verified the SN curve based on the single-point method combined with experimental data. However, the methods used by the above two groups of studies did not take the corrosion factor into account.

[0006] Lan (Weibull modeling of the fatigue life for steel rebar considering corrosion effects[J].International Journal of Fatigue, 2018, 111:134-143) introduced corrosion weight loss as a variable into the three-parameter Weibull model and established a surface model of fatigue life, stress amplitude and corrosion degree of steel strands. The basic steps are as follows: Step 1: Establish a two-parameter Weibull model of fatigue life without considering corrosion; Step 2: Take corrosion weight loss as an influencing factor and derive a three-parameter Weibull model to characterize fatigue life through mathematical transformation; Step 3: Based on the maximum likelihood method, estimate the model parameters and solve to obtain a three-dimensional surface of fatigue life of steel strands with weight loss rate and stress amplitude. However, this method does not consider the effect of protective coating on fatigue life of metal structures under corrosive environment, and corrosion weight loss has large errors in some cases. Summary of the invention

[0007] In order to overcome the deficiency that most of the fatigue life probability models in the prior art do not consider the corrosion influencing factors and the role of the protection system, the present invention proposes a method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion.

[0008] The specific process of the present invention is:

[0009] Step 1: Determine the factors affecting the surface of the coated metal structure:

[0010] By analyzing the actual application environment of metal structures, determine the factors affecting the surface of coated metal structures;

[0011] The actual temperature, humidity and pH value of the environment are determined by analyzing the factors that may easily lead to coating aging and substrate corrosion in the actual application environment of the structure, including ultraviolet radiation and salt spray corrosion.

[0012] Step 2: Prepare the test environment spectrum:

[0013] The environmental spectrum is compiled by converting actual environmental parameters.

[0014] The actual environmental parameters include temperature, humidity, ultraviolet intensity and corrosion intensity.

[0015] In compiling the test environment spectrum described:

[0016] The corrosion intensity is determined by the test method of alternating cycles of ultraviolet irradiation + acid solution immersion; the ultraviolet irradiation test is carried out in a UV3 ultraviolet aging test chamber.

[0017] The UV irradiation includes the condensation process, which is irradiation + condensation, and the process is cyclic; the UV irradiation is carried out in the same test chamber. The UV wavelength of the UV irradiation is 340nm, and the irradiation intensity is 0.76W / m 2 ×nm; condensation temperature is the test chamber temperature.

[0018] The solution immersion test was carried out in a constant temperature immersion test box with a pH value of 1 to simulate coastal atmospheric corrosion. The temperature of the immersion solution was set to 23.9°C; the module immersion time was 2 hours. The solution consisted of sulfuric acid, nitric acid and sodium chloride. The concentration of the sulfuric acid was 0.406 g / L, the concentration of the nitric acid was 8.51 g / L, and the concentration of the sodium chloride was 36.27 g / L.

[0019] Step 3: Carry out corrosion and fatigue tests and calculate the life results:

[0020] Carry out corrosion and fatigue tests according to the environmental profiles compiled in step 2.

[0021] I. Solution immersion test: The specimen is immersed in the mixture of sulfuric acid, nitric acid and sodium chloride in step 2 for 2 hours.

[0022] Ⅱ Ultraviolet irradiation test. Take out the test piece after immersion for 2 hours in I from the solution, hang it in the UV test box, and irradiate the suspended test piece with ultraviolet light; the irradiation time is 8 hours and the condensation time is 4 hours.

[0023] The irradiation time is the time that the ultraviolet light emitted by the ultraviolet lamp in the test box irradiates the test piece, and the irradiation time is the irradiation time. The condensation time is the time that the ultraviolet lamp in the ultraviolet test box is turned off, but the test piece is still suspended in the ultraviolet test box.

[0024] The process of the solution immersion test and the process of the ultraviolet irradiation test form a benchmark corrosion test. The benchmark corrosion test is 14 hours in total, of which 2 hours are the solution immersion test and 12 hours are the ultraviolet irradiation test. In the 12-hour ultraviolet irradiation test, the irradiation time is 8 hours and the condensation time is 4 hours.

