Method for predicting fatigue life of wind barrier under action of corrosion damage

Abstract

The invention discloses a wind barrier fatigue life prediction method under a corrosion damage effect, and relates to the technical field of railway bridge wind barrier fatigue life prediction, and the method comprises the following steps: building steel finite element models of different corrosion pit sizes according to steel material attributes; obtaining a steel S-N curve with the corrosion pit; establishing a wind barrier finite element model containing the corrosion pits; obtaining a stress time travel curve of the rusted railway bridge wind barrier in the service period; fatigue cycle times under different stress amplitudes are obtained through a rain flow counting method; and calculating the linear cumulative damage of the rusted railway bridge wind barrier within one year through a Palmron-Miner rule, and predicting the fatigue life of the rusted railway bridge wind barrier. According to the method for predicting the fatigue life of the wind barrier under the action of the corrosion damage, fatigue life prediction is carried out from the angle of a wind barrier structure, and a scientific and reliable basis is provided for maintenance and replacement of the wind barrier of a railway bridge.

Description

Technical Field

[0001] The present invention relates to the technical field of fatigue life prediction of wind barriers for railway bridges, and particularly to a method for predicting the fatigue life of wind barriers under the action of corrosion damage. Background Art

[0002] In the field of railway bridge engineering, especially for railway bridges under the coupling of natural random pulsating wind loads and high-salt environments, the wind barrier, as a key facility to ensure the safety and comfort of train operation, the accurate prediction of its fatigue life is of great significance for the long-term stable operation of the bridge. The high-salt environment will accelerate the corrosion process of the wind barrier structure, greatly increasing the risk of its fatigue failure.

[0003] However, the existing fatigue life prediction technologies for wind barriers of railway bridges have obvious deficiencies when facing the special working conditions of the coupling of natural random pulsating wind loads and high-salt environments. Usually, when predicting the fatigue life, it mainly focuses on conventional load actions, material inherent properties, and structural forms, etc., but fails to fully consider the serious impact of the corrosion damage caused by the high-salt environment on the fatigue life of the wind barrier, resulting in a large deviation between the predicted fatigue life and the actual situation, and unable to accurately reflect the true fatigue condition of the wind barrier of the railway bridge under high-salt service conditions.

[0004] Therefore, developing a fatigue life prediction technology method that can fully consider the influence of corrosion damage under the coupling of natural random pulsating wind loads and high-salt environments is of extremely important practical significance and urgency for improving the prediction accuracy of the fatigue life of wind barriers for railway bridges, ensuring the safe operation of railway bridges under the coupling of natural random pulsating wind loads and high-salt environments, and realizing scientific and reasonable maintenance management. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for predicting the fatigue life of a wind barrier under the action of corrosion damage, to solve the technical problem of predicting the fatigue life of a corroded railway bridge wind barrier under the coupling of natural random pulsating wind loads and high-salt environments, and at the same time, predicting the fatigue life from the perspective of the wind barrier structure rather than from the perspective of the steel material properties is also more accurate, providing a scientific and reliable basis for the maintenance and replacement decision-making of the railway bridge wind barrier.

[0006] To achieve the above purpose, the present invention provides a method for predicting the fatigue life of a wind barrier under the action of corrosion damage, including the following steps: S1. Establish a finite element model of steel with different corrosion pit sizes according to the material properties obtained from the uniaxial tensile experiment of Q235B steel; S2. Introduce a corrosion pit size coefficient into the traditional S-N curve, and fit the S-N curve of the steel with corrosion pits by the least square method; S3. Convert the S-N curve of steel with corrosion pits to the S-N curve of the wind barrier of a rusty railway bridge using the nominal stress method, and establish a finite element model of the wind barrier with corrosion pits; S4. Simulate the random natural wind pulsation wind field received by the wind barrier of a rusty railway bridge during service, and input the obtained natural wind pulsation wind field and the S-N curve of the wind barrier of a rusty railway bridge into the finite element model of the wind barrier of a rusty railway bridge to obtain the stress time history curve of the wind barrier of a rusty railway bridge during service; S5. Obtain the fatigue cycle times at different stress amplitudes through the rain flow counting method; S6. Calculate the linear cumulative damage of the wind barrier of a rusty railway bridge within one year through the Palmgren-Miner rule, and predict the fatigue life of the wind barrier of a rusty railway bridge.

