Metal material fatigue life prediction method based on plastic damping theory
By combining plastic damping theory with dynamic mechanical analysis, a fatigue life prediction model for metal materials is established, which solves the problem of low prediction accuracy of existing methods under irregular loads and achieves more accurate fatigue life prediction and a simple testing process.
Patent Information
- Application Number
- CN202510897592.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-01
- Publication Date
- 2025-10-17
AI Technical Summary
Existing fatigue life prediction methods for metal materials have problems in practical engineering, such as poor applicability, large computational workload, poor operability, and low prediction accuracy. In particular, it is difficult to accurately reflect the microstructural evolution of the material under irregular loads.
A method based on the combination of plastic damping theory and dynamic mechanical analysis technology is adopted. By conducting cyclic variable amplitude load fatigue failure tests on metal materials, strain and damping data are collected in real time. A quantitative relationship between plastic damping and fatigue life is established. Combining the plastic strain-stress model and the stress-fatigue life model, a fatigue life prediction model is constructed, and predictions are made through non-destructive damping performance tests.
It is closer to the actual service environment, improves the accuracy of fatigue life prediction and ease of operation, is applicable to a variety of metal materials, reduces testing costs, and can reflect the evolution of material microstructure.
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Figure CN120801068A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the field of material mechanical property testing, in particular to a metal material fatigue life prediction method based on plastic damping theory, which is suitable for engineering fields such as aerospace, automobile manufacturing, mechanical engineering, etc. that need to accurately evaluate the fatigue life of metal components. BACKGROUND
[0002] Fatigue and fracture are the main causes of engineering structure and component failure. According to a large number of statistical results, about 80% of the fracture accidents of various machines are caused by fatigue failure of metal materials. This alarming proportion highlights the importance of accurately predicting the fatigue life of metal materials for ensuring the safety and reliability of mechanical parts, components and even entire equipment.
[0003] Fatigue life prediction is a key problem in the field of materials science and engineering, and it is particularly important in high-demand applications such as aerospace and automobiles. Accurate prediction of the fatigue life of metal materials under cyclic loading not only significantly improves the safety and reliability of structures, but also effectively prevents potential structural failure and reduces maintenance costs.
[0004] Currently, fatigue life prediction methods show a trend from global to local, from macro to micro, and from uniaxial fatigue to multiaxial fatigue. Existing stress fatigue life models, strain fatigue life models, energy models, damage mechanics models, fracture mechanics models, and stress field intensity models are mostly based on deterministic fatigue S-N curves and are mainly used to estimate the fatigue life of structures under constant amplitude loading. However, in actual engineering, most mechanical components usually serve under a series of loadings with varying amplitudes over time.
[0005] Although many researchers have studied the variable amplitude fatigue life of materials based on S-N curves, due to factors such as original defects in materials and part size, the applicability of fatigue prediction models in engineering is poor, and there are problems such as large computational workload and poor operability. In addition, due to the large differences between material samples, the dispersion of fatigue life is large, which is also an important reason for the low accuracy of fatigue prediction models in prediction.
[0006] Fatigue fracture failure is usually caused by repeated changes in load, and fatigue is a cumulative damage process accompanied by microstructure evolution, often involving the formation and propagation of micro-cracks in metal materials. This microstructure change is difficult to evaluate through destructive testing. Damping performance testing is a non-destructive test, and the damping performance of metal materials can effectively reflect the existence and movement of internal defects in the fatigue process, as well as the configuration and interaction of various structural defects, thereby obtaining relevant information about the microstructure of metal materials during fatigue.
[0007] Therefore, in order to more truly simulate the amplitude load history of the device and better predict the actual fatigue life of the metal material, how to predict the fatigue life of the metal material based on the damping performance of the metal material is a problem to be solved by researchers in the field. SUMMARY
[0008] To solve the above technical problems, the application provides a metal material fatigue life prediction method based on plastic damping theory, which realizes high-precision prediction of the fatigue life of the metal material by combining plastic damping theory with dynamic mechanical analysis technology, and provides an effective means for reliability evaluation of engineering components.
[0009] The application aims to provide a metal material fatigue life prediction method based on plastic damping theory.
[0010] The above application purpose of the application is achieved by the following technical scheme:
[0011] A metal material fatigue life prediction method based on plastic damping theory, the method comprising the following steps:
[0012] Performing a fatigue failure test on a standard sample of a target metal material under cyclic amplitude load, and collecting strain data and damping data in real time during the test process, to obtain a complete fatigue failure data sequence of the standard sample;
[0013] Based on the fatigue failure data sequence, calculating the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample;
[0014] Based on the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample, combining a plastic strain-stress model and a stress-fatigue life model, obtaining a fatigue life prediction model;
[0015] Performing a damping performance test on a to-be-tested sample of the target metal material after fatigue treatment, to obtain strain data and damping data of the to-be-tested sample;
[0016] Based on the strain data and damping data of the to-be-tested sample, calculating the plastic strain and corresponding plastic damping of the to-be-tested sample;
[0017] Based on the plastic damping of the to-be-tested sample and the fatigue life prediction model, solving to obtain the fatigue life of the to-be-tested sample.