[0025] When the corrosion test is for 60 hours, it is equivalent to the specimen being corroded for 1 year in the actual atmospheric environment.

[0026] Based on the benchmark corrosion test, the process is repeated cyclically to conduct multiple corrosion tests of different durations, and each different duration is converted into different corrosion years in the actual atmospheric environment based on the duration of the benchmark corrosion test.

[0027] After each test is completed, the test is stopped, and the test piece is dried with cold air before the fatigue test is carried out. One test piece is placed in each test.

[0028] Fatigue tests were performed on all the dried specimens after corrosion tests. The loading method of sinusoidal wave equal amplitude spectrum was adopted, and the PVC adaptive compensation with peak and valley control was used to improve the loading accuracy. The specimens with the same corrosion time were loaded with equal radiation at five stress levels of 200MPa, 250MPa, 300MPa, 400MPa and 450MPa, and the loading frequency was 5Hz.

[0029] The fatigue life results obtained.

[0030] The logarithms of the fatigue test results of the aluminum alloy plate specimens with epoxy coating after corrosion for different time periods were taken, and the data were tested for normal distribution using the normal distribution probability.

[0031] Normal distribution probability diagram of logarithmic fatigue life of test piece after atmospheric exposure pre-corrosion with a confidence level of 95%. Linear fitting was performed on the data; the result of linear fitting passed the KS test with a significance level of α = 0.05. The normal deviation is the standard normal deviation u corresponding to the survival rate P P The value of .

[0032] Step 4: Establish a mathematical model:

[0033] The three-parameter power function form of the SN curve is logarithmized to obtain the three-parameter model of logarithmic fatigue life:

[0034] m ln(S i -S0)+ln N=ln C (1)

[0035] Where S0 is the approximate value of the material fatigue limit; S i is the stress level of the test; m and C are constants obtained by fitting. Let Y = ln N, X = ln (S-S0), a1 = ln C, a2 = -m, and simplify to obtain the following linear form:

[0036] Y=a1+a2X (2)

[0037] Taking into account the dispersion of the material, a value ε is added to the right side of formula (2) i After that, we get the mathematical model Y i =a1+a2X i +ε i ; Among them, X i is the observed data, X i (x i ,y i ), i = 1, 2, ..., n. i Regression analysis was performed, and the ε i It obeys normal distribution, and the covariance Cov(ε i , ε j )=0,i≠j,that is, ε i and ε j Independent of each other. i is a mathematical model established according to formula (2), Y i Normal distribution The above X i refers to the X value of a particular test, where X is X=ln(S-S0) in the previous paragraph; ε i and ε j are two random numbers that follow a normal distribution.

[0038] Step 5: Introduce corrosion factor:

[0039] The corrosion degree of the coated metal is characterized by corrosion time t, and the expression of a2 is shown in (3)

[0040]

[0041] in, is the slope parameter of the SN curve when not corroded, and w represents the time parameter related to the corrosion time.

[0042] The standard deviation of logarithmic fatigue life under each stress level σ(S i ) is linearly related to the logarithmic value of the corresponding stress, as shown in formula (4):

[0043] σ(S i )=b1+b2lnS i (4)

[0044] σ=σ0 is the mean value of logarithmic stress The standard deviation at , then formula (4) is converted to:

[0045]

[0046] Si is the stress level of the test, b1 and b2 are shape parameters, and y0 is the initial value of the model.

[0047] Step 6: Establish the log-likelihood function:

[0048] Let g = b2 / σ0, h i =1+g(ln S i -y0), then σ(S i )=h i ·σ0, we get Y i The probability density function of is:

[0049]

[0050] Take the logarithm of the parameters on both sides of the equal sign in formula (6) to construct the likelihood function, then the log-likelihood function is:

[0051] Where: L is the likelihood function; lnL is the natural logarithm of the likelihood function L.

[0052] Step 7: Establish a fatigue life probability model considering the influence of corrosion:

[0053] Substitute the test results into the log-likelihood function in step 6 and establish a system of equations to solve the model parameters.