[0007] Preferably, S1 includes the following steps: S11. Fabricate a batch of standard tensile specimens of 8-mm-thick Q235B steel plates and conduct uniaxial tensile tests; S12. Obtain the material parameters of the steel through uniaxial tensile tests, including elastic modulus, Poisson's ratio, yield strength, ultimate strength, engineering stress, and engineering strain; S13. Convert the engineering stress and engineering strain curves obtained from the uniaxial tensile test into true stress and strain through the following formula: (1); In the formula: is the true stress of the steel, is the engineering stress of the steel, is the true strain of the steel, is the engineering strain of the steel; S14. Establish a three-dimensional finite element model of steel with corrosion pits having the same dimensions as those in the uniaxial tensile test, input the material parameters and the true stress-strain curve of the steel into the model, set the same boundary conditions and load values as those in the uniaxial tensile test, and set a reasonable mesh size.

[0008] Preferably, S2 includes the following steps: S21. The general expression of the traditional S-N curve is: (2); In the formula: N is the fatigue life of steel without corrosion pits, is the stress amplitude, , are material constants; Considering that the exponential function shifts the entire S-N curve downward and also changes the variation rate of the S-N curve, it is assumed that the relationship between the fatigue life of steel with corrosion pits and the fatigue life without corrosion pits is as shown in Equation (3). Substituting Equation (2) into it, the unified S-N curve formula (4) considering the corrosion pit coefficient is obtained: (3); (4); In the formula: is the fatigue life of steel with corrosion pits, is the fatigue life of steel without corrosion pits, is the corrosion pit coefficient, is the coefficient related to the stress amplitude; S22. In the finite element software, by changing the characteristic parameters of the corrosion pits, namely the corrosion depth H, corrosion width W, stress amplitude Sa, and the spacing L between corrosion pits, the post-processing results under different corrosion pit characteristic parameters are obtained. The obtained post-processing results are respectively imported into the fatigue analysis software to calculate the fatigue life; S23. According to the calculation results, the depth-width ratio η is introduced, and nonlinear fitting is performed using origin. Finally, the S-N curve of the steel component with corrosion pits is obtained: (5).

[0009] Preferably, in the fatigue life prediction model of the S3 structural member, the nominal stress method and the S-N curve are used. By changing the boundary conditions of the material finite element model, the S-N curve of the material is replaced with the S-N curve of the structure, and finite element calculation is carried out to obtain the fatigue life prediction model applied to the wind barrier structural member.

[0010] Preferably, S4 includes the steps: S41. Simulate the random natural wind pulsating wind pressure to obtain the wind pressure time history curves and power spectral density curves at the top, 3 / 4, 1 / 2, and 1 / 4 positions of the wind barrier respectively; S42. Input the obtained natural wind pulsating wind field and the S-N curve of the rusty railway bridge wind barrier into the finite element model. Among them, the random natural wind pulsating wind pressure is loaded in a partitioned manner, and the wind pressure time history curves at the top, 3 / 4, 1 / 2, and 1 / 4 positions of the wind barrier are respectively loaded at the top, 3 / 4, 1 / 2, and 1 / 4 positions of the wind barrier, and then the stress time history curve of the rusty railway bridge wind barrier during service is calculated.

[0011] Preferably, S41 includes the following steps: S411. The wind speed spectrum adopts the Davenport pulsating wind speed spectrum, and its formula is: (6); In the formula: is the power spectrum of pulsating wind speed; k is the ground roughness coefficient; is the average wind speed at a height of 10 m at this location; is the pulsating wind frequency; is the turbulence integral scale coefficient, ; S412. Deduce the power spectral density of random natural wind pulsating wind pressure according to the Wiener-Khintchine theorem and the pulsating wind pressure power spectrum formula: (7); In the formula: is the power spectral density function of the random natural wind pulsating wind pressure time history; is the atmospheric density; is z the wind speed at height, , is the wind speed power exponent; is Z the wind pressure value at height, and other symbols are the same as those in the formula in step S411; S413. According to the Shinozuka theory, the random natural wind pulsating wind pressure time history formula is expressed as follows: (8); In the formula: N is a sufficiently large positive integer; is the frequency increment; is a random variable uniformly distributed in the interval (0, 2). According to the central limit theorem, when N is large enough, the simulated random process approaches a Gaussian random process; S414. Deduce the pulsating wind load time history function from the random natural wind pulsating wind pressure time history formula: (9); In the formula: is the shape coefficient at height, is the windward area at height and is the random pulsating wind pressure at height.

