A method and system for rapidly evaluating the stress corrosion susceptibility of fatigue-damaged components

Abstract

This invention provides a method and system for rapidly evaluating the stress corrosion susceptibility of fatigue-damaged components, belonging to the field of metal corrosion assessment. The method includes: conducting pre-fatigue interruption experiments on undamaged component samples for different cycles and measuring the average local orientation difference of the fatigue-damaged samples; conducting slow strain rate tensile experiments on slow strain rate tensile samples to determine the stress-strain curve; calculating the stress corrosion susceptibility value corresponding to each candidate parameter based on the stress-strain curve; linearly fitting the stress corrosion susceptibility value corresponding to each candidate parameter with the average local orientation difference, and determining the candidate parameter with the best linear fitting effect; measuring the average local orientation difference of the damaged component to be evaluated, and determining the stress corrosion susceptibility value of the damaged component to be evaluated based on the linear relationship between the stress corrosion susceptibility value and the average local orientation difference. This invention improves the calculation efficiency of the stress corrosion susceptibility value of in-service components.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of metal corrosion evaluation, in particular to a method and system for quickly evaluating stress corrosion sensitivity of a fatigue-damaged component. BACKGROUND

[0002] During the working process of a mechanical component, various forms of damage accumulation, such as low-cycle fatigue damage, high-cycle fatigue damage, and creep damage, are inevitable. The accumulation of such damage will cause changes in the microstructure, which will change the corrosion resistance of the component. Load-bearing components working in a corrosive environment are at risk of stress corrosion. How to quickly evaluate the stress corrosion resistance of the damaged component material is of great significance to safety production.

[0003] The traditional method for quickly evaluating the stress corrosion sensitivity of a material is the slow strain rate test method. However, for a damaged component, it is too destructive to obtain enough material for slow tensile specimen processing, and the process is complex and difficult to obtain results quickly.

[0004] Therefore, it is necessary to provide a new method for quickly evaluating the stress corrosion sensitivity of a load-bearing component after fatigue damage. SUMMARY

[0005] The purpose of the present application is to provide a method and system for quickly evaluating the stress corrosion sensitivity of a fatigue-damaged component, which can simply and quickly evaluate the stress corrosion sensitivity value of a damaged load-bearing component.

[0006] To achieve the above purpose, the present application provides the following solutions:

[0007] A method for quickly evaluating the stress corrosion sensitivity of a fatigue-damaged component, comprising:

[0008] Performing a pre-fatigue experiment on an undamaged component specimen to obtain a fatigue-damaged specimen, and measuring the local orientation difference average value of the fatigue-damaged specimen;

[0009] Processing the fatigue-damaged specimen into a slow strain rate tensile specimen;

[0010] Performing a slow strain rate tensile experiment on the slow strain rate tensile specimen to determine the stress-strain curve of the slow strain rate tensile specimen;

[0011] According to the stress-strain curve of the slow strain rate tensile specimen, calculating the stress corrosion sensitivity value corresponding to each candidate parameter; the candidate parameters include tensile strength, yield strength, reduction of area, fracture time, and curve area.

[0012] linearly fitting the stress corrosion sensitivity value corresponding to each candidate parameter with the local misorientation average value of the fatigue damage sample, and determining the candidate parameter with the best linear fitting effect;

[0013] determining the linear relationship between the stress corrosion sensitivity value and the local misorientation average value according to the linear fitting result of the stress corrosion sensitivity value corresponding to the candidate parameter with the best linear fitting effect and the local misorientation average value of the fatigue damage sample;

[0014] measuring the local misorientation average value of the fatigue damage component to be evaluated;

[0015] determining the stress corrosion sensitivity value of the fatigue damage component to be evaluated according to the local misorientation average value of the fatigue damage component to be evaluated and the linear relationship between the stress corrosion sensitivity value and the local misorientation average value.

[0016] Optionally, the number of the undamaged component samples is multiple; and the cycle loading times of the pre-fatigue experiments of each undamaged component sample are different.