[0018] Preferably, the fatigue failure test on the standard sample of the target metal material under cyclic amplitude load comprises:
[0019] Manufacturing the target metal material that has not been subjected to fatigue treatment into a sample with a shape and size suitable for a dynamic mechanical analyzer, to obtain the to-be-tested sample;
[0020] performing a fatigue failure test on the to-be-tested sample according to preset first fatigue test parameters by using the dynamic mechanical analyzer, until the to-be-tested sample occurs fatigue failure, wherein,
[0021] The first fatigue test parameters include a loading frequency, a strain loading amplitude, and a test temperature.
[0022] Preferably, the calculating the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample based on the fatigue failure data sequence comprises:
[0023] drawing a damping strain curve under different cycle numbers based on the strain data and the corresponding damping data in the fatigue failure data sequence;
[0024] determining a second critical strain value per cycle by solving a second derivative of the damping strain curve, wherein the second critical strain value is a minimum strain value at which plastic deformation starts, that is, a maximum absolute value of a positive to negative change of the second derivative of the damping strain curve;
[0025] calculating the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample based on the determined second critical strain value and the strain data and the corresponding damping data in the fatigue failure data sequence.
[0026] Preferably, the calculating the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample based on the fatigue failure data sequence comprises:
[0027] calculating the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample based on the strain data and the corresponding damping data in the fatigue failure data sequence, in combination with dislocation damping theory and plastic damping theory.
[0028] Preferably, the calculating the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample based on the strain data and the corresponding damping data in the fatigue failure data sequence, in combination with dislocation damping theory and plastic damping theory comprises:
[0029] drawing a damping strain curve under different cycle numbers based on the strain data and the corresponding damping data in the fatigue failure data sequence;
[0030] determining a first critical strain value per cycle by solving a first derivative of the damping strain curve, wherein the first critical strain value is a minimum strain value at which strain amplitude and damping have a correlation, that is, a minimum strain value corresponding to a monotonous increase when the first derivative of the damping strain curve is greater than 0;
[0031] drawing a G-L curve of a fatigue process of the standard sample during the fatigue failure test based on the strain data and corresponding damping data in the fatigue failure data sequence, the first critical strain value, and the dislocation damping theory;
[0032] preliminarily determining a second critical strain value based on the dislocation damping theory and the G-L curve, wherein the second critical strain value is a minimum strain at which plastic deformation begins to occur;
[0033] drawing a plastic damping fitting curve of the fatigue process of the standard sample during the fatigue failure test based on the plastic damping theory and the preliminarily determined second critical strain value, to verify the accuracy of the second critical strain value through the plastic damping fitting curve;
[0034] calculating plastic damping corresponding to a maximum plastic strain per cycle of the standard sample based on the verified second critical strain value and the strain data and corresponding damping data in the fatigue failure data sequence.
[0035] Preferably, the fatigue life prediction model obtained based on the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample, in combination with a plastic strain-stress model and a stress-fatigue life model, comprises:
[0036] constructing a functional relationship between plastic strain and fatigue life based on the plastic strain-stress model and the stress-fatigue life model;
[0037] substituting the functional relationship between plastic strain and fatigue life into a plastic damping model to obtain a functional relationship between plastic damping and fatigue life;
[0038] performing data fitting on parameters in the functional relationship between plastic damping and fatigue life based on the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample, to obtain numerical values of the parameters;
[0039] substituting the obtained numerical values of the parameters into the functional relationship between plastic damping and fatigue life to obtain an initial fatigue life prediction model.
[0040] Preferably, the fatigue life prediction model obtained based on the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample, in combination with a plastic strain-stress model and a stress-fatigue life model, further comprises:
[0041] after substituting the obtained numerical values of the parameters into the functional relationship between plastic damping and fatigue life to obtain an initial fatigue life prediction model, introducing an initial state correction factor and a residual life prediction factor into the initial fatigue life prediction model to obtain a corrected fatigue life prediction model.
[0042] Preferably, the damping performance test on the target metal material sample after fatigue treatment to obtain the strain data and damping data of the sample under test comprises:
[0043] The dynamic mechanical analyzer is used to perform a cycle of variable amplitude load fatigue failure test on the sample under test according to the preset second fatigue test parameters to obtain the strain data and damping data of the sample under test, wherein,
[0044] The second fatigue test parameters include loading frequency, strain loading amplitude and test temperature, and the loading frequency, strain loading amplitude and test temperature in the second fatigue test parameters are the same as those in the first fatigue test parameters.
