CN109855959A - A kind of prediction technique of Metal Material Fatigue intensity - Google Patents
A kind of prediction technique of Metal Material Fatigue intensity Download PDFInfo
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Abstract
The invention discloses a kind of prediction techniques of Metal Material Fatigue intensity, belong to metal material performance test technical field.Step are as follows: (1) select homologous series material to carry out tensile property test；(2) fatigue property test；(3) parameter fitting: using the stretching and fatigue data measured, the σ of material is acquiredy/σbWith σw/σyValue, then with σy/σbValue is abscissa, with σw/σyValue is that ordinate draws σw/σy‑‑σy/σbRelational graph, and parameter ω and C are acquired by linear fit；(4) σ of material is determined by the tensile property of material to be predictedy/σbValue, the σ of material can be further determined that by the straight line being fittedw/σyValue, to acquire the fatigue strength σ of respective materialwPredicted value.The present invention is by establishing fatigue strength and yield strength, the intrinsic relationship of tensile strength, it is only necessary to which the Fatigue Strength Prediction of all homologous series metal materials can be realized with a small amount of testing fatigue for extension test.
Description
Technical field
The present invention relates to metal material performance test technical fields, and in particular to a kind of prediction of Metal Material Fatigue intensity
Method.
Background technique
As the key index of engineering material long service security reliability under the effect of repeat load, fatigue strength
(refers generally to material and be subjected to 107Maximum stress [Meyers, the M.A.& when fatigue fracture does not occur after secondary alternate load effect
Chawla,K.K.Mechanical behavior of materials(Cambridge University Press,2009)]
Giving more sustained attention for Anti fatigue Design developers is obtained.Fatigue of materials intensity specific value is obtained at present relies primarily on tired survey
Examination obtains load and lifetime data fatigue testing specimen on fatigue tester by way of CYCLIC LOADING, and by further
Reckoning acquire fatigue strength.Specific reckoning mode is broadly divided into two classes, first is that the S-L based on Basquin formula
(S-N) method [Basquin O.H.The exponential law of endurance tests, Proceedings,
ASTM, ASTEA 10 (1910) 625-630.], second is that the confidence limit based on probability statistics-reliability-stress (C-R-S) lifting
Method [GB/T 24176-2009 Metal Material Fatigue test data statistical project and analysis method]；The various methods of follow-up developments
[Yang Yong is raw, a kind of fatigue strength prediction technique by stress amplitude method of Liu Taowei: CN200810043469.8.2009-01-14；Li Jiu
Pattern, Wang Qingyuan, Liu Yongjie, Zhang Hong, Xie Shaoxiong, Hou Fang turbine rotor super high cycle fatigue fatigue strength and Fatigue Life Assessment
Method: CN201610486983.3.2016-12-07.] also basic simplification or amendment derived to above two mode.
Above-mentioned fatigue strength detection method is more rigorous accurate, can carry out specific aim inspection to certain material and loading method
It surveys, obtains reliable result.However also caused several practical problems simultaneously: firstly, two kinds of projectional techniques be required to it is a large amount of tired
Labor data do basis, and the economic cost of testing fatigue and time cost are higher；Secondly, during selection or developing material
It certainly will be related to being compared to each other for homologous series multiple material or same material various states fatigue behaviour, but pass through fatigue detecting and obtain
Results of property it is mutually indepedent, can not utilize storeroom interrelated simplified detection process, causing must to every kind of materials behavior
It must carry out repeating test；Third, contribution ten of the mutually independent fatigue detection result to clear fatigue strength key influence factor
It is point limited, so cause material selection in development process due to a lack of clearly target and the case where blindness trial and error.These problems
The development process of antifatigue design of material is seriously constrained, also reflects that this index of fatigue strength is made in key wherein indirectly
With.Therefore, fatigue detecting how is avoided as far as possible, quickly knows the fatigue strength of homologous series multiple material, is really realized from " inspection
The transformation that " prediction " is arrived in survey ", is to have the problem of great practice significance.
The problem of about Fatigue Strength Prediction, the trial of early stage fromBetween 1870 research work [A.Z.Versuche über Biegung und Verdrehung von Eisbahnwagen–Achsender Fahrt.Z.Bauw.8(1858)641–652.].By the summarizing to a large amount of fatigue datas,
It points out, there are the relationship of approximately linear, formulae express between fatigue of materials intensity and tensile strength are as follows: σw/σb=C, wherein C=0.3
~0.5.The fatigue strength of material is associated with by formula with other mechanical properties for the first time, and thus to tired field
Development produce far-reaching influence.On the one hand, according to this empirical relation, parameter C value is being fitted by available data
Under the premise of, the fatigue strength of material can skip testing process and directly calculate to obtain by tensile strength, convenient and efficient；On the other hand,
What the formula embodied fatigue strength and tensile strength just sets relationship, i.e., fatigue may be implemented by way of improving tensile strength
The raising of intensity, so that the exploitation for antifatigue material provides specific direction.