[0017] Optionally, the pre-fatigue experiment is performed on the undamaged component sample to obtain a fatigue damage sample, and the local misorientation average value of the fatigue damage sample is measured, specifically including:

[0018] performing the interrupted fatigue experiment under strain control on the undamaged component sample to obtain a fatigue damage sample, and cutting a sample of a set size along a direction perpendicular to an axis direction of the fatigue damage sample to obtain a micro-observation sample;

[0019] performing sandpaper grinding treatment on the micro-observation sample, and performing backscattered electron diffraction measurement after polishing using an oxide polishing suspension to obtain a local misorientation map of the fatigue damage sample;

[0020] determining the local misorientation average value of the fatigue damage sample according to the local misorientation map of the fatigue damage sample.

[0021] Optionally, the fatigue damage sample is processed into a slow strain rate tensile sample, specifically including:

[0022] cutting a slow strain rate tensile sample of a set size along a direction parallel to the axis direction of the pre-fatigue sample.

[0023] Optionally, the stress corrosion sensitivity value corresponding to the candidate parameter j is calculated using the following formula:

[0024]

[0025] wherein, I j is the stress corrosion sensitivity value corresponding to the candidate parameter j, SSRT s,jSSRT is the value of the candidate parameter j for the slow strain rate tensile test after the test. a,j SSRT is the value of the candidate parameter j in an inert environment.

[0026] Optionally, the stress corrosion sensitivity value corresponding to each candidate parameter is linearly fitted with the local misorientation average value of the fatigue damage sample respectively, and the candidate parameter with the best linear fitting effect is determined according to the linear fitting result, and specifically includes:

[0027] According to the local misorientation average value of the fatigue damage sample, a sensitive factor of the local misorientation average value is calculated:

[0028]

[0029] Wherein, D K is the sensitive factor of the local misorientation average value, K i is the local misorientation average value after i cycle loading cycles, and K0 is the local misorientation average value without fatigue damage;

[0030] For any candidate parameter, according to the stress corrosion sensitivity value of the candidate parameter, the sensitive factor of the candidate parameter is calculated:

[0031]

[0032] Wherein, D I is the sensitive factor of the candidate parameter, I i is the stress corrosion sensitivity value after i cycle loading cycles, and I0 is the stress corrosion sensitivity value without fatigue damage;

[0033] The sensitive factor of the local misorientation average value is linearly fitted with the sensitive factor of each candidate parameter respectively, and the optimal parameter is determined according to the linear fitting result; the optimal parameter is the candidate parameter corresponding to the sensitive factor with the highest fitting degree;

[0034] According to the stress corrosion sensitivity value of the optimal parameter and the local misorientation average value of the fatigue damage sample, the candidate parameter with the best linear fitting effect is determined.

[0035] In order to achieve the above purpose, the present application also provides the following schemes:

[0036] A system for quickly evaluating the stress corrosion sensitivity of a fatigue damage component, comprising:

[0037] A pre-fatigue test module is used for pre-fatigue test on an undamaged component sample to obtain a fatigue damage sample, and the local misorientation average value of the fatigue damage sample is measured;

[0038] A sample processing module is associated with the pre-fatigue experiment module and used to process the fatigue damage sample into a slow strain rate tensile sample;

[0039] A slow strain rate tensile module is connected with the sample processing module and used to perform a slow strain rate tensile experiment on the slow strain rate tensile sample to determine a stress-strain curve of the slow strain rate tensile sample;

[0040] A stress corrosion sensitivity calculation module is connected with the slow strain rate tensile module and used to calculate a stress corrosion sensitivity value corresponding to each candidate parameter according to the stress-strain curve of the slow strain rate tensile sample; the candidate parameters include tensile strength, yield strength, reduction of area, fracture time and curve enclosed area;

[0041] A linear fitting module is connected with the pre-fatigue experiment module and the stress corrosion sensitivity calculation module respectively and used to perform linear fitting on the stress corrosion sensitivity value corresponding to each candidate parameter and the local misorientation average value of the fatigue damage sample respectively and determine a candidate parameter with the best linear fitting effect;