[0054] Substitute the test results in Table 1 into equations (8) to (12) and solve them to obtain the model parameters:

[0055]

[0056] Substitute the test results into the equations above and solve the unknown parameters through numerical calculation. i It obeys the normal distribution, and it is known that u P is the standard normal skewness, then ln N P =ln N+u P σ(S i ), and substitute formula (5) to obtain:

[0057] ln P =ln N+u P σ0[1+g(ln S i -y0)] (13)

[0058] Substituting the above formula into formula (1), the fatigue life probability model considering the influence of corrosion is obtained as follows:

[0059]

[0060] So far, the fatigue life probability model of coated metal structures under the influence of corrosion is obtained.

[0061] The invention is based on the maximum likelihood estimation method, takes the corrosion time as an influencing factor, and proposes a method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion.

[0062] According to the derived model, the present invention fits the post-corrosion fatigue test results to obtain a three-dimensional surface model (CSN surface) of the fatigue life of the coated metal structure changing with the corrosion time and stress intensity, and analyzes the fatigue life degradation law. The CSN surface is projected onto the YOZ plane to obtain the PSN curve under different survival rates, thereby using the fatigue life SN curve to evaluate the fatigue life and predict and analyze the remaining life of the structure.

[0063] The present invention, based on the maximum likelihood estimation method, proposes a method for establishing and applying the CSN surface and PSN curve of a coated aluminum alloy structure under the influence of corrosion. Using the established CSN surface and PSN curve, the fatigue life of the material under different corrosion times and load levels can be found on the curve, and the fatigue life is the predicted value of the fatigue life. The CSN surface and PSN curve obtained by the present invention are both derived from the least squares fitting of the test data and the analysis of the maximum likelihood estimation. The material life change law described by the curve and the material life change under the actual environment have small errors, so the life prediction result has a smaller error than the actual life. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a schematic diagram of the technical solution of the present invention.

[0065] Figure 2 is the normal distribution probability plot of logarithmic fatigue life after atmospheric exposure.

[0066] Figure 3 It is a flow chart of the present invention.

[0067] In the figure: 1. Lifespan value; 2. Normal distribution baseline. DETAILED DESCRIPTION

[0068] This embodiment is a method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion. The specific process is:

[0069] Step 1: Determine the surface treatment process and protection system of the structure:

[0070] By analyzing the actual application environment of metal structures, the surface treatment process and protection system of the structure are determined.

[0071] Specifically, the factors that may cause coating aging and substrate corrosion in the actual application environment of the structure are analyzed to determine the actual temperature, humidity and pH value of the environment. The influencing factors include ultraviolet radiation and salt spray corrosion.

[0072] In this embodiment, the metal structure base material is 7075-T6 aluminum alloy, and the surface protection process is sulfuric acid anodizing followed by epoxy coating. The epoxy coating is composed of bisphenol A epoxy resin, pigment particles, filler and curing agent. Among them:

[0073] The pigment particles are one of titanium dioxide, zinc chrome yellow and lead chrome yellow; the fillers are talcum powder and calcium magnesium carbonate; and the curing agent is polyamide.

[0074] The polyamide is a condensation polymer, and its molecular chain contains a large number of -CONH structures; the polyamide has a very narrow softening point range and is prone to rapid solidification.

[0075] The service environment of the metal structure is the atmospheric exposure environment of the coastal area of ​​Wanning, Hainan. The main influencing factors are ultraviolet and acid solution corrosion. The annual average temperature is 24.6℃, the relative humidity is 86%, and the annual average SO2 content is 0.045275mg / m 3 The annual average content of NO2 is 0.002025mg / m 3 , Cl - Annual deposition rate: 14.5875 mg / m 2 d.

[0076] Step 2: Prepare the test environment spectrum:

[0077] By converting the actual environmental parameters, the environmental spectrum is compiled

[0078] The actual environmental parameters include temperature, humidity, ultraviolet intensity and corrosion intensity. Specifically, the irradiation time of the ultraviolet test is calculated according to the ratio of ultraviolet radiation in a certain area to the total solar radiation and the actual annual radiation.

