CN113392504B - Method for predicting influence of defects on high-cycle and ultra-high-cycle fatigue strength - Google Patents
Method for predicting influence of defects on high-cycle and ultra-high-cycle fatigue strength Download PDFInfo
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- 230000007547 defect Effects 0.000 title claims abstract description 163
- 238000000034 method Methods 0.000 title claims abstract description 35
- 230000000694 effects Effects 0.000 claims abstract description 22
- 239000000463 material Substances 0.000 claims abstract description 18
- 238000009661 fatigue test Methods 0.000 claims description 23
- 238000005452 bending Methods 0.000 claims description 8
- 230000000376 effect on fatigue Effects 0.000 claims description 6
- 238000010348 incorporation Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 5
- 238000000691 measurement method Methods 0.000 claims description 5
- 238000002360 preparation method Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000013001 point bending Methods 0.000 claims description 2
- 238000011156 evaluation Methods 0.000 abstract description 4
- 238000013178 mathematical model Methods 0.000 abstract description 4
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- 229910001069 Ti alloy Inorganic materials 0.000 description 8
- 238000012360 testing method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 229910000831 Steel Inorganic materials 0.000 description 2
- 238000003801 milling Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000010959 steel Substances 0.000 description 2
- 230000003872 anastomosis Effects 0.000 description 1
- 238000010892 electric spark Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000007373 indentation Methods 0.000 description 1
- 230000000977 initiatory effect Effects 0.000 description 1
- 238000004626 scanning electron microscopy Methods 0.000 description 1
- 230000003442 weekly effect Effects 0.000 description 1
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- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/04—Ageing analysis or optimisation against ageing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract
The invention provides a method for predicting the influence of defects on high-cycle and ultra-high-cycle fatigue strength. By using this relationship, the effect of the defect on the fatigue strength can be characterized by the size of the defect, and thus the effect of the defect on the fatigue strength can be predicted. The method disclosed by the invention is simple in form and convenient to apply, solves the problems of mathematical model description and difficult accurate evaluation of the influence of defects on high-cycle and ultra-high-cycle fatigue strength, and provides model and technical support for the research and evaluation of fatigue performance of materials or engineering parts containing defects.
Description
Technical Field
The invention relates to a method for predicting high-cycle and ultra-high-cycle fatigue strength of a material or an engineering part, in particular to a method for predicting the influence of defects on the high-cycle and ultra-high-cycle fatigue strength.
Background
Actual engineering components often inevitably suffer from various types of defects, such as metallurgical defects during material preparation, possible impact defects during component service, and the like. Under the action of an external load, local stress concentration at the defect often causes the initiation of fatigue cracks, and the fatigue resistance of the material is obviously reduced. Therefore, the method for establishing the influence of the defects on the fatigue strength has important scientific significance and engineering application value.
Disclosure of Invention
The invention aims to provide a method for predicting the influence of defects on high-cycle and ultra-high-cycle fatigue strength of materials or engineering parts.
The technical content of the invention is as follows:
a method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength comprising the steps of:
(1) Fatigue test is performed on the smooth sample for prediction and the sample containing defects to obtain the fatigue strength of the smooth sample for prediction under a certain life, and the fatigue strength sigma of the sample containing defects w,1 ，σ w,2 ，…，σ w,n And corresponding defect sizesWherein area is i (i=1, 2.,. N) is the projected area of defect i perpendicular to the primary stress axis;
(2) The fatigue strength and defect size at this lifetime are assumed to satisfy the following relationship:
i.e.
Wherein sigma w Representing fatigue strength, sigma w,0 Indicating the fatigue strength of a smooth sample;representing the defect size, area is the projected area of the defect perpendicular to the principal stress axis; />Is critical defect size, less than this size, the defect has no effect on fatigue strength; m and C are parameters related to material, fatigue life and defect incorporation form;
(3) Substituting the obtained material parameters m and C into the formula (2) to obtain an influence model of the defect on the fatigue strength under the service life.
Further, the fatigue test comprises an axial stress fatigue test, a rotation bending fatigue test, a four-point bending fatigue test and an ultrasonic frequency fatigue test.