[0042] A relationship determination module is connected with the linear fitting module and used to determine a linear relationship between the stress corrosion sensitivity value and the local misorientation average value according to the linear fitting result of the stress corrosion sensitivity value corresponding to the candidate parameter with the best linear fitting effect and the local misorientation average value of the fatigue damage sample;

[0043] A microstructure measurement module is used to measure the local misorientation average value of a fatigue damage component to be evaluated;

[0044] An evaluation module is connected with the relationship determination module and the microstructure measurement module respectively and used to determine a stress corrosion sensitivity value of the fatigue damage component to be evaluated according to the linear relationship between the stress corrosion sensitivity value and the local misorientation average value and the local misorientation average value of the fatigue damage component to be evaluated.

[0045] According to the specific embodiments of the present application, the following technical effects are provided:

[0046] The present application firstly performs a pre-fatigue experiment and a slow strain rate tensile experiment on an undamaged component sample, establishes a linear relationship between the damage degree (local misorientation average value) of a bearing component and the stress corrosion sensitivity, and directly measures the KAM average value of the bearing component after the bearing component is damaged, so that the influence of the fatigue damage on the stress corrosion sensitivity can be quickly determined according to the linear relationship. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below only illustrate some of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0048] Figure 1 Flow chart of the method for rapidly evaluating stress corrosion sensitivity of fatigue damaged components provided by the present application;

[0049] Figure 2 Schematic diagram of the geometric size of the sample required for the pre-fatigue experiment;

[0050] Figure 3 Schematic diagram of the geometric size of the slow strain rate tensile sample;

[0051] Figure 4 Linear fitting result graph of the sensitive factor of the KAM average value and the sensitive factor of the area reduction and the curve area;

[0052] Figure 5 Schematic diagram of the system for rapidly evaluating stress corrosion sensitivity of fatigue damaged components provided by the present application.

[0053] Symbol explanation:

[0054] 1-pre-fatigue experiment module, 2-sample processing module, 3-slow strain rate tensile module, 4-stress corrosion sensitivity calculation module, 5-linear fitting module, 6-relationship determination module, 7-microstructure measurement module, 8-evaluation module. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0056] The purpose of the present application is to provide a method and system for rapidly evaluating stress corrosion sensitivity of fatigue damaged components. After the component is damaged, the influence of fatigue damage on stress corrosion sensitivity can be rapidly characterized by measuring the Kernel Average Misorientation (KAM) average value of the component, and according to the linear relationship.

[0057] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0058] Embodiment one

[0059] As Figure 1 shown, the embodiment provides a method for quickly evaluating stress corrosion sensitivity of fatigue damaged components, comprising:

[0060] Step 100: pre-fatigue test is performed on the undamaged component sample to obtain a fatigue damaged sample, and the average value of local orientation difference of the fatigue damaged sample is measured.

[0061] Specifically, the interrupted fatigue test under strain control is performed on the undamaged component sample to obtain a fatigue damaged sample, and a sample of a set size is taken along the direction perpendicular to the axis direction of the fatigue damaged sample to obtain a micro observation sample. After sandpaper grinding treatment is performed on the micro observation sample and polishing is performed using an oxide polishing suspension, backscattering electron diffraction measurement is performed to obtain a local orientation difference map of the fatigue damaged sample. According to the local orientation difference map of the fatigue damaged sample, the average value of local orientation difference of the fatigue damaged sample is determined.

[0062] Preferably, the number of undamaged component samples is multiple; and the cycle loading times of pre-fatigue tests of respective undamaged component samples are different.

[0063] Pre-fatigue tests of different cycle loading times are performed using the same material (component sample) as the load bearing component to be evaluated. The KAM average values of samples after fatigue of different cycle loading times are measured.