In recent years, with the continuous development of material science and technology, Materials with High Strength [Gleiter,
H.Nanocrystalline materials.Prog.Mater.Sci.33(1989)223–315；Aggen,G.et al.ASM
handbook properties and selection:Irons,steels,and high-performance alloys
Vol.1 (ASM International, USA, 1990)] it emerges one after another, the research about fatigue strength is it is thus found that new
Problem: when strength of materials raising (is about 1400MPa to steel, is about 480MPa to copper alloy, be about to aluminium alloy to a certain extent
340MPa), if continuing to improve tensile strength, fatigue strength no longer will linearly improve therewith or growth trend obviously slows down, or
Tend to be saturated, or even has downward trend；In this caseFormula is no longer applicable in.Therefore, establish a kind of fatigue strength with
Universality quantitative relationship between tensile property, realizes the quick predict of fatigue strength, becomes current urgent problem to be solved.
Summary of the invention
The purpose of the present invention is to provide a kind of prediction techniques of Metal Material Fatigue intensity, and this method is by establishing fatigue
Intensity and yield strength, the intrinsic relationship of tensile strength, it is only necessary to which all homologys can be realized in extension test and a small amount of testing fatigue
The Fatigue Strength Prediction of column metal material.Engineering material exploitation can be effectively reduced using this method to survey with the fatigue in selection course
Examination is expected to replace repeatedly the antifatigue design of material mode of tradition of trial and error, realizes that real fatigue strength is efficiently predicted.
To achieve the above object, the technical solution adopted in the present invention is as follows:
A kind of prediction technique of Metal Material Fatigue intensity, this method comprises the following steps:
(1) it selects several homologous series metal materials to carry out tensile property test, obtains several groups material yield strength σyWith
Tensile strength sigmabValue；
(2) fatigue property test:
It selects 2-4 kind material to prepare fatigue test specimen in homologous series metal material, fatigue strength test is carried out to it,
Obtain the fatigue strength σ of materialwMeasured value；
(3) parameter fitting:
Using the tensile property data and fatigue strength data measured, the σ of material is acquiredy/σbWith σw/σyValue, then with σy/
σbValue is abscissa, with σw/σyValue is that ordinate draws σw/σy--σy/σbRelational graph, and by linear fit acquire parameter ω with
C, wherein ω is the negative inverse of fitting a straight line slope, and C is fitting a straight line and σy/σbThe intercept of axis；
(4) Fatigue Strength Prediction:
The σ of material is determined by the tensile property of material to be predictedy/σbValue, i.e. σw/σy--σy/σbAbscissa in relational graph
Position can further determine that the σ of material by fitting a straight linew/σyValue, i.e. ordinate position, to acquire the fatigue of respective material
Intensity σwPredicted value；Alternatively, by the tensile property σ of material to be predictedy、σbIt is directly substituted into formula (1) with parameter value ω, C, through counting
Calculate the fatigue strength σ for acquiring respective materialwPredicted value；
In above-mentioned steps (1), selected homologous series metal material refer to same metal material by different predeformation techniques or
The several material obtained after heat treatment.
In above-mentioned steps (1), after the unified processing of homologous series metal material is stretched sample, carried out under same experimental conditions
Tensile property test.
In above-mentioned steps (2), in order to guarantee prediction result accuracy and reduce testing fatigue amount, tensile property should be selected
The biggish 2-4 kind material of difference carries out fatigue property test.
In above-mentioned steps (2), fatigue samples are processed with the material selected, sample surfaces must carry out unified polishing treatment, protect
Demonstrate,prove the consistency of surface state；Then required loading environment is selected uniformly to carry out fatigue property test.
This method is suitable for steel, copper alloy, aluminium alloy or magnesium alloy；Suitable for various predeformation and heat treatment process；It is suitable
It is tension and compression, bending loading method and different cyclic loading ratios and circulation cycle with loading environment.