[0079] In compiling the test environment spectrum described:

[0080] The corrosion intensity is determined by the test method of alternating cycles of ultraviolet irradiation + acid solution immersion; the ultraviolet irradiation test is carried out in a UV3 ultraviolet aging test chamber, the lamp model is UVA-340, the electric heating tube power is 3KW, and the distilled water is heated at the bottom.

[0081] The UV irradiation includes the condensation process, which is irradiation + condensation, and the process is cyclic; the UV irradiation is carried out in the same test chamber. The UV wavelength of the UV irradiation is 340nm, and the irradiation intensity is 0.76W / m 2 ×nm; condensation temperature is the test chamber temperature.

[0082] In this embodiment, the measurement data of the local ultraviolet radiation at the Wanning Experiment Station in Hainan Province shows that the annual radiation of the local group ultraviolet radiation is 315.14 MJ / m2 ×(1.27%~4.05%)≈4~6MJ / m 2 . Divide the annual UV radiation by the radiation intensity of 0.76W / m 2 × nm, divided by the ultraviolet wavelength of 340 nm, and then divided by 3600 seconds, the range of irradiation time in the ultraviolet test is obtained. The calculation results show that the irradiation time of this embodiment is 4.3 to 17.2 hours.

[0083] The irradiation time and condensation time of each UV module are set according to the determined irradiation time, and the irradiation time of the UV module is required to be less than the local irradiation time in Wanning, Hainan, that is, 4.3 to 17.2 hours in the previous paragraph. The conditions of the UV module determined in this embodiment are set to 8 hours of irradiation + 4 hours of condensation; when irradiating, the blackboard temperature in the experimental box is 60°C; when condensing, the blackboard temperature in the experimental box is 50°C.

[0084] The solution immersion test was carried out in a constant temperature immersion test box with a pH value of 1 to simulate coastal atmospheric corrosion. The temperature of the immersion solution was set to 23.9°C; the module immersion time was 2 hours. The solution consisted of sulfuric acid, nitric acid and sodium chloride. The concentration of the sulfuric acid was 0.406 g / L, the concentration of the nitric acid was 8.51 g / L, and the concentration of the sodium chloride was 36.27 g / L.

[0085] Step 3: Carry out corrosion and fatigue tests and calculate the life results:

[0086] Carry out corrosion and fatigue tests according to the environmental profiles compiled in step 2.

[0087] This embodiment conducts the following tests on a 7075-T6 aluminum alloy test piece with epoxy coating:

[0088] I. Solution immersion test: The specimen is immersed in the mixture of sulfuric acid, nitric acid and sodium chloride in step 2 for 2 hours.

[0089] Ⅱ Ultraviolet irradiation test. Take out the test piece after immersion for 2 hours in I from the solution, hang it in the UV test box, and irradiate the suspended test piece with ultraviolet light; the irradiation time is 8 hours and the condensation time is 4 hours.

[0090] The irradiation time is the time that the ultraviolet light emitted by the ultraviolet lamp in the test box irradiates the test piece, and the irradiation time is the irradiation time. The condensation time is the time that the ultraviolet lamp in the ultraviolet test box is turned off, but the test piece is still suspended in the ultraviolet test box.

[0091] The process of the solution immersion test and the process of the ultraviolet irradiation test form a benchmark corrosion test. The benchmark corrosion test is 14 hours in total, of which 2 hours are the solution immersion test and 12 hours are the ultraviolet irradiation test. In the 12-hour ultraviolet irradiation test, the irradiation time is 8 hours and the condensation time is 4 hours.

[0092] When the corrosion test is for 60 hours, it is equivalent to the specimen being corroded for 1 year in the actual atmospheric environment.

[0093] Based on the benchmark corrosion test, the process is repeated cyclically to conduct multiple corrosion tests of different durations, and each different duration is converted into different corrosion years in the actual atmospheric environment based on the duration of the benchmark corrosion test.

[0094] In this embodiment, 7 groups of corrosion tests with different corrosion times were carried out. The corrosion time of each group of specimens was 0h, 60h, 120h, 240h, 420h, 720h and 1200h, respectively. The corresponding corrosion time in the actual atmospheric environment was 0 year, 1 year, 2 years, 4 years, 7 years, 12 years and 20 years, respectively.