[0064] Specifically, the low cycle fatigue (LCF) experiment of interrupted strain control is adopted to perform pre-fatigue test on the undamaged material. The LCF experiment adopts a triangular waveform, is performed at room temperature, and appropriate strain ratio, strain amplitude and strain rate are selected. A micro observation sample of a set size is taken along the direction perpendicular to the axis direction of the pre-fatigue test, sandpaper grinding treatment is performed on the micro observation sample, and polishing is performed using an oxide polishing suspension, and electron backscatter diffraction (EBSD) measurement is performed to obtain KAM maps of different cycle loading times, and the corresponding KAM average values are calculated.

[0065] Step 200: the fatigue damaged sample is processed into a slow strain rate tensile sample.

[0066] In the embodiment, the slow strain rate tensile sample of a set size is taken along the direction parallel to the axis direction of the fatigue sample.

[0067] Step 300: slow strain rate tensile experiment is performed on the slow strain rate tensile sample to determine the stress-strain curve of the slow strain rate tensile sample.

[0068] Specifically, a slow strain rate test is performed in an environment corresponding to an actual working condition, and a suitable loading strain rate is selected, generally 10 -6 s -1 as the experimental strain rate.

[0069] Step 400: According to the stress-strain curve of the slow strain rate test sample, the stress corrosion sensitivity value corresponding to each candidate parameter is calculated. The candidate parameters include tensile strength, yield strength, reduction of area, fracture time and curve area.

[0070] The stress corrosion sensitivity value corresponding to the candidate parameter j is calculated by the following formula:

[0071]

[0072] wherein, I j is the stress corrosion sensitivity value corresponding to the candidate parameter j, the larger the value, the higher the stress corrosion sensitivity of the material, SSRT s,j is the value of the candidate parameter j after the slow strain rate test, that is, the result obtained by the material in the corrosion environment, SSRT a,j is the value of the candidate parameter j in the inert environment, that is, the result obtained by the material in the inert environment.

[0073] Step 500: Linearly fit the stress corrosion sensitivity value corresponding to each candidate parameter with the local misorientation average value of the fatigue damage sample, and determine the candidate parameter with the best linear fitting effect.

[0074] Specifically, according to the local misorientation average value of the fatigue damage sample, the sensitivity factor of the local misorientation average value is calculated. For any candidate parameter, according to the stress corrosion sensitivity value of the candidate parameter, the sensitivity factor of the candidate parameter is calculated. Linearly fit the sensitivity factor of the local misorientation average value with the sensitivity factor of each candidate parameter, and determine the optimal parameter according to the linear fitting result. The optimal parameter is the candidate parameter corresponding to the sensitivity factor with the highest fitting degree. According to the stress corrosion sensitivity value of the optimal parameter and the local misorientation average value of the fatigue damage component sample, the candidate parameter with the best linear fitting effect is determined.

[0075] After obtaining the stress corrosion sensitivity values represented by different candidate parameters, the KAM value and the sensitivity factor of the stress corrosion sensitivity values represented by different candidate parameters can be calculated, and then the KAM average value sensitivity factor and the sensitivity factor of the stress corrosion sensitivity values represented by different candidate parameters are linearly fitted, and the stress corrosion sensitivity calculated by the candidate parameter with the highest fitting degree is determined as the parameter representing the stress corrosion sensitivity of the material.

[0076] Step 600: determining the linear relationship between the stress corrosion sensitivity value and the local orientation difference average value according to the linear fitting result of the stress corrosion sensitivity value corresponding to the candidate parameter with the best linear fitting effect and the local orientation difference average value of the fatigue damage sample.

[0077] Step 700: measuring the local orientation difference average value of the fatigue damage component to be evaluated.

[0078] Step 800: determining the stress corrosion sensitivity value of the fatigue damage component to be evaluated according to the local orientation difference average value of the fatigue damage component to be evaluated and the linear relationship between the stress corrosion sensitivity value and the local orientation difference average value.

[0079] When the bearing component is damaged, the stress corrosion sensitivity value of the damaged component can be quickly calculated through the KAM measurement of a small part of the material, the KAM average value obtained, and the linear relationship.