Further, the defect size is obtained by a method of preparing defects.
It is also possible that the defect size is determined by measurement.
Further, the measurement method is determined by measuring the size of the defect on the fatigue fracture scanning electron microscope picture, and preferably, the measurement method is determined by measuring the size of the defect on the fatigue fracture scanning electron microscope picture through image processing software.
Further, the defect size is less than or equal to 1000 μm.
Further, m is obtained by adopting a least square method on the fatigue strength and the defect size of the defect sample lower than the fatigue strength of the smooth sample; preferably, the calculating method of m is as follows:
further, C is obtained by adopting a least square method on the fatigue strength and the defect size of the defect sample lower than the fatigue strength of the smooth sample; preferably, the calculation method of C is as follows:
the method disclosed by the invention determines the high-cycle and ultra-high-cycle fatigue strength of a smooth sample and a sample containing defects under a certain service life through a fatigue experiment, and then determines the influence relationship of the defects on the fatigue strength under the service life through a mathematical model. By using this relationship, the effect of the defect on the fatigue strength can be characterized by the size of the defect, and thus the effect of the defect on the fatigue strength can be predicted. The method disclosed by the invention is simple in form and convenient to apply, solves the problems of mathematical model description and difficult accurate evaluation of the influence of defects on high-cycle and ultra-high-cycle fatigue strength, and provides model and technical support for the research and evaluation of fatigue performance of materials or engineering parts containing defects.
Drawings
Fig. 1: TC17 titanium alloy rotary bending fatigue test sample (unit: mm) smooth test sample;
fig. 2: a TC17 titanium alloy rotating bending fatigue test sample (unit: mm) contains a defect A test sample defect schematic diagram;
fig. 3: a defect schematic diagram of a TC17 titanium alloy rotating bending fatigue test sample (unit: mm) containing a defect B test sample;
fig. 4: a defect schematic diagram of a TC17 titanium alloy rotating bending fatigue test sample (unit: mm) containing a defect C test sample;
fig. 5: a defect schematic diagram of a TC17 titanium alloy rotating bending fatigue test sample (unit: mm) containing a defect D test sample;
fig. 6: TC17 titanium alloy smooth sample and defect-containing sample S-N data;
fig. 7: influence model results of defects on the ultra-high cycle fatigue strength of the TC17 titanium alloy;
fig. 8: effect of defects on EA4T axle steel fatigue limit in literature model results.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
Example 1:
first, a rotational bending fatigue test (stress ratio r= -1) was performed under different stress amplitudes on the smooth sample and the defect-containing sample of the titanium alloy shown in fig. 1 to 5, and fatigue performance data thereof were obtained as shown in fig. 6. The defects in fig. 2-4 were drilled using a micro milling machine at the smallest cross-section of the smooth specimen shown in fig. 1, and the corresponding defect sizes were the average of the sizes obtained by fatigue fracture scanning electron microscopy pictures. In defect pair 10 8 The effect of fatigue strength at round is exemplified, and based on the experimental results in FIG. 6, 10 is obtained 8 Fatigue strength 635MPa of smooth sample at round and fatigue strength sigma of sample containing defect B w,1 ＝563MPaFatigue strength sigma of C specimen containing defect w,2 ＝448MPa/> Fatigue strength sigma of defect-containing D specimen w,3 ＝390MPa/>Here, 10 8 Fatigue strength at week was taken as 10 in the experimental data tested 8 Stress amplitude minimum and experience 10 for samples subjected to fatigue failure before weekly times 8 Average of stress amplitude maxima of samples that did not fail in fatigue after the week.
Then, the above-mentioned defects B, C and D were sampled at 10 8 The fatigue strength and the corresponding defect size under the cycle are substituted into the formula (2), and parameters m and C are obtained through a least square method.
And finally, substituting parameters m and C into the formula (2) to obtain an influence model result of the defect on the fatigue strength under the service life. FIG. 7 shows a defect pair 10 8 Effect of fatigue strength on cycle model results and fatigue strength of 620MPa with the sample containing defect AThe anastomosis is very good. Fig. 7 shows that the model is well able to correlate and predict the effect of defects on fatigue strength.