[0012] Preferably, for the stress time history curve result of the rusty railway bridge wind barrier obtained in S42 during service, the rain flow counting method is used to process the data to obtain the fatigue action times under different stress amplitudes .

[0013] Preferably, S6 includes the following steps: S61. From the S-N curve of the steel component with corrosion pits obtained in S4, calculate different stress amplitudes Fatigue life under ; S62. The different stress amplitudes obtained after the rain-flow counting method processing from S5 Fatigue action times under ; S63. Calculate according to the Palmgren-Miner rule according to the following formula: (10); (11); In the formula: D is the fatigue cumulative damage, is the fatigue life cycle number used by the structure under this cyclic load, , have the same meaning as above; S64. Query the daily shifts passing through the wind barrier of the rusty railway bridge according to the train operation schedule, that is, the daily fatigue cycle number , multiply this value by 365 to get the annual fatigue cycle number , calculate the years of use of the wind barrier of the rusty railway bridge under this cyclic load through the following formula: ; In the formula: is the years of use of the wind barrier of the rusty railway bridge under this cyclic load, is the fatigue life cycle number used by the structure under this cyclic load, is the annual fatigue cycle number.

[0014] Therefore, the present invention adopts the above-mentioned method for predicting the fatigue life of the wind barrier under the action of rust damage, solves the technical problem of predicting the fatigue life of the wind barrier of the rusty railway bridge under the coupling of natural random pulsating wind load and high-salt environment, and is more accurate in predicting the fatigue life from the perspective of the wind barrier structure rather than from the perspective of the steel material properties, which provides a scientific and reliable basis for the maintenance and replacement of the wind barrier of the railway bridge.

[0015] Next, through the drawings and embodiments, the technical solutions of the present invention will be further described in detail. Brief Description of the Drawings

[0016] Figure 1 is a flowchart of a method for predicting the fatigue life of a wind barrier under the action of rust damage according to the present invention; Figure 2 is a schematic diagram of the influence curve of different characteristic parameters on the fatigue life according to the present invention, (a) is the corrosion pit depth, (b) is the corrosion pit width, and (c) is the stress amplitude; Figure 3This is a specific example of the S-N curve of a steel component with corrosion pits provided by an embodiment of the present invention. Figure 4 This is the wind pressure time history curve at 1 meter, 2 meters, 3 meters, and 4 meters of the wind barrier of the present invention. (a) is the wind pressure time history curve at 1 meter, (b) is the wind pressure time history curve at 2 meters, (c) is the wind pressure time history curve at 3 meters, and (d) is the wind pressure time history curve at 4 meters. Detailed implementation manners

[0017] The technical solutions of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0018] Unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those of ordinary skill in the field to which the present invention belongs. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or objects appearing before this term cover the elements or objects listed after this term and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left", "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0019] Embodiment Please refer to Figures 1 - 4 , the present invention provides a method for predicting the fatigue life of a wind barrier under the action of corrosion damage, including the following steps: S1. First, according to the uniaxial tensile test of Q235B steel, material parameters such as the elastic modulus, Poisson's ratio, yield strength, ultimate strength, and stress-strain curve of the steel are obtained. These obtained material parameters are imported into finite element software to establish multiple three-dimensional steel finite element models with corrosion pits of different sizes.

[0020] S11. For the material parameters in the three-dimensional steel finite element model with corrosion pits, according to "Metallic materials - Tensile testing - Part 1: Method of test at room temperature", a batch of standard tensile specimens of 8-mm-thick Q235B steel plates produced by a certain steel structure company are fabricated, and the uniaxial tensile test is carried out in accordance with "Metallic materials - Fatigue testing - Method of axial force control". S12. Parameters such as the elastic modulus, Poisson's ratio, yield strength, ultimate strength, engineering stress, and engineering strain of the steel are obtained through the uniaxial tensile test.