[0080] The present application firstly establishes the linear relationship between the damage degree (local orientation difference average value) of the bearing component and the stress corrosion sensitivity. The KAM average value is measured after the pre-fatigue experiment of the measured material, and the slow strain rate tensile experiment is carried out. The stress corrosion sensitivity values of different parameters are measured, and the sensitivity coefficients of the KAM average value and each stress corrosion sensitivity value are calculated. Then, the KAM average value sensitivity coefficient and the sensitivity coefficient corresponding to each stress corrosion sensitivity value are linearly fitted, and the stress corrosion sensitivity value of the parameter with good fitting result is obtained. Thus, the stress corrosion sensitivity of the damaged component can be quickly calculated by measuring the KAM average value.

[0081] In order to better understand the scheme of the present application, the following will be further described by taking the test material 25Cr2Ni2MoV as an example.

[0082] The chemical composition of the test material is shown in Table 1. The bearing component required for the pre-fatigue experiment is processed using the material, and the geometric size of the sample is shown in Table 2. Figure 2 The interrupted fatigue experiment under strain control is carried out on the undamaged sample. The interrupted fatigue experiment load spectrum loading mode is triangular wave loading, the experiment temperature is 25℃, the strain ratio is -1, the strain amplitude is ±0.3%, and the experiment adopts a constant strain loading rate of 0.008mm / mm·s -1 The fatigue life experiment result shows that the average life of 25Cr2Ni2MoV is about 24000 cycles under the current condition. Therefore, the samples with interrupted fatigue cycle times of 5000 cycles, 10000 cycles, 15000 cycles and 20000 cycles are selected to carry out the fatigue damage research.

[0083] Table 1 Chemical composition of 25Cr2Ni2MoV rotor steel base material and weld material

[0084]

[0085] After obtaining the specimens after different cycle fatigue, the EBSD experiment was carried out on the circular specimens with a thickness of 2 mm and a diameter of 11 mm, which were cut from the specimens perpendicular to the axis direction of the pre-fatigue experiment. The electron microscope magnification was 1000 times, and the scanning step was 0.1 μm. Before the experiment, the specimen needed to be ground in turn using SiC sandpaper with particle sizes of 220 mesh, 400 mesh, 800 mesh, 1200 mesh and 2000 mesh, and polished for one hour using an oxide polishing suspension (OP-UN NonDry). After the experiment, the KAM map and the local orientation difference distribution of the specimens after different fatigue cycles were analyzed by Channel5 software. Table 2 is the KAM average value of the material after different cycle loading fatigue calculated.

[0086] Table 2 KAM average value

[0087] Cycle number KAM (°) No fatigue 0.698 5000 cycles 0.579 10000 cycles 0.530 15000 cycles 0.512 20000 cycles 0.503

[0088] After completing the EBSD measurement, the specimens after different cycle loading fatigue were processed into slow strain rate tensile test specimens. The geometric size of the slow strain rate tensile specimen is shown in Figure 3 The slow strain rate tensile test equipment is a stress corrosion test machine produced by the American Cortest company. In order to simulate the actual service process of the component, the stress corrosion cracking sensitivity of the specimen under different fatigue damage was evaluated in the form of 180°C air and 180°C, 3.5% NaCl solution environment contrast experiment. The specimen was ultrasonically cleaned using deionized water, anhydrous ethanol and acetone. The stress-strain curve during the experiment was recorded by the displacement sensor and the load sensor, and the strain loading rate during the experiment was 10 -6 s -1 Three groups of parallel specimens were used under each condition.

[0089] After completing the slow strain rate tensile test, the stress-strain curve of the specimen after different cycle loading fatigue was obtained. The stress corrosion sensitivity value was calculated by taking the tensile strength, yield strength, reduction of area, fracture time and the area contained in the stress-strain curve as parameters. The slow strain rate tensile test results and the stress corrosion sensitivity calculation results are shown in Tables 3 and 4 respectively. The results show that the stress corrosion cracking sensitivity coefficients calculated by the tensile strength and the yield strength are small, and the stress corrosion cracking sensitivity coefficient value calculated by the fracture time is too large, and neither of them is suitable for reflecting the influence of fatigue damage on the stress corrosion cracking performance. Only the change trend of the reduction of area and the stress-strain curve area can better match the change of the KAM value.