The advantages of the present invention are as follows:
1, the present invention is solved the problems, such as by tensile property rapid Estimation fatigue strength.The acquisition of fatigue strength is main at present
By testing fatigue, therefore economic cost and time cost remain high.The present invention existsThe basis of formula scheduling theory
On, by the universality quantitative relationship established between fatigue strength and tensile property, effectively reduce engineering material exploitation and selection
A large amount of fatigue experiments test in the process, realizes fatigue of materials intensity and efficiently predicts.
2, the present invention solves the related question between homologous series different conditions fatigue of materials intensity.Real material exploitation and choosing
It often faces during selecting with a series of (basis such as of the same race) different conditions (such as different predeformation amounts, different heat treatment work
Skill etc.) storeroom fatigue strength comparison problem, can only carry out one by one by conventional method testing fatigue obtain it is respective tired
Labor intensity value.Formula major parameter involved in the present invention can regard constant as to homologous series material, and only pass through a small amount of fatigue
Test can determine specific value, thus obtain the efficient predictor formula of the series material fatigue strength, substitute into optionally stretching property
The fatigue strength of respective material can be obtained.This method not only greatly reduces necessary testing fatigue amount, also successfully realizes
Different conditions storeroom fatigue strength it is interrelated, and then the exploitation for antifatigue material and selection provide great side
Just.
3, the present invention combines the deep understanding to fatigue damage essence, proposes completely new fatigue strength theory model；It should
Theoretical key feature is: withFor basic function form, dynamic fatigue is predicted with static tensile
It can be fundamental guiding ideology, by several big influence factors of the fatigue strength such as elastic properties of materials, plasticity, hardening capacity, tissue defects
Integration embodied a concentrated reflection of the basic principle of fatigue damage, and in brief set up fatigue strength σwWith yield strength σy、
Tensile strength σbIntrinsic relationship, combined universality and practicability, embodied the dual value of the theory.
Detailed description of the invention
Fig. 1 is Metal Material Fatigue intensity prediction method flow chart.
Fig. 2 is fatigue strength " lever law " theoretical schematic diagram.
Fig. 3 is different fatigue intensity-tensile strength relationship and Fatigue Strength Prediction σw/σy--σy/σbRelational graph；Wherein:
(a) SPCC and SPRC material σw--σbLinear relationship chart；(b) SPCC and SPRC material σw/σy--σy/σbRelational graph；(c) QBe2 material
Expect σw--σbNon-linear relation figure；(d) QBe2 material σw/σy--σy/σbRelational graph；(e) Cu-5Al material σw--σbNon-linear relation
Figure；(f) Cu-5Al material σw/σy--σy/σbRelational graph.
Fig. 4 is the Fatigue Strength Prediction σ of material under heterogeneity and techniquew/σy--σy/σbRelational graph；Wherein: (a) steel；
(b) copper alloy；(c) aluminium alloy；(d) magnesium alloy.
Fig. 5 is the Fatigue Strength Prediction σ of material under different loading environmentsw/σy--σy/σbRelational graph；Wherein: (a) circulating cycle
Secondary variation；(b) load ratio changes；(c) loading method changes.
Fig. 6 is Fatigue Strength Prediction result Accuracy Verification.
Fig. 7 is the Fatigue Strength Prediction situation of 5052 aluminium alloys in embodiment 1.
Fig. 8 is the Fatigue Strength Prediction situation of Fe-30Mn-0.9C TWIP steel in embodiment 2.
Specific embodiment
Below in conjunction with drawings and examples, the present invention is described in detail.
Fig. 1 is the operating process of the efficient prediction technique of Metal Material Fatigue intensity of the present invention, and this method includes five main
Step: (1) tensile property is tested；(2) fatigue test specimen selects；(3) fatigue property test；(4) parameter fitting；(5) tired
Prediction of strength.It is easy to operate efficient, it is widely used in various different metal materials, technique and loading environment.
This method realizes prediction using fatigue strength " lever law ", and the title is derived from fatigue strength, yield strength and resists
The equilibrium relation of similar lever, formula citation form between tensile strength are as follows:(such as Fig. 2).Wherein σwIt is tired strong
Degree, σyFor yield strength, σbFor tensile strength, parameter respectively relevant to defect and elasticity modulus.To homologous series material, ω,
C is constant, at this time σw/σyWith σy/σbIt is in a linear relationship, pass through the linear fit of two groups or more fatigue and stretching data
It can determine the specific value of ω and C.After parameter value determines, yield strength and the tension that need to only measure the series any materials are strong
Degree, can substitute into above-mentioned formula and acquire corresponding fatigue strength values, be achieved in efficient prediction.