[0021] The specific parameters are as follows: elastic modulus of 210 GPa, Poisson's ratio of 0.3, yield strength of 235 MPa, and tensile strength of 415 MPa.

[0022] S13. Convert the engineering stress and engineering strain curves obtained from the uniaxial tensile test into true stress and strain through the following formula. The conversion of the engineering stress and strain into the true stress and strain curves actually input into the finite element software can be achieved by the following formula: (1); In the formula, is the true stress of the steel, is the engineering stress of the steel, is the true strain of the steel, is the engineering strain of the steel.

[0023] S14. Establish a three-dimensional finite element model of steel with corrosion pits having the same size as that in the uniaxial tensile test, and input the material parameters obtained from the uniaxial tensile test and the true stress-strain curve of the steel into the model. Set the boundary conditions to be load-controlled in the form of reference points. Couple reference point 1 and reference point 2 with the surface of the specimen clamping end respectively. Set reference point 1 to be completely fixed, and set reference point 2 to be an axial tensile cyclic load. The load value is based on the statistical scheme and analysis method of metal material fatigue test data. The loading is divided into 6 equally spaced stress levels, and the stress ratio is taken as 0, that is, the minimum stress is 0, and the applied stress magnitude is the stress amplitude magnitude. Use the loading coefficient to represent the relationship between the stress level applied to the model and the yield stress level. The loading coefficient is the ratio of the applied load to the yield load .

[0024] Apply six different load levels to the model. The specific values are shown in Table 1 below. Considering both the calculation time and the accuracy, set the element size of the parallel section of the specimen to be 2 mm and the other element sizes to be 4 mm. The mesh type is C3D8R.

[0025] Table 1 Loads applied to the three-dimensional finite element model of steel with corrosion pits ; S2. Obtain the fatigue life of the steel with corrosion pits at different pitting depths, pitting widths, stress amplitudes, and corrosion pit spacings, and fit the relationship curves between different parameters and the fatigue life. It is not difficult to find that the pitting depth and pitting width have a greater impact on the fatigue life of the steel. Therefore, introduce the pitting size coefficient, the depth-width ratio of the corrosion pit, into the traditional S-N curve, and fit the S-N curve of the steel component with corrosion pits by the least square method.

[0026] S21. The general expression of the traditional S-N curve is: (2); Where: N is the fatigue life of the steel without corrosion pits, is the stress amplitude, , are material constants.

[0027] Considering that the exponential function can shift the entire S-N curve downward and also change the change rate of the S-N curve, it is assumed that the relationship between the fatigue life of the steel with corrosion pits and the fatigue life without corrosion pits is as shown in Equation (3). Substituting Equation (2) into it, the unified S-N curve formula (4) considering the corrosion pit coefficient can be obtained: (3); (4); Where: is the fatigue life of the steel with corrosion pits, is the fatigue life of the steel without corrosion pits, is the corrosion pit coefficient, is the coefficient related to the stress amplitude; S22. In the finite element software, by changing the characteristic parameters of the corrosion pits, such as the corrosion depth L, the corrosion width W, the stress amplitude Sa, and the spacing L between the corrosion pits, the post-processing results under different characteristic parameters of the corrosion pits are obtained. Subsequently, the obtained post-processing result files are respectively imported into the fatigue analysis software to calculate the fatigue life. The calculation results and the specific values of the characteristic parameters are shown in Table 2 below.

[0028] Table 2 Characteristic parameters of corrosion pits and calculation results of fatigue life ; ; ; ; ; S23. As Figure 2 shown, according to the calculation results, it can be seen that the corrosion depth L, the corrosion width W, and the stress amplitude Sa of the corrosion pits have a greater impact on the fatigue life, while the spacing L between the corrosion pits has little impact on the fatigue life. Therefore, the depth-width ratio η is introduced, and the obtained data is non-linearly fitted, and the fitting degree is Finally, the S-N curve of the steel component with corrosion pits as shown in Figure 3 can be obtained: (5); The S-N curve of the material can be converted into the S-N curve of the structure according to the following formula: (6); Where, is the stress of the structural S-N curve, is the stress of the material S-N curve, is the size coefficient, is the surface quality coefficient, is the loading method, is the fatigue notch coefficient of the structure.