[0045] Preferably, the calculation of the plastic strain and the corresponding plastic damping of the sample under test based on the strain data and the damping data of the sample under test comprises:
[0046] Based on the strain data and the damping data of the sample under test, the maximum plastic strain and the corresponding plastic damping of the sample under test at the current cycle are calculated.
[0047] Correspondingly, the fatigue life of the sample under test is solved based on the plastic damping of the sample under test and the fatigue life prediction model.
[0048] The maximum plastic strain of the sample under test at the current cycle is input into the fatigue life prediction model to solve the fatigue life of the sample under test.
[0049] Compared with the existing metal material fatigue life prediction method, the above technical solutions of the present application have the following beneficial effects:
[0050] 1. More close to the actual service environment: Compared with the regular load fatigue loading, the cycle variable amplitude load fatigue failure test method used in the present application is more close to the irregular load of the material in the service environment, and can more truly simulate the actual stress state of the material.
[0051] 2. Reflecting the evolution of material microstructure: The fatigue life prediction model proposed in the present application is based on the plastic damping theory, which can effectively reflect the evolution of material microstructure, better present the fatigue state of the material, and predict the fatigue life. Through the non-destructive test parameter of damping performance, the micro changes such as the formation of internal defects and the expansion of micro cracks of the material can be captured, and the shortcomings that the existing method is difficult to evaluate the influence of microstructure are overcome.
[0052] 3. Improve the prediction accuracy: combined with the plastic strain-stress model and stress-fatigue life model, the quantitative relationship between plastic damping and fatigue life is established, and the prediction accuracy of the model is improved through data fitting and correction factor adjustment;
[0053] 4. Simple operation and wide applicability: the method is based on dynamic mechanical analysis, and the test process is relatively simple. It is suitable for a variety of metal materials, including pure metals, alloys, etc., overcoming the limitations of existing methods on material types;
[0054] 5. Non-destructive testing, low cost: using damping performance testing as a non-destructive testing method, destructive testing is avoided, repeated testing is possible, testing costs are reduced, and fatigue monitoring of materials in actual service is also possible. BRIEF DESCRIPTION OF DRAWINGS
[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.
[0056] Figure 1 It is a flowchart of a metal material fatigue life prediction method based on plastic damping theory in an embodiment of the present application;
[0057] Figure 2A It is a damping fatigue curve of pure Sn without power supply;
[0058] Figure 2B It is a damping fatigue curve of pure Sn with a current density of 75A / cm 2 ;
[0059] Figure 3A It is a damping strain curve of pure Sn under different cycle times without power supply;
[0060] Figure 3B It is a damping strain curve of pure Sn under different cycle times with a current density of 75A / cm 2 ;
[0061] Figure 4A It is a G-L curve of pure Sn in the fatigue deformation process without power supply;
[0062] Figure 4B It is a G-L curve of pure Sn in the fatigue deformation process with a current density of 75A / cm 2 ;
[0063] Figure 5AFitting curve of plastic damping for pure Sn in fatigue process without current
[0064] Figure 5B Fitting curve of plastic damping for pure Sn in fatigue process with current density 75 A / cm 2
[0065] Figure 6A Fitting curve of plastic damping and fatigue life function relationship for pure Sn in fatigue process without current and confidence band
[0066] Figure 6B Fitting curve of plastic damping and fatigue life function relationship for pure Sn in fatigue process with current density 75 A / cm 2 DETAILED DESCRIPTION
[0067] In order to make the skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by the skilled in the art without creative labor fall within the scope of protection of the present application.
[0068] In the embodiments provided in the present application, it should be understood that the disclosed method and system can be implemented in other ways. The system embodiments described below are only schematic. For example, the division of the units and modules is only a logical function division, and there can be another division manner in actual implementation. For example, a plurality of units or modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the various components shown or discussed can be indirect coupling or communication connection through some interfaces, devices or modules, and can be electrical, mechanical or other forms.
[0069] In addition, each functional unit in each embodiment of the present application can be integrated into one processor, or each unit can be a separate device, or two or more units can be integrated into one device. Each functional unit in each embodiment of the present application can be realized in the form of hardware or in the form of hardware plus software functional unit.
[0070] Those skilled in the art can understand that all or part of the steps of the following method embodiments can be completed by program instructions and related hardware. The aforementioned program instructions can be stored in a computer readable storage medium, and the program instructions execute the steps of the method embodiments when executed. The aforementioned storage medium includes a mobile storage device, a read only memory (ROM), a magnetic disc or an optical disc, and various storage media that can store program codes.
[0071] In addition, the terms "first", "second", "third", etc. are used only to describe various conditions, and are not to be construed as indicating or implying relative importance or a specific number of the technical features indicated thereby. Thus, the features defined with "first", "second", "third", etc. can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" or "several" is two or more, unless otherwise explicitly and specifically limited.