The method of the present invention the principles of science is as follows:
The fatigue strength " lever law " used in this method is the model based on fatigue damage basic principle, the mould
Type integrates several big influence factors of fatigue strength, is embodied in the following aspects:
Firstly, fatigue damage substantially derives from irreversible plastic deformation of material during cyclic deformation, therefore draw
The yield strength σ that can embody plastic deformation complexity is enteredy, yield strength is bigger, is more conducive to material and is integrally plastically deformed
The control of amount, to be conducive to fatigue strength raising.
Second, although damage is from plastic deformation, under the load-up condition close to fatigue strength, material is often located
In the state of integral, flexible deformation local plastic deformation, this relates to elasticity between material each section --- and plastic deformation is matched
Problem, therefore the parameter C of reflection elastic deformation characteristic is introduced, the parameter is directly related with elasticity modulus of materials, and modulus is bigger, C
Value is bigger, and integral, flexible deformation quantity is smaller under the conditions of representing same load, and corresponding topical amount of plastic deformation is also smaller, is conducive to tired
Labor intensity improves.
The matching of third, integral, flexible and local plastic produces fatigue damage localization problem, and damage is more concentrated, material
It is easier in shorter circulation cycle crack initiation, this pole for the crack initiation stage occupies the high cycle fatigue in most service life
It is unfavorable.Therefore, the ability of material itself resistance local plastic deformation is most important to fatigue strength.Based on the above fact, mould
Type introduces the yield tensile ratio σ that can embody material work hardening capacityy/σbThis index, yield tensile ratio is smaller, material processing hardening energy
Power is better, and the ability of strain resistant localization is stronger, is more conducive to fatigue strength raising.
4th, for fatigue damage Localization Problems, other than homogeneous deformation ability above-mentioned, also with material itself
Uniformity coefficient it is closely related.In Practical Project material often exist as locally grow up crystal grain, the second coarse phase, be mingled with
The defects of object, loose hole, their presence directly affect the distribution of fatigue damage, or even can change tired crack initiation behavior.
Parameter ω is the concentrated reflection of defect this factor to Fatigue Strength Effect, defect bring localized failure journey in a model
Degree is higher, and ω value is bigger, is more unfavorable for the raising of fatigue strength.
Above four aspects represent the key factor for influencing Metal Material Fatigue intensity；If only considering front two o'clock,
Pattern function form withFormula is similar, therefore the model is considered as pairThe development and perfection of formula.This
Outside, which embodies the influence to fatigue behaviour such as elastic properties of materials, plasticity, hardening capacity, tissue defects comprehensively, enumerates system
The about key index of fatigue strength has embodied a concentrated reflection of the essence of fatigue damage, it is sufficient to as the theoretical basis of this patent, realize tired
The efficient prediction of labor intensity.
The technology of the present invention effect one: the Fatigue Strength Prediction under different fatigue intensity-tensile strength relationship.Data statistic
It is bright, approximately linear (Fig. 3 a) or non-linear (figure may be presented under different conditions, between fatigue of materials intensity and tensile strength
3c, e) relationship, andFormula is only effective to linear relationship.The model that this patent uses is strong to various types of fatigues
Degree --- tensile strength relationship is applicable, is embodied in σw/σy--σy/σbGood linear relationship under coordinate system (Fig. 3 b,
d,f).It can be seen that the scope of application of this method is far beyond conventional method.
The technology of the present invention effect two: the Fatigue Strength Prediction of material under heterogeneity and technique.By to typical project material
Material stretches the finishing analysis with fatigue data it is found that this method is suitable for multiple material (including but not limited to steel, copper alloy, aluminium
Alloy, magnesium alloy) and technology type (various predeformation and heat treatment process).With the variation of material and technology, parameter ω and C is taken
Value is varied, but data are in σw/σy--σy/σbGood linear relationship is showed under coordinate system, show with model coincide compared with
Good (Fig. 4).
The technology of the present invention effect three: the Fatigue Strength Prediction of material under different loading environments.In addition to material oneself state
The adaptation of variation, this method can also cope with the variation of external condition well.Such as Fig. 5, with loading method, cyclic loading ratio
The variation of R and circulation cycle, parameter ω and C value is varied, but σw/σy--σy/σbRelationship remains linear.As it can be seen that making
It can get the fatigue strength values under a variety of external conditions with this method.