[0029] (7); In the formula, is a material constant, only related to the material strength; r is the hole radius, is the stress concentration coefficient.

[0030] S3. Convert the S-N curve of the steel with corrosion pits to the S-N curve of the rusty railway wind barrier by using the nominal stress method.

[0031] (8); In the formula, is the local maximum stress in the finite element software, is the nominal stress.

[0032] S4. Simulate the random natural wind pulsation wind field received during the service process of the rusty wind barrier, and input the obtained random natural wind pulsation wind field and the S-N curve of the rusty railway wind barrier into the finite element model to calculate the stress time history curve of the structure of the rusty railway wind barrier during service.

[0033] S41. When the wind barrier is subjected to wind load, the wind pressure received at each height is usually not equal. Therefore, simulate the random natural wind pulsation wind pressure, and obtain the wind pressure time history curves at the top, 3 / 4, 1 / 2, and 1 / 4 of the wind barrier as Figure 4 shown.

[0034] S411. The wind speed spectrum adopts the Davenport pulsating wind speed spectrum, and its formula is: (9); In the formula: is the pulsating wind speed power spectrum; k is the ground roughness coefficient; is the average wind speed at a height of 10 m at this location; is the pulsating wind frequency; x is the turbulence integral scale coefficient, .

[0035] S412. Deduce the random natural wind pulsation wind pressure power spectral density according to the Wiener-Khintchine theorem and the pulsating wind pressure power spectrum formula: (10); In the formula: is the power spectral density function of the time history of random natural wind pulsating wind pressure; is the atmospheric density; is z the wind speed at height , is the wind speed power exponent; is Z the wind pressure value at height , and other symbols are the same as those in the formula of step S411.

[0036] S413. According to the Shinozuka theory, the formula of the time history of random natural wind pulsating wind pressure is expressed as follows: (11); In the formula: N is a sufficiently large positive integer; is the frequency increment; is a random variable uniformly distributed in the interval (0, 2). According to the central limit theorem, when N is large enough, the simulated random process approaches a Gaussian random process.

[0037] S414. Through the formula of the time history of random natural wind pulsating wind pressure, the time history function of the pulsating wind load can be deduced: (12); In the formula: is the shape coefficient at height , is the windward area at height and is the random pulsating wind pressure at height .

[0038] S42. Input the obtained time history curve of the natural wind pulsating wind and the S-N curve of the wind barrier of the corroded railway bridge into the finite element model. Among them, the loading of the random natural wind pulsating wind pressure adopts the partition loading method, and the time history curves of the wind pressure at the top, 3 / 4, 1 / 2, and 1 / 4 of the wind barrier are respectively loaded at the top, 3 / 4, 1 / 2, and 1 / 4 of the wind barrier to calculate the stress time history curve of the corroded railway wind barrier during its service life.

[0039] S5. Calculate the fatigue action times under different stress amplitudes through the rain-flow counting method.

[0040] Based on the obtained stress time history curve results of the wind barrier of the corroded railway bridge during its service life, calculate the fatigue action times under different stress amplitudes by the rain-flow counting method , where the fatigue action times corresponding to the stress amplitude is , and the remaining stress amplitudes also correspond one by one to the number of fatigue actions.

[0041] S6. Calculate the linear cumulative loss of the rusty railway bridge wind barrier within one year through the Palmgren-Miner rule, so as to predict the fatigue life of the rusty railway bridge wind barrier.

[0042] S61. According to the S-N curve of the steel component with corrosion pits obtained in step S4, calculate the fatigue life under different stress amplitudes under .

[0043] S62. Record the number of fatigue actions under different stress amplitudes obtained after processing by the rain flow counting method as under .

[0044] S63. Calculate according to the Palmgren-Miner rule according to the following formula (13); (14); In the formula: D is the fatigue cumulative damage, is the number of fatigue life cycles that the structure can use under this cyclic load, , have the same meaning as above.