[0090] Table 3 Slow strain rate tensile test results

[0091]

[0092] Table 4 Stress corrosion sensitivity calculation results

[0093] σ b is the tensile strength, σ s is the yield strength, is the stress corrosion sensitivity value of the reduction of area, I b is the stress corrosion sensitivity value of the tensile strength, I s is the stress corrosion sensitivity value of the yield strength, I φ is the stress corrosion sensitivity value of the reduction of area, I t is the stress corrosion sensitivity value of the fracture time, I A is the stress corrosion sensitivity value of the curve area.

[0094] The KAM value and the stress corrosion cracking (SCC) sensitivity factor are calculated by the following formula, and the average value of the KAM sensitivity factor D K is linearly fitted with the sensitivity factor D of the reduction of area and the sensitivity factor D IA of the curve area, respectively, and the results are shown in Figure 4 . The results show that D K has a higher degree of linear fitting and better fitting effect than D , so it is determined to use D to represent the stress corrosion sensitivity after damage, and the linear relationship between D K and D is obtained.

[0095]

[0096]

[0097]

[0098] wherein, K i is the average value of KAM after i cycle loading cycles, K0 is the average value of KAM without fatigue damage, is the stress corrosion sensitivity value of the reduction of area after i cycle loading cycles, I is the stress corrosion sensitivity value of the reduction of area without fatigue damage, I Ai is the stress corrosion sensitivity value of the curve area after i cycle loading cycles, I A0To the stress corrosion sensitivity value of the curve surrounding area without fatigue damage.

[0099] After the component is damaged, the influence of fatigue damage on stress corrosion sensitivity can be quickly characterized by measuring the KAM average value of the component according to a linear relationship.

[0100] Embodiment two

[0101] In order to perform the method corresponding to the above-mentioned embodiment one, to realize the corresponding function and technical effect, the following provides a system for quickly evaluating the stress corrosion sensitivity of a fatigue damaged component.

[0102] As Figure 5 shown, the system for quickly evaluating the stress corrosion sensitivity of a fatigue damaged component provided by the embodiment includes a pre-fatigue experiment module 1, a sample processing module 2, a slow strain rate tension module 3, a stress corrosion sensitivity calculation module 4, a linear fitting module 5, a relationship determination module 6, a microstructure measurement module 7, and an evaluation module 8.

[0103] The pre-fatigue experiment module 1 is used to perform a pre-fatigue experiment on an undamaged component sample to obtain a fatigue damaged sample, and measure the local misorientation average value of the fatigue damaged sample.

[0104] The sample processing module 2 is associated with the pre-fatigue experiment module 1, and the sample processing module 2 is used to process the fatigue damaged sample into a slow strain rate tension sample.

[0105] The slow strain rate tension module 3 is associated with the sample processing module 2, and the slow strain rate tension module 3 is used to perform a slow strain rate tension experiment on the slow strain rate tension sample to determine the stress-strain curve of the slow strain rate tension sample.

[0106] The stress corrosion sensitivity calculation module 4 is connected with the slow strain rate tension module 3, and the stress corrosion sensitivity calculation module 4 is used to calculate the stress corrosion sensitivity value corresponding to each candidate parameter according to the stress-strain curve of the slow strain rate tension sample. The candidate parameters include tensile strength, yield strength, reduction of area, fracture time, and curve surrounding area.

[0107] The linear fitting module 5 is respectively connected with the pre-fatigue experiment module 1 and the stress corrosion sensitivity calculation module 4, and the linear fitting module 5 is used to respectively linearly fit the stress corrosion sensitivity value corresponding to each candidate parameter with the local misorientation average value of the fatigue damaged sample, and determine the candidate parameter with the best linear fitting effect.