The technology of the present invention effect four: the high efficiency and accuracy of Fatigue Strength Prediction.The model form that this patent is related to
Simply, prediction technique is fast practical, it is only necessary to which the prediction of fatigue strength can be realized with a small amount of testing fatigue for extension test, have low
Cost, efficient outstanding advantage.In addition, being counted through mass data, the Fatigue Strength Prediction value and experiment obtained by this method
It is higher to be worth degree of agreement, calculating error mostly within 10% (Fig. 6) embodies the accuracy of this method to a certain extent and reliable
Property.
To sum up, this method has both universality, practicability and reliability, has wide range of applications, and operation is simple and feasible, can protect
Greatly reduce necessary testing fatigue under the premise of card forecasting accuracy, is a kind of efficient Fatigue Strength Prediction method.
Embodiment 1:
The present embodiment is aluminum alloy fatigue prediction of strength, and detailed process is as follows:
(1) material:
5052 aluminium alloys, different predeformation and condition of heat treatment (O, H32, H34, H36, H38).
(2) process:
Step 1: tensile property test.The unified processing of above-mentioned material is stretched into sample, is drawn under same experimental conditions
Performance test is stretched, yield strength σ is obtainedyWith tensile strength sigmabValue (specific data are shown in Table 1).
Step 2: fatigue test specimen selection.In order to reduce fatigue to the greatest extent while guaranteeing prediction result accuracy as far as possible
Test volume should select the biggish 2-4 kind material of tensile property difference to carry out fatigue property test.Due to the material for including in this example
State is less, therefore only selects 2 kinds of testing of materials fatigue strength, is respectively as follows: 5052-O, 5052-H36.
Step 3: fatigue property test.Fatigue samples are processed with the material selected, sample surfaces must carry out at unified polishing
Reason, guarantees the consistency of surface state.Then it selects required loading environment uniformly to carry out fatigue property test, it is strong to obtain fatigue
Spend σwMeasured value (specific data are shown in Table 1).
Step 4: parameter fitting.As shown in Fig. 7 (a) solid dot, using the stretching and fatigue data measured, 5052- is acquired
The σ of O, 5052-H36 materialy/σbWith σw/σyValue is plotted in σ respectively as horizontal, ordinatew/σy--σy/σbIn relational graph, and lead to
It crosses linear fit and acquires parameter ω and C, wherein ω is the negative inverse of fitting a straight line slope, and C is fitting a straight line and σy/σbAxis is cut
Away from (such as Fig. 2).Specific data are referring to table 1.
Step 5: Fatigue Strength Prediction.Such as Fig. 7 (a) hollow dots, pass through material to be predicted (5052-H32, H34, H38)
Tensile property can determine abscissa positions (σy/σb), ordinate position (σ can be further determined that by extending to fitting a straight linew/σy), from
And acquire the fatigue strength σ of respective materialwPredicted value.It can also be by by tensile property σy、σbPublic affairs are directly substituted into parameter value ω, C
FormulaMethod acquire fatigue strength σwPredicted value (specific data are shown in Table 1).
Step 6: forecasting accuracy assessment.Such as Fig. 7 (a) semi-hollow point, it is practical that 5052-H32, H34, H38 material can be substituted into
The fatigue strength values measured are compared with predicted value, predict order of accuarcy such as Fig. 7 (b), deviation see Table 1 for details (note: this step
Belong to the verifying to this method, can be omitted in actual mechanical process).
1 5052 aluminum alloy fatigue prediction of strength related data summary sheet of table
Embodiment 2:
The present embodiment is TWIP steel Fatigue Strength Prediction, and detailed process is as follows:
(1) material:
Fe-30Mn-0.9C TWIP steel, different pre-tension deformation states (original state, pre-stretching 30%, 60%, 70%).
(2) process:
Step 1: tensile property test.The unified processing of above-mentioned material is stretched into sample, is drawn under same experimental conditions
Performance test is stretched, yield strength σ is obtainedyWith tensile strength sigmabValue (specific data are shown in Table 2).
Step 2: fatigue test specimen selection.In order to reduce fatigue to the greatest extent while guaranteeing prediction result accuracy as far as possible
Test volume should select the biggish 2-4 kind material of tensile property difference to carry out fatigue property test.Due to the material for including in this example
State is less, therefore only selects 2 kinds of testing of materials fatigue strength, is respectively as follows: the original state of Fe-30Mn-0.9C (0%) and pre-stretching
70%.
Step 3: fatigue property test.Fatigue samples are processed with the material selected, sample surfaces must carry out at unified polishing
Reason, guarantees the consistency of surface state.Then it selects required loading environment uniformly to carry out fatigue property test, it is strong to obtain fatigue
Spend σwMeasured value (specific data are shown in Table 2).