[0072] The present application provides a method for testing the damping performance of a material by a dynamic mechanical analyzer, dividing the plastic damping of each cycle loading process of the material according to the damping strain curve, combining a plastic strain-stress model and a stress-fatigue life model, and establishing a fatigue life prediction model based on plastic damping. The specific implementation steps of the method are as follows:
[0073] 1) Standard sample preparation and test equipment
[0074] ① Standard sample preparation
[0075] The standard sample for testing fatigue can be used for dynamic mechanical analysis, regardless of the forming method;
[0076] ② Test equipment
[0077] Any instrument that can measure the damping performance of the sample can be used, such as a dynamic mechanical analyzer;
[0078] 2) Test process
[0079] ① First, the prepared sample is subjected to a fatigue failure test on the dynamic mechanical analyzer to obtain strain data and damping data during each cycle of loading;
[0080] ② Then, the damping performance of the sample to be tested after fatigue treatment (actual use) is tested within the corresponding strain range on the dynamic mechanical analyzer;
[0081] 3) Fatigue life prediction of the actual used sample to be tested
[0082] ①Firstly, the sample damping fatigue failure experimental data is processed, the plastic strain and plastic damping of the material per cycle are calculated according to the dislocation damping theory of Granato-Lücke and the plastic damping theory of Peguin, the plastic strain-stress model and the stress-fatigue life model are combined to obtain the fatigue life prediction model, and the parameters in the fatigue life prediction model are obtained by fitting with the data processing software;
[0083] ②The plastic strain and the corresponding plastic damping of the data obtained from the actual used sample to be tested are calculated, and then the life of the sample is predicted according to the fatigue life prediction model.
[0084] As Figure 1 shown, the embodiment of the present application provides a metal material fatigue life prediction method based on plastic damping theory, which can include the following steps:
[0085] S1, the standard sample of the target metal material is subjected to fatigue failure test under cyclic variable amplitude load, and the strain data and damping data in each cycle of the loading process are collected in real time during the test to obtain the complete fatigue failure data sequence of the standard sample;
[0086] Specifically, the process of the fatigue failure test of the standard sample of the target metal material under cyclic variable amplitude load is as follows:
[0087] The target metal material which has not been subjected to fatigue treatment is made into a sample with a shape and size suitable for a dynamic mechanical analyzer to obtain a to-be-tested sample;
[0088] The dynamic mechanical analyzer is used to perform fatigue failure test on the to-be-tested sample under cyclic variable amplitude load according to the first fatigue test parameters, until the to-be-tested sample fails, wherein,
[0089] The first fatigue test parameters include loading frequency, strain loading amplitude and test temperature.
[0090] S2, the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample is calculated based on the fatigue failure data sequence, which can be calculated by one of the following two methods:
[0091] Method one:
[0092] The damping strain curve under different cycle numbers is plotted based on the strain data and the corresponding damping data in the fatigue failure data sequence;
[0093] The second critical strain value per cycle is determined by solving the second derivative of the damping strain curve, wherein the second critical strain value is the minimum strain value at which plastic deformation begins, that is, the maximum absolute value of the second derivative of the damping strain curve changes from positive to negative;
[0094] Based on the determined second critical strain value and the strain data and corresponding damping data in the fatigue failure data sequence, the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample is calculated.
[0095] Method two:
[0096] Based on the strain data and corresponding damping data in the fatigue failure data sequence, the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample is calculated by combining dislocation damping theory and plastic damping theory, and the specific process is as follows:
[0097] Based on the strain data and corresponding damping data in the fatigue failure data sequence, the damping strain curve under different cycle numbers is drawn;
[0098] The first critical strain value of each cycle is determined by solving the first derivative of the damping strain curve, wherein the first critical strain value is the minimum strain when the strain amplitude and the damping have a correlation, that is, the minimum strain value corresponding to the first derivative of the damping strain curve greater than 0 and monotonically increasing;
[0099] Based on the strain data and corresponding damping data in the fatigue failure data sequence, the first critical strain value and the dislocation damping theory, the G-L curve of the fatigue process when the standard sample is tested for fatigue failure is drawn;
[0100] Based on the dislocation damping theory and the G-L curve, the second critical strain value is preliminarily determined, wherein the second critical strain value is the minimum strain at which plastic deformation begins to occur;
[0101] Based on the plastic damping theory and the preliminarily determined second critical strain value, the plastic damping fitting curve of the fatigue process when the standard sample is tested for fatigue failure is drawn, so as to verify the accuracy of the second critical strain value through the plastic damping fitting curve;
[0102] Based on the verified second critical strain value and the strain data and corresponding damping data in the fatigue failure data sequence, the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample is calculated.
[0103] S3, based on the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample, combining the plastic strain-stress model and the stress-fatigue life model, the fatigue life prediction model is obtained, and the specific process is as follows:
[0104] Based on the plastic strain-stress model and the stress-fatigue life model, a functional relationship between plastic strain and fatigue life is constructed;
[0105] The functional relationship between plastic strain and fatigue life is substituted into the plastic damping model to obtain the functional relationship between plastic damping and fatigue life;
[0106] The parameters in the functional relationship between the plastic damping and the fatigue life are fitted based on the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample, and the numerical values of the parameters are obtained.