[0108] The relationship determining module 6 is connected with the linear fitting module 5, and is configured to determine a linear relationship between the stress corrosion sensitivity value and the local misorientation average value according to a linear fitting result of the stress corrosion sensitivity value and the local misorientation average value corresponding to the candidate parameter with the best linear fitting effect.

[0109] The microstructure measuring module 7 is configured to measure the local misorientation average value of the fatigue damage component to be evaluated.

[0110] The evaluation module 8 is connected with the relationship determining module 6 and the microstructure measuring module 7 respectively, and is configured to determine the stress corrosion sensitivity value of the fatigue damage component to be evaluated according to the local misorientation average value of the fatigue damage component to be evaluated and the linear relationship between the stress corrosion sensitivity value and the local misorientation average value.

[0111] Compared with the prior art, the system for quickly evaluating the stress corrosion sensitivity of the fatigue damage component provided in the embodiment has the same beneficial effects as the method for quickly evaluating the stress corrosion sensitivity of the fatigue damage component provided in the first embodiment, and thus the repeated description is omitted here.

[0112] Embodiment Three

[0113] The embodiment provides an electronic device, including a memory and a processor, the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic device to execute the method for quickly evaluating the stress corrosion sensitivity of the fatigue damage component in the first embodiment.

[0114] Optionally, the electronic device can be a server.

[0115] In addition, the embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method for quickly evaluating the stress corrosion sensitivity of the fatigue damage component in the first embodiment.

[0116] The embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and the same or similar parts of each embodiment can be referred to each other.

[0117] The principles and implementation manners of the present application are described by using specific examples in the present application, and the above description of the embodiments is only used to help understand the method of the present application and its core idea; meanwhile, for the general technical personnel in the art, the specific implementation manners and application ranges can be changed according to the idea of the present application. In conclusion, the content of the specification should not be understood as the limitation of the present application.

Claims

1. A method for rapidly evaluating the stress corrosion susceptibility of a fatigue-damaged component, characterized by, The method for rapidly evaluating stress corrosion sensitivity of a fatigue-damaged component comprises the following steps: The pre-fatigue experiment is performed on the undamaged component sample to obtain a fatigue-damaged sample, and the average value of the local orientation difference of the fatigue-damaged sample is measured, specifically including the following steps: the interrupted fatigue experiment under strain control is performed on the undamaged component sample to obtain a fatigue-damaged sample, and a sample with a set size is cut along the direction perpendicular to the axis of the fatigue-damaged sample to obtain a microscopic observation sample; the microscopic observation sample is subjected to sandpaper grinding treatment, and then polished using an oxide polishing suspension, and then subjected to backscattered electron diffraction measurement to obtain a local orientation difference map of the fatigue-damaged sample; the average value of the local orientation difference of the fatigue-damaged sample is determined according to the local orientation difference map of the fatigue-damaged sample; The fatigue-damaged sample is processed into a slow strain rate tensile sample, specifically including the following steps: a slow strain rate tensile sample with a set size is cut along the direction parallel to the axis of the fatigue sample; The slow strain rate tensile experiment is performed on the slow strain rate tensile sample to determine the stress-strain curve of the slow strain rate tensile sample; According to the stress-strain curve of the slow strain rate tensile sample, a stress corrosion sensitivity value corresponding to each candidate parameter is calculated; the candidate parameter is calculated by using the following formula j The corresponding stress corrosion sensitivity value is: ; wherein, I j The candidate parameter j corresponds to the stress corrosion sensitivity value, SSRT s,j The value of the candidate parameter j after the slow strain rate tensile experiment, SSRT a,j The value of the candidate parameter j in an inert environment; the candidate parameters include tensile strength, yield strength, reduction of area, fracture time and curve area. linearly fitting the stress corrosion sensitivity value corresponding to each candidate parameter with the local misorientation average value of the fatigue damage sample, and determining the candidate parameter with the best linear fitting effect, specifically comprising: calculating a sensitive factor of the local misorientation average value according to the local misorientation average value of the fatigue damage sample: ; wherein, D K the sensitive factor of the local misorientation average value, K i the local misorientation average value after i cycle loading weeks, K 0 is the local misorientation average value without fatigue damage; for any candidate parameter, calculating a sensitive factor of the candidate parameter according to the stress corrosion sensitivity value of the candidate parameter: ; wherein, D I the sensitive factor of the candidate parameter, I i the stress corrosion sensitivity value after i cycle loading weeks, I 0 is the stress corrosion sensitivity value without fatigue damage; linearly fitting the sensitive factor of the local misorientation average value with the sensitive factor of each candidate parameter, and determining the optimal parameter according to the linear fitting result; the optimal parameter is the candidate parameter corresponding to the sensitive factor with the highest fitting degree; determining the candidate parameter with the best linear fitting effect according to the stress corrosion sensitivity value of the optimal parameter and the local misorientation average value of the fatigue damage sample; The linear relationship between the stress corrosion sensitivity value and the average value of the local orientation difference is determined according to the linear fitting result of the stress corrosion sensitivity value corresponding to the candidate parameter with the best linear fitting effect and the average value of the local orientation difference of the fatigue-damaged sample; The average value of the local orientation difference of the fatigue-damaged component to be evaluated is measured; The stress corrosion sensitivity value of the fatigue-damaged component to be evaluated is determined according to the average value of the local orientation difference of the fatigue-damaged component to be evaluated and the linear relationship between the stress corrosion sensitivity value and the average value of the local orientation difference.