Step 4: parameter fitting.As shown in Fig. 8 (a) solid dot, using the stretching and fatigue data measured, Fe- is acquired
The σ of 30Mn-0.9C-0%, 70% materialy/σbWith σw/σyValue is plotted in σ respectively as horizontal, ordinatew/σy--σy/σbRelational graph
In, and parameter ω and C are acquired by linear fit, wherein ω is the negative inverse of fitting a straight line slope, and C is fitting a straight line and σy/σb
The intercept (such as Fig. 2) of axis.Specific data are referring to table 2.
Step 5: Fatigue Strength Prediction.Such as Fig. 8 (a) hollow dots, by material to be predicted (Fe-30Mn-0.9C-30%,
60%) tensile property can determine abscissa positions (σy/σb), ordinate position can be further determined that by extending to fitting a straight line
(σw/σy), to acquire the fatigue strength σ of respective materialwPredicted value.It can also be by by tensile property σy、σbWith parameter value ω, C
It is directly substituted into formulaMethod acquire fatigue strength σwPredicted value (specific data are shown in Table 2).
Step 6: forecasting accuracy assessment.Such as Fig. 8 (a) semi-hollow point, Fe-30Mn-0.9C-30%, 60% material can be substituted into
Expect that actually measured fatigue strength values are compared with predicted value, predicts order of accuarcy such as Fig. 8 (b), see Table 2 for details for deviation (note:
This step belongs to the verifying to this method, can be omitted in actual mechanical process).
2 Fe-30Mn-0.9C TWIP steel Fatigue Strength Prediction related data summary sheet of table
Claims (6)
1. a kind of prediction technique of Metal Material Fatigue intensity, it is characterised in that: this method comprises the following steps:
(1) it selects several homologous series metal materials to carry out tensile property test, obtains several groups material yield strength σyIt is strong with tension
Spend σbValue；
(2) fatigue property test:
It selects 2-4 kind material to prepare fatigue test specimen in homologous series metal material, fatigue strength test is carried out to it, obtain
The fatigue strength σ of materialwMeasured value；
(3) parameter fitting:
Using the tensile property data and fatigue strength data measured, the σ of material is acquiredy/σbWith σw/σyValue, then with σy/σbValue
For abscissa, with σw/σyValue is that ordinate draws σw/σy--σy/σbRelational graph, and parameter ω and C are acquired by linear fit,
Middle ω is the negative inverse of fitting a straight line slope, and C is fitting a straight line and σy/σbThe intercept of axis；
(4) Fatigue Strength Prediction:
The σ of material is determined by the tensile property of material to be predictedy/σbValue, i.e. σw/σy--σy/σbAbscissa positions in relational graph,
The σ of material can be further determined that by the straight line that step (3) is fittedw/σyValue, i.e. ordinate position, to acquire respective material
Fatigue strength σwPredicted value；Alternatively, by the tensile property σ of material to be predictedy、σbFormula is directly substituted into parameter value ω, C
(1), it is computed the fatigue strength σ for acquiring respective materialwPredicted value；
2. the prediction technique of Metal Material Fatigue intensity according to claim 1, it is characterised in that: selected in step (1)
Homologous series metal material refers to the several material that same metal material obtains after different predeformation techniques or heat treatment.
3. the prediction technique of Metal Material Fatigue intensity according to claim 1, it is characterised in that:, will be same in step (1)
After the unified processing of series metal material stretches sample, tensile property test is carried out under same experimental conditions.
4. the prediction technique of Metal Material Fatigue intensity according to claim 1, it is characterised in that: in step (2), in order to
Guarantee prediction result accuracy and reduce testing fatigue amount, the biggish 2-4 kind material of tensile property difference should be selected to carry out tired
Labor performance test.
5. the prediction technique of Metal Material Fatigue intensity according to claim 1, it is characterised in that: in step (2), with choosing
Material out processes fatigue samples, and sample surfaces must carry out unified polishing treatment, guarantee the consistency of surface state；Then it selects
Required loading environment uniformly carries out fatigue property test.
6. the prediction technique of Metal Material Fatigue intensity according to claim 1, it is characterised in that: this method is suitable for
Steel, copper alloy, aluminium alloy or magnesium alloy；Suitable for various predeformation and heat treatment process；Being applicable in loading environment is tension and compression, bending
Loading method and different cyclic loadings ratio and circulation cycle.
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