[0095] Group unit 1 2 3 4 5 6 7 Corrosion test piece h 0 60 120 240 420 720 1200 Corresponding corrosion years Year 0 1 2 4 7 12 20 Number of test pieces Item 5

[0096] After each test is completed, the test is stopped, and the test piece is dried with cold air before the fatigue test is carried out. One test piece is placed in each test.

[0097] The fatigue test was carried out on all the dried specimens after corrosion test using MTS 810 fatigue testing machine. The loading method of sinusoidal wave equal amplitude spectrum was adopted, and the PVC adaptive compensation of peak and valley control was used to improve the loading accuracy. The specimens with the same corrosion time were loaded with equal radiation at five stress levels of 200MPa, 250MPa, 300MPa, 400MPa and 450MPa, and the loading frequency was 5Hz.

[0098] The fatigue life results are shown in Table 1.

[0099] Table 1 Fatigue test results of aluminum alloy plate specimens with epoxy coating after different corrosion times

[0100]

[0101] The logarithms of the fatigue test results of the aluminum alloy plate specimens with epoxy coating after corrosion for different time periods were taken, and the data were tested for normal distribution using the normal distribution probability.

[0102] The normal distribution probability diagram of the logarithmic fatigue life of the test piece after atmospheric exposure pre-corrosion is set at a confidence level of 95%. At this time, the linear fitting result of the data passed the KS test with a significance level of α = 0.05. The test results are as follows Figure 1shown. Figure 1 The life span value 1 in is distributed along the normal distribution baseline 2, indicating that the experimental data satisfies the log-normal distribution and is tested. The normal skewness is the standard normal skewness u corresponding to the survival rate P. P The value of the standard normal skewness u P It is a concept in the field of mathematical statistics. The standard normal skewness u P Obtained through literature review, page 429 of "Principles and Technologies of Aircraft Structure Life Control" compiled by He Yuting et al.

[0103] Step 4: Establish a mathematical model:

[0104] The three-parameter power function form of the SN curve is logarithmized to obtain the three-parameter model of logarithmic fatigue life:

[0105] m ln(S i -S0)+ln N=ln C (1)

[0106] Where S0 is the approximate value of the material fatigue limit; S i is the stress level of the test; m and C are constants obtained by fitting. Let Y = ln N, X = ln (S-S0), a1 = ln C, a2 = -m, and simplify to obtain the following linear form:

[0107] Y=a1+a2X (2)

[0108] Taking into account the dispersion of the material, a value ε is added to the right side of formula (2) i After that, we get the mathematical model Y i =a1+a2X i +ε i ; Among them, X i is the observed data, X i (x i ,y i ), i = 1, 2, ..., n. i Regression analysis was performed, and the ε i It obeys normal distribution, and the covariance Cov(ε i , ε j )=0,i≠j,that is, ε i and ε j Independent of each other. i is a mathematical model established according to formula (2), Y i Normal distribution The above X i refers to the X value of a particular test, where X is X=ln(S-S0) in the previous paragraph; ε i and ε jare two random numbers that obey the normal distribution. Obey is a professional term in the field of mathematical statistics.

[0109] Step 5: Introduce corrosion factor:

[0110] The corrosion degree of the coated metal is characterized by corrosion time t, and the expression of a2 is shown in (3)

[0111]

[0112] in, is the slope parameter of the SN curve when not corroded, and w represents the time parameter related to the corrosion time.

[0113] In this embodiment, the standard deviation of logarithmic fatigue life under each stress level σ(S i ) is linearly related to the logarithmic value of the corresponding stress, as shown in formula (4):

[0114] σ(S i )=b1+b2 ln S i (4)

[0115] σ0σ0 is the mean value of logarithmic stress The standard deviation at , then formula (4) is converted to:

[0116]

[0117] Si is the stress level of the test, b1 and b2 are shape parameters, and y0 is the initial value of the model.