2. The method for rapidly evaluating stress corrosion susceptibility of a fatigue-damaged component according to claim 1, characterized by, The number of the undamaged component samples is multiple; the cycle loading times of the pre-fatigue experiments of the undamaged component samples are different.

3. A system for rapidly evaluating stress corrosion susceptibility of a fatigue-damaged component, applied to the method for rapidly evaluating stress corrosion susceptibility of a fatigue-damaged component according to any one of claims 1 to 2, characterized by, The system for rapidly evaluating stress corrosion sensitivity of a fatigue-damaged component comprises: The pre-fatigue experiment module is used to perform a pre-fatigue experiment on an undamaged component sample to obtain a fatigue-damaged sample, and measure the average value of the local orientation difference of the fatigue-damaged sample; The sample processing module is associated with the pre-fatigue experiment module and is used to process the fatigue-damaged sample into a slow strain rate tensile sample; The slow strain rate tensile module is connected with the sample processing module and is used to perform a slow strain rate tensile experiment on the slow strain rate tensile sample to determine the stress-strain curve of the slow strain rate tensile sample; The stress corrosion sensitivity calculation module is connected with the slow strain rate tensile module and is used to calculate the stress corrosion sensitivity value corresponding to each candidate parameter according to the stress-strain curve of the slow strain rate tensile sample; the candidate parameters include tensile strength, yield strength, reduction of area, fracture time and curve area; The linear fitting module is respectively connected with the pre-fatigue experiment module and the stress corrosion sensitivity calculation module, and is used to respectively perform linear fitting on the stress corrosion sensitivity value corresponding to each candidate parameter and the average value of the local orientation difference of the fatigue-damaged sample, and determine the candidate parameter with the best linear fitting effect. The relationship determining module is connected with the linear fitting module, and is configured to determine a linear relationship between the stress corrosion sensitivity value and the local misorientation average value according to a linear fitting result of the stress corrosion sensitivity value corresponding to the candidate parameter with the best linear fitting effect and the local misorientation average value of the fatigue damage sample; The microstructure measuring module is configured to measure the local misorientation average value of the fatigue damage component to be evaluated; The evaluation module is connected with the relationship determining module and the microstructure measuring module respectively, and is configured to determine the stress corrosion sensitivity value of the fatigue damage component to be evaluated according to the local misorientation average value of the fatigue damage component to be evaluated and the linear relationship between the stress corrosion sensitivity value and the local misorientation average value.

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