[0107] The numerical values of the parameters are substituted into the functional relationship between the plastic damping and the fatigue life to obtain an initial fatigue life prediction model.
[0108] Further, the fatigue life prediction model construction process can further include:
[0109] After substituting the numerical values of the parameters into the functional relationship between the plastic damping and the fatigue life to obtain an initial fatigue life prediction model, an initial state correction factor and a residual life prediction factor are introduced into the initial fatigue life prediction model to obtain a corrected fatigue life prediction model.
[0110] S4, the damping performance of the target metal material after fatigue treatment is tested, and the strain data and damping data of the test sample are obtained, and the specific process is as follows:
[0111] The dynamic mechanical analyzer is used to perform a cycle of variable amplitude load fatigue failure test on the test sample according to the preset second fatigue test parameters, and the strain data and damping data of the test sample are obtained, wherein,
[0112] The second fatigue test parameters include loading frequency, strain loading amplitude and test temperature, and the loading frequency, strain loading amplitude and test temperature in the second fatigue test parameters are the same as the loading frequency, strain loading amplitude and test temperature in the first fatigue test parameters.
[0113] S5, based on the strain data and damping data of the test sample, the plastic strain and the corresponding plastic damping of the test sample are calculated, that is, based on the strain data and damping data of the test sample, the maximum plastic strain and the corresponding plastic damping of the test sample under the current cycle are calculated.
[0114] S6, based on the plastic damping of the test sample and the fatigue life prediction model, the fatigue life of the test sample is solved, that is, the plastic damping corresponding to the maximum plastic strain of the test sample under the current cycle is input into the fatigue life prediction model, and the fatigue life of the test sample is solved.
[0115] In summary, the fatigue life prediction method of metal materials based on plastic damping theory in this embodiment first performs a fatigue failure test of a cyclic variable amplitude load on a standard sample of the target metal material, and collects the strain data and damping data of each cycle of loading in real time during the test to obtain a complete fatigue failure data sequence of the standard sample; then, the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample is calculated based on the fatigue failure data sequence; then, based on the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample, combined with the plastic strain-stress model and the stress-fatigue life model, a fatigue life prediction model is obtained; then, a damping performance test is performed on the test sample of the target metal material after fatigue treatment to obtain the strain data and damping data of the test sample; then, based on the strain data and damping data of the test sample, the plastic strain and corresponding plastic damping of the test sample are calculated; finally, based on the plastic damping of the test sample and the fatigue life prediction model, the fatigue life of the test sample is solved.
[0116] Compared with the traditional SN curve model, the prediction method of the embodiment of the present application is closer to the variable amplitude load conditions of the material during service through cyclic damping testing; based on the plastic damping theory, it can reflect microscopic processes such as dislocation movement and defect evolution inside the material, thereby improving the prediction accuracy; non-destructive damping testing is used for the test samples to avoid destructive testing, and the data processing efficiency is high, which is suitable for rapid evaluation on engineering sites.
[0117] The technical solution provided in this application can realize the prediction of material fatigue life. In order to more clearly demonstrate the working principle and technical effect of the metal material fatigue life prediction method based on plastic damping theory in this application, it is explained in detail through the following examples.
[0118] In this example, the target metal material is pure tin, and the standard sample is a pure tin sheet with a size of 60×5×0.8mm. 3 The test temperature is room temperature, the loading frequency is 1.0 Hz, the strain loading amplitude is 0.113%, and the data of the damping and strain changes with time (number of cycles) are obtained under no power and 75 A / cm2 current density. Figure 2A and Figure 2B As shown (the horizontal axis is the number of cycles, and the vertical axis is the damping corresponding to the maximum strain per cycle), Figure 2A and Figure 2B The pure tin sheet is shown in the condition of no electricity and 75A / cm 2 The curve of the damping value changing with the number of cycles when the current density is 1.5 Ω. As can be seen from the figure, with the increase of the number of cycles, the damping value shows a certain trend of change, reflecting the performance evolution of the material during the fatigue process;
[0119] The cyclic stress-strain response of pure tin is dominated by cyclic softening, which is a process accompanied by mean stress relaxation and can be described by the Landgraf model:
[0120] σ mN = σ mi N r ,
[0121] where σ mi is the initial mean stress value, σ mN is the mean stress value after N cycles, M is a constant, ε a is the strain amplitude (half amplitude), and ε ath is the threshold value of strain amplitude. M and ε ath can be regarded as fitting constants. The mean stress in one cycle is defined as:
[0122]
[0123] where σ m is the mean stress value in one cycle, σ min is the minimum stress value in one cycle, and σ max is the maximum stress value in one cycle. In this example, the minimum stress is almost zero, so the mean stress is half of the maximum stress. Combining equation (1) and equation (2), the relationship between σ maxN and N (i.e., the stress-fatigue life model) can be obtained as:
[0124] σ maxN = σ maxi N r (3)
[0125] where σ maxN is the maximum stress value in the Nth cycle, and σ maxi is the initial maximum stress value.