Example 2:
FIG. 8 shows the results of a model of the effect of a defect on the Fatigue limit (expressed in stress amplitude) of EA4T axle steel in the document [ Zhang et al, int J Fatigue 2020,132:105379 ]. It can be seen that the model results agree well with the experimental results.
Example 3: a method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength comprising the steps of:
(1) Performing a fatigue test on the smooth sample for prediction and the sample containing the defect to obtain the fatigue strength of the smooth sample for prediction under a certain service life and the fatigue strength of the sample containing the defect;
(2) Determining the influence relation of the defect on the fatigue strength under the service life through a mathematical model;
(3) By using the relation, the influence of the defect on the fatigue strength is characterized by the size of the defect, and further, the influence of the defect on the fatigue strength is predicted.
Example 4:
a method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength comprising the steps of:
(1) Fatigue test is performed on the smooth sample for prediction and the sample containing defects to obtain the fatigue strength of the smooth sample for prediction under a certain life, and the fatigue strength sigma of the sample containing defects w,1 ，σ w,2 ，…，σ w,n And corresponding defect sizesWherein area is i (i=1, 2.,. N) is the projected area of defect i perpendicular to the primary stress axis;
(2) The fatigue strength and defect size at this lifetime are assumed to satisfy the following relationship:
i.e.
Wherein sigma w Representing fatigue strength, sigma w,0 Indicating the fatigue strength of a smooth sample;representing the defect size, area is the projected area of the defect perpendicular to the principal stress axis; />Is critical defect size, less than this size, the defect has no effect on fatigue strength; m and C are parameters related to material, fatigue life and defect incorporation form;
(3) Substituting the obtained material parameters m and C into the formula (2) to obtain an influence model of the defect on the fatigue strength under the service life.
Example 5:
a method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength comprising the steps of:
(1) Fatigue test is performed on the smooth sample for prediction and the sample containing defects to obtain the fatigue strength of the smooth sample for prediction under a certain life, and the fatigue strength sigma of the sample containing defects w,1 ，σ w,2 ，…，σ w,n And corresponding defect sizesWherein area is i (i=1, 2.,. N) is the projected area of defect i perpendicular to the primary stress axis;
(2) The fatigue strength and defect size at this lifetime are assumed to satisfy the following relationship:
i.e.
Wherein sigma w Representing fatigue strength, sigma w,0 Indicating the fatigue strength of a smooth sample;representing the defect size, area is the projected area of the defect perpendicular to the principal stress axis; />Is critical defect size, less than this size, the defect has no effect on fatigue strength; m and C are parameters related to material, fatigue life and defect incorporation form;
(3) Substituting the obtained material parameters m and C into the formula (2) to obtain an influence model of the defect on the fatigue strength under the service life;
the defect size is obtained by a defect preparation method, wherein the preparation method comprises the prior art of micro milling machine, electric spark, indentation and the like.
Example 6:
a method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength comprising the steps of:
(1) Fatigue test is performed on the smooth sample for prediction and the sample containing defects to obtain the fatigue strength of the smooth sample for prediction under a certain life, and the fatigue strength sigma of the sample containing defects w,1 ，σ w,2 ，…，σ w,n And corresponding defect sizesWherein area is i (i=1, 2.,. N) is the projected area of defect i perpendicular to the primary stress axis;
(2) The fatigue strength and defect size at this lifetime are assumed to satisfy the following relationship:
i.e.
Wherein sigma w Representing fatigue strength, sigma w,0 Indicating the fatigue strength of a smooth sample;representing the defect size, area is the projected area of the defect perpendicular to the principal stress axis; />Is critical defect size, less than this size, the defect has no effect on fatigue strength; m and C are parameters related to material, fatigue life and defect incorporation form;
(3) Substituting the obtained material parameters m and C into the formula (2) to obtain an influence model of the defect on the fatigue strength under the service life;
the defect size is determined by measurement; the measurement method is to measure the size of the defect on the fatigue fracture scanning electron microscope picture; the measurement of the defect size on the fatigue fracture scanning electron microscope picture is determined by Image processing software (such as Image-Pro Plus software).