[0118] Step 6: Establish the log-likelihood function:

[0119] Let g = b2 / σ0, h i =1+g(ln S i -y0), then σ(S i )=h i ·σ0, we get Y i The probability density function of is:

[0120]

[0121] Take the logarithm of the parameters on both sides of the equal sign in formula (6) to construct the likelihood function, then the log-likelihood function is:

[0122] Where: L is the likelihood function; lnL is the natural logarithm of the likelihood function L. (The meanings of other letters have been explained in the previous article.)

[0123] Step 7: Establish a fatigue life probability model considering the influence of corrosion:

[0124] Substitute the test results into the log-likelihood function in step 6 and establish a system of equations to solve the model parameters.

[0125] Substituting the test results in Table 1 into equations (8) to (12), the model parameters shown in Table 2 are obtained.

[0126]

[0127]

[0128] Substitute the test results into the equations above and solve the unknown parameters through numerical calculation. i It obeys the normal distribution, and it is known that u P is the standard normal skewness, then ln N P =ln N+u P σ(S i ), and substitute formula (5) to obtain:

[0129] ln P =ln N+u P σ0[1+g(ln S i -y0)] (13)

[0130] Substituting the above formula into formula (1), the fatigue life probability model considering the influence of corrosion is obtained as follows:

[0131]

[0132] So far, the fatigue life probability model of coated metal structures under the influence of corrosion is obtained.

Claims

1. A method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion, characterized in that the specific process is: Step 1: Determine the factors affecting the surface of the coated metal structure: By analyzing the actual application environment of metal structures, determine the factors affecting the surface of coated metal structures; The influencing factors include ultraviolet radiation and salt spray corrosion; Step 2: Prepare the test environment spectrum: By converting the actual environmental parameters, the environmental spectrum is compiled; The actual environmental parameters include temperature, humidity, ultraviolet intensity and corrosion intensity; Step 3: Carry out corrosion and fatigue tests and calculate the life results: Carry out corrosion and fatigue tests according to the environmental spectrum conditions compiled in step 2; Solution immersion test: the specimen was immersed in the mixture of sulfuric acid, nitric acid and sodium chloride in step 2 for 2 hours; II ultraviolet irradiation test; take out the test piece after immersion for 2 hours in I from the solution, hang it in the ultraviolet test box, and irradiate the suspended test piece with ultraviolet light; wherein, The irradiation time is 8 hours, and the condensation time is 4 hours; the process of the solution immersion test and the process of the ultraviolet irradiation test form a benchmark corrosion test; based on the benchmark corrosion test, the process is repeated cyclically to conduct multiple corrosion tests of different durations, and each different duration is converted into different corrosion years in the actual atmospheric environment based on the duration of the benchmark corrosion test; When the corrosion test is for 60 hours, it is equivalent to the specimen being corroded for 1 year in the actual atmospheric environment; After each group of tests is completed, the test is stopped, and fatigue tests are carried out after the test pieces are dried with cold air; one test piece is placed in each group of tests; fatigue tests are carried out on all test pieces dried after corrosion tests; fatigue life results are obtained; the logarithms of the fatigue test results of the aluminum alloy plate specimens with epoxy coatings that have been corroded for different periods of time are taken, and the data are tested for normal distribution through normal distribution probability; Step 4: Establish a mathematical model: The three-parameter power function form of the SN curve is logarithmized to obtain the three-parameter model of logarithmic fatigue life: mln(S i -S0)+ln N=ln C (1) Where S0 is the approximate value of the material fatigue limit; S i is the stress level of the test; m and C are constants obtained by fitting; let Y = lnN, X = ln(S-S0), a1 = ln C, a2 = -m, and simplify to obtain the following linear form: Y=a1+a2X (2) Taking into account the dispersion of the material, a value ε is added to the right side of formula (2) i After that, we get the mathematical model Y i =a1+a2X i +ε i ; Among them, X i is the observed data, X i (x i ,y i ), i = 1, 2, ..., n; for the X i Regression analysis was performed, and the ε i It obeys normal distribution, and the covariance Cov(ε i , ε j )=0,i≠j,that is, ε i and ε j Independent of each other; Y i is a mathematical model established according to formula (2), Y i Normal distribution The X i is the value of X for a particular trial, where X is X=ln(S-S0) in the previous paragraph; ε i and ε j are two random numbers that follow a normal distribution; Step 5: Introduce corrosion factor: The corrosion degree of the coated metal is characterized by corrosion time t, and the expression of a2 is shown in (3) in, is the slope parameter of the SN curve when there is no corrosion, w represents the time parameter related to the corrosion time, and the standard deviation of the logarithmic fatigue life at each stress level is σ(S i ) is linearly related to the logarithmic value of the corresponding stress, as shown in formula (4): σ(S i )=b1+b2lnS i (4) σ=σ0 is the mean value of logarithmic stress The standard deviation at , then formula (4) is converted to: Si is the stress level of the test, b1 and b2 are shape parameters, and y0 is the initial value of the model; Step 6: Establish the log-likelihood function: Let g = b2 / σ0, h i =1+g(lnS i -y0), then σ(S i )=h i ·σ0, we get Y i The probability density function of is: Take the logarithm of the parameters on both sides of the equal sign in formula (6) to construct the likelihood function, then the log-likelihood function is: Where: L is the likelihood function; lnL is the natural logarithm of the likelihood function L; Step 7: Establish a fatigue life probability model considering the influence of corrosion: Substitute the fatigue life test results obtained in step 3 into the log-likelihood function in step 6 to establish a system of equations to solve the model parameters; The fatigue life probability model considering the influence of corrosion is obtained by formula (14): So far, the fatigue life probability model of coated metal structures under the influence of corrosion is obtained.