[0126] The cyclic stress-plastic strain curve can be described by the following equation (i.e., the plastic strain-stress model):
[0127]
[0128] where ε ap is the plastic strain amplitude (i.e., the maximum plastic strain) in one cycle, σ a is the stress amplitude (i.e., the maximum stress) in one cycle, K' is the cyclic strength coefficient, and n' is the cyclic strain hardening exponent. Since σ a = σ max , equation (3) is substituted into equation (4) to obtain the functional relationship between plastic strain and fatigue life:
[0129] ε ap =P×N q (5)
[0130] in,
[0131] σ maxi is the initial maximum stress.
[0132] At lower strains, the relationship between damping and strain amplitude can be divided into three stages. The strain amplitude is independent of damping stage, and its strain amplitude is lower than the first critical strain value ε cr1 , the first critical strain value ε cr1 is the minimum strain when the strain amplitude is correlated with the damping, that is, the minimum strain value corresponding to the first-order derivative of the damping strain curve is greater than 0 and monotonically increases; in the strain amplitude-dependent damping stage, the strain amplitude is at the first critical strain value ε cr1 and the second critical strain value ε cr2 Between, ε cr2 It is the minimum strain at which plastic deformation begins, that is, the minimum strain value corresponding to the maximum absolute value of the second-order derivative of the damping strain curve from positive to negative; plastic damping is also the damping stage where the strain amplitude is strongly correlated, and its strain amplitude is higher than the second critical strain value ε cr2 ,like Figure 3A and Figure 3B As shown, Figure 3A and Figure 3B The pure tin sheet is shown in the condition of no electricity and 75A / cm 2 The damping-strain relationship curves for different cycle numbers at different current densities are shown. The curves are divided into three stages: strain amplitude-independent damping, strain amplitude-dependent damping, and plastic damping, clearly reflecting the changing characteristics of damping performance under different strain amplitudes.
[0133] According to the dislocation damping model proposed by Granato and Lücke (i.e., the Granato-Lücke dislocation damping model), when the strain amplitude is greater than the first critical strain value ε cr1 hour, With ε -1 A linear relationship ( represents the strain amplitude-dependent damping), both of which are only present at the second critical strain value ε cr2 The following can be well fitted into a linear relationship. Due to the second critical strain value ε cr2 represents the beginning of plastic deformation, and the strain range in this embodiment is fixed, so the second critical strain value ε cr2 The size of is used to calculate the plastic strain of the sample during the fatigue process, such as Figure 4A and Figure 4BAs shown, based on the Granato-Lücke dislocation damping theory, Figure 4A and Figure 4B The fatigue process of pure tin sheet is plotted when no power is applied and when a current density of 75A / cm2 is applied. With ε -1 When the strain amplitude is lower than the second critical strain value ε cr2 When , the curve shows a good linear relationship, which verifies the applicability of the dislocation damping model.
[0134] When the strain amplitude exceeds the second critical strain value ε cr2 When , the damping is more strongly affected by the strain amplitude. According to the plastic damping model proposed by Peguin:
[0135]
[0136] in,
[0137] Where ρ is the dislocation density; b is the Burgers vector; ν is the eigenfrequency of the dislocation; f is the test frequency; H is the activation energy; K is a constant; T is the temperature; α is the orientation factor, which is 0.5; V is the dislocation activation volume; G is the elastic shear modulus; h is a constant with a value between 0.5 and 1; and ε is the strain amplitude.
[0138] Since the dislocation activation volume V can be expressed in terms of stress:
[0139]
[0140] σ=Gε
[0141] Combining formula (9), we can see that and (ε-ε cr2 ) 0.5 There is a linear relationship between:
[0142]
[0143] in, is plastic damping.
[0144] This linear relationship further confirms that the irreversible motion of dislocations is the main reason for the increase in damping at higher strain amplitudes, e.g. Figure 5A and Figure 5B As shown, according to Peguin's plastic damping theory, Figure 5A and Figure 5B The results were respectively compared when no power was supplied and when 75A / cm 2 The plastic damping data of the current density is fitted to obtain the relationship between plastic damping and (ε-ε cr2). The fitting results show that plastic damping is related to (ε-ε cr2 ) to the power of 0.5, which is consistent with the theoretical derivation.