Example 7:
a method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength comprising the steps of:
(1) Fatigue test is performed on the smooth sample for prediction and the sample containing defects to obtain the fatigue strength of the smooth sample for prediction under a certain life, and the fatigue strength sigma of the sample containing defects w,1 ，σ w,2 ，…，σ w,n And corresponding defect sizesWherein area is i (i=1, 2.,. N) is the projected area of defect i perpendicular to the primary stress axis;
(2) The fatigue strength and defect size at this lifetime are assumed to satisfy the following relationship:
i.e.
Wherein sigma w Representing fatigue strength, sigma w,0 Indicating the fatigue strength of a smooth sample;representing the defect size, area is the projected area of the defect perpendicular to the principal stress axis; />Is critical defect size, less than this size, the defect has no effect on fatigue strength; m and C are parameters related to material, fatigue life and defect incorporation form;
(3) Substituting the obtained material parameters m and C into the formula (2) to obtain an influence model of the defect on the fatigue strength under the service life;
the defect size is determined by measurement; the measurement method is to measure the size of the defect on the fatigue fracture scanning electron microscope picture;
m is obtained by adopting a least square method on the fatigue strength and the defect size of the defect sample lower than the fatigue strength of the smooth sample; preferably, the calculating method of m is as follows:
c, obtaining the fatigue strength and the defect size of the defect sample lower than the fatigue strength of the smooth sample by adopting a least square method; preferably, the calculation method of C is as follows:
by now it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been shown and described herein in detail, many other variations or modifications of the invention consistent with the principles of the invention may be directly ascertained or inferred from the present disclosure without departing from the spirit and scope of the invention. Accordingly, the scope of the present invention should be understood and deemed to cover all such other variations or modifications.
Claims (7)
1. A method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength comprising the steps of:
(1) Fatigue test is performed on the smooth sample for prediction and the sample containing defects to obtain the fatigue strength of the smooth sample for prediction under a certain life, and the fatigue strength sigma of the sample containing defects w,1 ，σ w,2 ，…，σ w,n And corresponding defect sizesWherein area is i I=1, 2..n, is the projected area of defect i perpendicular to the principal stress axis;
(2) The fatigue strength and defect size at this lifetime satisfy the following relationship:
i.e.
Wherein sigma w Representing fatigue strength, sigma w,0 Indicating the fatigue strength of a smooth sample;representing the defect size, area is the projected area of the defect perpendicular to the principal stress axis; />Is critical defect size, less than this size, the defect has no effect on fatigue strength; m and C are parameters related to material, fatigue life and defect incorporation form; m is obtained by adopting a least square method on the fatigue strength and the defect size of the defect sample lower than the fatigue strength of the smooth sample; the calculating method of m is as follows: the method comprises the steps of carrying out a first treatment on the surface of the
C, obtaining the fatigue strength and the defect size of the defect sample lower than the fatigue strength of the smooth sample by adopting a least square method; the calculation method of C is as follows:
(3) Substituting the obtained material parameters m and C into the formula (2) to obtain an influence model of the defect on the fatigue strength under the service life.
2. The method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength of claim 1, wherein: the fatigue test comprises an axial stress fatigue test, a rotary bending fatigue test, a four-point bending fatigue test and an ultrasonic frequency fatigue test.
3. The method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength of claim 1, wherein: the defect size is obtained by the preparation method of the defect.
4. The method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength of claim 1, wherein: the defect size is determined by measurement.
5. The method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength of claim 4, wherein: the measurement method is used for determining the size of the defect on the fatigue fracture scanning electron microscope picture.
6. The method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength of claim 5, wherein: and determining the size of the defect on the fatigue fracture scanning electron microscope picture through image processing software.
7. The method of predicting the effect of defects on high cycle and ultra-high cycle fatigue strength of claim 1, wherein: the defect size is less than or equal to 1000 mu m.
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