[0045] S64. Query the train schedule to query the number of daily trips passing by the rusty railway bridge wind barrier, that is, the daily fatigue cycle number , multiply this value by 365 to get the annual fatigue cycle number , and the number of years that the rusty railway bridge wind barrier can be used under this cyclic load can be calculated through the following formula: (15); In the formula is the number of years that the rusty railway bridge wind barrier can be used under this cyclic load, is the number of fatigue life cycles that the structure can use under this cyclic load, is the annual fatigue cycle number.

[0046] Therefore, the present invention adopts the above-mentioned method for predicting the fatigue life of the wind barrier under the action of rust damage, solves the technical problem of predicting the fatigue life of the rusty railway bridge wind barrier under the coupling of natural random pulsating wind load and high-salt environment, and is more accurate in predicting the fatigue life from the perspective of the wind barrier structure rather than from the perspective of the steel material properties, which provides a scientific and reliable basis for the maintenance and replacement of the railway bridge wind barrier.

[0047] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions of the present invention or make equivalent replacements, and these modifications or equivalent replacements do not enable the modified technical solutions to depart from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for predicting fatigue life of wind barriers under corrosion damage, characterized in that: The following steps are involved: S1. Based on the material properties obtained from the uniaxial tensile test of Q235B steel, a finite element model of steel with different corrosion pit sizes was established; S2. Introducing the corrosion pit size coefficient into the traditional SN curve, the SN curve of steel with corrosion pits was fitted by the least square method; S3. The SN curve of the steel with corrosion pits is converted into the SN curve of the wind barrier of the corroded railway bridge by using the nominal stress method, and a finite element model of the wind barrier with corrosion pits is established; S4, simulating the random natural wind pulsation wind field to which the wind barrier of the corroded railway bridge is subjected during its service, and inputting the obtained natural wind pulsation wind field together with the SN curve of the wind barrier of the corroded railway bridge into the finite element model of the wind barrier of the corroded railway bridge, and obtaining the stress time history curve of the wind barrier of the corroded railway bridge during its service; S5. Obtain the number of fatigue cycles under different stress amplitudes by rain flow counting method; S6. The linear cumulative damage of the wind barrier of the corroded railway bridge within one year is calculated by the Palmgren-Miner law, and the fatigue life of the wind barrier of the corroded railway bridge is predicted.

2. The method for predicting fatigue life of wind barriers under corrosion damage according to claim 1 is characterized in that: S1 includes the following steps: S11. Prepare a batch of 8mm thick Q235B steel plate standard tensile specimens and conduct uniaxial tensile tests; S12. Obtain material parameters of steel through uniaxial tensile tests, including elastic modulus, Poisson's ratio, yield strength, ultimate strength, engineering stress, and engineering strain; S13. The engineering stress and engineering strain curves obtained from the uniaxial tensile test are converted into real stress and strain using the following formula: （1）； Where: is the true stress of the steel, is the engineering stress of steel, is the real strain of steel, is the engineering strain of steel; S14. Establish a three-dimensional steel finite element model containing corrosion pits with the same size as the uniaxial tensile test, input the material parameters and the true stress-strain curve of the steel into the model, set the same boundary conditions and load values ​​as the uniaxial tensile test, and set a reasonable grid size.

3. The method for predicting fatigue life of wind barriers under corrosion damage according to claim 2 is characterized in that: S2 includes the following steps: S21. The general expression of the traditional SN curve is: （2）； Where: N is the fatigue life of the steel without corrosion pits, is the stress amplitude, , is the material constant; Considering that the exponential function makes the SN curve move downward as a whole and changes the rate of change of the SN curve, it is assumed that the relationship between the fatigue life of steel with corrosion pits and the fatigue life without corrosion pits is as shown in formula (3). Substituting formula (2) into the formula (4) to obtain the unified SN curve formula considering the corrosion pit coefficient: （3）； （4）； Where: is the fatigue life of steel with corrosion pits, Fatigue life of non-pitting steel. is the pitting coefficient, is the coefficient related to the stress amplitude; S22, in the finite element software, by changing the characteristic parameters of the corrosion pits, corrosion depth H, corrosion width W, stress amplitude Sa, and spacing L between corrosion pits, obtain post-processing results under different corrosion pit characteristic parameters, and import the obtained post-processing results into fatigue analysis software to calculate fatigue life; S23. According to the calculation results, the depth-to-width ratio η is introduced, and origin is used for nonlinear fitting, and finally the SN curve of the steel component containing corrosion pits is obtained: （5）。 4. The method for predicting fatigue life of a wind barrier under corrosion damage according to claim 3 is characterized by: In the fatigue life prediction model of S3 structural parts, the nominal stress method and SN curve are used. By changing the boundary conditions of the material finite element model, the SN curve of the material is replaced by the SN curve of the structure, and finite element calculation is performed to obtain the fatigue life prediction model applied to wind barrier structural parts.