[0145] During the test, the maximum strain amplitude per cycle is a constant ε ac Since the plastic deformation increases from the second critical strain value ε cr2 At the beginning, the plastic strain amplitude per cycle ε ap It can be expressed as:
[0146] ε ap =ε ac -ε cr2 (11)
[0147] Substitute ε in formula (11) and formula (5) ap Substituting into formula (7) and taking the logarithm of both sides of the equation, we get:
[0148]
[0149] The deformation can be obtained:
[0150]
[0151] in,
[0152] Among them, formula (12) or formula (13) is the functional relationship between plastic damping and fatigue life. The parameters C1, C2, and q are calculated by the plastic damping corresponding to the maximum plastic strain of each cycle through the test data and substituted into formula (12) or formula (13) to obtain the data fitting by the least squares method. After the values of the parameters C1, C2, and q are obtained through data fitting, the specific values of the parameters C1, C2, and q are substituted into formula (12) or formula (13) to obtain the initial fatigue life prediction model of the target metal material (such as Figure 6A and Figure 6B The functional relationships shown in the figure are: no power and 75A / cm 2 The initial fatigue life prediction model of pure tin metal material under the current condition of current density is shown in Figure 2. Figure 6A and Figure 6B As shown, Figure 6A and Figure 6B The results show the pure tin sheet when it is not powered and when it is powered at 75A / cm 2 The current density, plastic damping and fatigue life data are fitted to obtain A linear relationship curve with N is drawn, and a 95% confidence band is drawn. This curve establishes a quantitative relationship between plastic damping and fatigue life, providing a model basis for fatigue life prediction.
[0153] Since the microstructure of each sample is different, the damping performance of different samples measured under the same conditions also has some differences. Therefore, the initial state correction factor λ and the remaining life prediction correction factor μ are introduced in formula (13):
[0154]
[0155] wherein, is the plastic damping value at the first loading in the fitting data, is the plastic damping value at the first loading in the sample data, the remaining life prediction correction factor μ is 1 when the model is constructed, and is:
[0156]
[0157] wherein, is the non-plastic damping value at the first loading in the fitting data, is the non-plastic damping value at the first loading in the sample data.
[0158] It should be noted that formula (15) is the corrected fatigue life prediction model, wherein N is the fatigue life. When the formula is substituted by the plastic damping calculation, the obtained N is the prior fatigue life, and when the formula is substituted by the non-plastic damping calculation, the obtained N is the remaining fatigue life.
[0159] The samples were subjected to fatigue treatment under the action of no current and 75 A / cm 2 The damping performance of the samples was tested, the damping strain curves were analyzed, and the initial state correction factor λ and the remaining life prediction correction factor μ under the action of no current and 75 A / cm 2 The analysis results were substituted into formula (15) to calculate the prediction results, as shown in Table 1.
[0160] Table 1 Prediction life results of the fatigue life prediction model applied to the prior fatigue of 30, 40, 75, 80 and 100 cycles
[0161]
[0162] From the data in the above table, it can be seen that the method proposed in the application has a smaller prediction error of the fatigue life of metal materials, and the total fatigue life prediction error is controlled at a low level under different prior fatigue cycles and current conditions, fully illustrating the accuracy and reliability of the method.
[0163] The various 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 between the various embodiments can be referred to each other. For the device disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the related parts can be referred to the method part.
[0164] The skilled person can further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in the above description in general terms. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.
[0165] The steps of the method or algorithm described in combination with the embodiments disclosed herein can be directly implemented by hardware, software modules executed by a processor, or a combination of both. The software modules can be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
[0166] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. The present application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for predicting fatigue life of metal materials based on plastic damping theory, characterized in that: The method comprises the following steps: Performing a cyclic variable amplitude load fatigue failure test on a standard sample of the target metal material, and collecting strain data and damping data in real time during each cycle of loading during the test to obtain a complete fatigue failure data sequence of the standard sample; Calculating the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample based on the fatigue failure data sequence; Based on the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample, a fatigue life prediction model is obtained by combining the plastic strain-stress model and the stress-fatigue life model; Performing a damping performance test on a target metal material sample that has been fatigue treated to obtain strain data and damping data of the sample; Calculating the plastic strain and corresponding plastic damping of the sample to be tested based on the strain data and damping data of the sample to be tested; Based on the plastic damping of the sample to be tested and the fatigue life prediction model, the fatigue life of the sample to be tested is obtained by solving.
2. The method for predicting fatigue life of metal materials based on plastic damping theory according to claim 1, characterized in that: The fatigue failure test of the standard sample of the target metal material under cyclic variable amplitude load includes: The target metal material that has not been fatigue treated is made into a sample with a shape and size suitable for a dynamic mechanical analyzer to obtain the sample to be tested; The dynamic mechanical analyzer is used to perform a fatigue failure test of a cyclic variable amplitude load on the sample to be tested according to a preset first fatigue test parameter until the sample to be tested fails due to fatigue, wherein: The first fatigue test parameters include loading frequency, strain loading amplitude and test temperature.