2. The method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion as described in claim 1 is characterized in that the corrosion intensity in step 2 is determined by a test method of alternating cycles of ultraviolet irradiation + acid solution immersion; the ultraviolet irradiation test is carried out in a UV3 ultraviolet aging test box.

3. The method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion as claimed in claim 1, characterized in that, in step 2, when compiling the test environment spectrum, the ultraviolet irradiation includes a condensation process of irradiation + condensation, and the process is cycled; the ultraviolet irradiation is carried out in the same test chamber; the ultraviolet wavelength of the ultraviolet irradiation is 340nm, and the irradiation intensity is 0.76W / m 2 ×nm; condensation temperature is the test chamber temperature; The solution immersion test is carried out in a constant temperature immersion test box with a pH value of 1, which is used to simulate coastal atmospheric corrosion. The temperature of the immersion solution is set to 23.9°C; the module immersion time is 2 hours; the solution consists of sulfuric acid, nitric acid and sodium chloride; the concentration of the sulfuric acid is 0.406 g / L, the concentration of the nitric acid is 8.51 g / L, and the concentration of the sodium chloride is 36.27 g / L.

4. The method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion as described in claim 1 is characterized in that the benchmark corrosion test in step 3 is a total of 14 hours; 2 hours of which are solution immersion tests and 12 hours are ultraviolet irradiation tests; in the 12-hour ultraviolet irradiation test, the irradiation time is 8 hours and the condensation time is 4 hours.

5. The method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion as described in claim 1 is characterized in that the fatigue test in step 3 adopts a sinusoidal equal-amplitude spectrum loading method, combined with peak-valley controlled PVC adaptive compensation to improve loading accuracy; each test piece with the same corrosion time is subjected to equal-radius loading at five stress levels of 200MPa, 250MPa, 300MPa, 400MPa and 450MPa, and the loading frequency is 5Hz.

6. The method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion as claimed in claim 1, characterized in that the normal distribution probability diagram of the logarithmic fatigue life of the test piece after atmospheric exposure pre-corrosion is set at a confidence level of 95%; a linear fit is performed on the data; the result of the linear fit passes the KS test with a significance level of α=0.05; the normal deviation is the standard normal deviation u corresponding to the survival rate P P The value of .

7. The method for establishing a fatigue life probability model of a coated metal structure under the influence of corrosion as claimed in claim 1, characterized in that in step 7, when establishing the fatigue life probability model considering the influence of corrosion, the model parameters are:

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