5. The method for predicting fatigue life of wind barriers under corrosion damage according to claim 4 is characterized in that: S4 includes the steps: S41, simulate the random natural wind pulsation wind pressure, and obtain the wind pressure time history curves and power spectrum density curves at the top, 3 / 4, 1 / 2 and 1 / 4 of the wind barrier respectively; S42. The obtained natural wind pulsation wind field and the SN curve of the wind barrier of the corroded railway bridge are input into the finite element model together, wherein the loading of the random natural wind pulsation wind pressure adopts the partition loading method to load the wind pressure time history curves at the top, 3 / 4, 1 / 2 and 1 / 4 of the wind barrier respectively at the top, 3 / 4, 1 / 2 and 1 / 4 of the wind barrier, and then the stress time history curve of the wind barrier of the corroded railway bridge during its service is calculated.

6. The method for predicting fatigue life of wind barriers under corrosion damage according to claim 5 is characterized in that: S41 includes the following steps: S411. The wind speed spectrum adopts the Davenport pulsating wind speed spectrum, and its formula is: （6）； Where: is the fluctuating wind speed power spectrum; k is the ground roughness coefficient; The average wind speed at a height of 10m at this location; is the pulsating wind frequency; x is the turbulence integral scale coefficient, ; S412. According to the Wiener-Khintchine theorem and the fluctuating wind pressure power spectrum formula, the random natural wind fluctuating wind pressure power spectrum density is derived: （7）； Where: is the power spectrum density function of the random natural wind pulsation wind pressure time history; is the atmospheric density; is the wind speed at height z, , is the wind speed power index; is the wind pressure value at height Z, and other symbols are the same as the formula in step S411; S413. According to Shinozuka theory, the time history formula of random natural wind pulsation wind pressure is expressed as follows: （8）； Where: N is a sufficiently large positive integer; is the frequency increment; is a random variable uniformly distributed in the interval (0, 2). According to the central extreme value theorem, when N is large enough, the simulated random process approaches a Gaussian random process; S414. The fluctuating wind load time history function is derived from the random natural wind fluctuating wind pressure time history formula: （9）； Where: for Height of body shape factor, for The frontal area of ​​the height and for Highly random pulsating wind pressure.

7. The method for predicting fatigue life of wind barriers under corrosion damage according to claim 6 is characterized by: The stress time history curve results of the corroded railway bridge wind barrier obtained by S42 during service were processed by the rain flow counting method to obtain different stress amplitudes. Fatigue effect times , … .

8. The method for predicting fatigue life of wind barriers under corrosion damage according to claim 7 is characterized in that: S6 includes the following steps: S61. Calculate the different stress amplitudes based on the SN curve of the steel component with corrosion pits obtained in S4. Fatigue life under ; S62, obtained from S5 and processed by rain flow counting method to obtain different stress amplitudes Fatigue effect times ; S63. Calculate according to the Palmgren-Miner rule using the following formula: （10）； （11）； Where: D is the cumulative fatigue damage, is the number of fatigue life cycles of the structure under this cyclic load, , Same meaning as above; S64. Query the number of fatigue cycles of the trains passing through the wind barrier of the rusted railway bridge every day according to the train dispatch table. , multiply this value by 365 to get the number of fatigue cycles per year , the years of service of the wind barrier of the corroded railway bridge under the cyclic load can be calculated by the following formula: （12）； Where: is the number of years the wind barrier of the corroded railway bridge was used under the cyclic load. is the number of fatigue life cycles of the structure under this cyclic load, is the number of fatigue cycles per year.

Images