3. The method for predicting fatigue life of metal materials based on plastic damping theory according to claim 1, characterized in that: Calculating the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample based on the fatigue failure data sequence includes: Drawing damping strain curves at different cycle numbers based on the strain data and corresponding damping data in the fatigue failure data sequence; Determining a second critical strain value of each cycle by solving the second derivative of the damping strain curve, wherein the second critical strain value is the minimum strain at which plastic deformation begins to occur, that is, the minimum strain value corresponding to the maximum absolute value of the second derivative of the damping strain curve from positive to negative; The plastic damping corresponding to the maximum plastic strain per cycle of the standard sample is calculated based on the determined second critical strain value and the strain data and corresponding damping data in the fatigue failure data sequence.
4. The method for predicting fatigue life of metal materials based on plastic damping theory according to claim 1, characterized in that: Calculating the plastic damping corresponding to the maximum plastic strain of each cycle of the standard sample based on the fatigue failure data sequence includes: Based on the strain data and corresponding damping data in the fatigue failure data sequence, the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample is calculated in combination with the dislocation damping theory and the plastic damping theory.
5. The method for predicting fatigue life of metal materials based on plastic damping theory according to claim 4, characterized in that: The step of calculating the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample based on the strain data and the corresponding damping data in the fatigue failure data sequence and combining the dislocation damping theory and the plastic damping theory includes: Drawing damping strain curves at different cycle numbers based on the strain data and corresponding damping data in the fatigue failure data sequence; Determining a first critical strain value for each cycle by solving the first-order derivative of the damping strain curve, wherein the first critical strain value is the minimum strain when the strain amplitude is correlated with the damping, that is, the minimum strain value corresponding to the first-order derivative of the damping strain curve being greater than 0 and monotonically increasing; Based on the strain data and corresponding damping data in the fatigue failure data sequence, the first critical strain value, and the dislocation damping theory, plotting a GL curve of the fatigue process of the standard sample when the fatigue failure test is performed; Preliminarily determining a second critical strain value based on the dislocation damping theory and the GL curve, wherein the second critical strain value is the minimum strain at which plastic deformation begins; Drawing a plastic damping fitting curve of the fatigue process of the standard sample during the fatigue failure test based on the plastic damping theory and the preliminarily determined second critical strain value, so as to verify the accuracy of the second critical strain value through the plastic damping fitting curve; Based on the verified second critical strain value and the strain data and corresponding damping data in the fatigue failure data sequence, the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample is calculated.
6. The method for predicting fatigue life of metal materials based on plastic damping theory according to claim 1, characterized in that: The fatigue life prediction model obtained based on the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample, combined with the plastic strain-stress model and the stress-fatigue life model, includes: Based on the plastic strain-stress model and the stress-fatigue life model, constructing a functional relationship between plastic strain and fatigue life; Substituting the functional relationship between the plastic strain and the fatigue life into the plastic damping model to obtain the functional relationship between the plastic damping and the fatigue life; Based on the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample, data fitting is performed on the parameters in the functional relationship between the plastic damping and the fatigue life to obtain the values of the parameters; The obtained values of the parameters are substituted into the functional relationship between the plastic damping and the fatigue life to obtain the initial fatigue life prediction model.
7. The method for predicting fatigue life of metal materials based on plastic damping theory according to claim 6, characterized in that: The fatigue life prediction model obtained based on the plastic damping corresponding to the maximum plastic strain per cycle of the standard sample in combination with the plastic strain-stress model and the stress-fatigue life model also includes: After substituting the obtained numerical values of each parameter into the functional relationship between plastic damping and fatigue life to obtain the initial fatigue life prediction model, an initial state correction factor and a remaining life prediction factor are introduced into the initial fatigue life prediction model to obtain a corrected fatigue life prediction model.
8. The method for predicting fatigue life of metal materials based on plastic damping theory according to claim 1, characterized in that: The damping performance test is performed on the fatigue-treated target metal sample to obtain strain data and damping data of the sample, including: A dynamic mechanical analyzer is used to perform a fatigue failure test of a variable amplitude load on the sample to be tested according to a preset second fatigue test parameter to obtain strain data and damping data of the sample to be tested, wherein: The second fatigue test parameters include loading frequency, strain loading amplitude and test temperature, and the loading frequency, strain loading amplitude and test temperature in the second fatigue test parameters are the same as the loading frequency, strain loading amplitude and test temperature in the first fatigue test parameters.
9. The method for predicting fatigue life of metal materials based on plastic damping theory according to claim 8, characterized in that: The calculating of the plastic strain and the corresponding plastic damping of the sample to be tested based on the strain data and the damping data of the sample to be tested includes: Calculating the maximum plastic strain and corresponding plastic damping of the sample under test in a current cycle based on the strain data and damping data of the sample under test; Accordingly, the step of solving the fatigue life of the sample to be tested based on the plastic damping of the sample to be tested and the fatigue life prediction model includes: The plastic damping corresponding to the maximum plastic strain of the sample to be tested in the current cycle is input into the fatigue life prediction model to solve and obtain the fatigue life of the sample to be tested.