CN107563054B - A kind of turbine disk life expectance analysis method of the Weakest-Link methods based on SWT parameters - Google Patents
A kind of turbine disk life expectance analysis method of the Weakest-Link methods based on SWT parameters Download PDFInfo
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Abstract
The turbine disk life expectance analysis method for the Weakest Link methods based on SWT parameters that the invention discloses a kind of, step：(1) smooth pole sample and different dimension scale center hole plane plate specimens are separately designed, the low-cycle fatigue experiment of turbine disk sample coupon is carried out；(2) it is analyzed by fatigue life Weibull estimation of distribution parameters value and obtains service life profile exponent bN；(3) tri- parameter Power Functions life models of SWT are established, analyze to obtain index coefficient m by least square regression；(4) impairment parameter profile exponent b is calculatedW；(5) effective impairment parameter is calculated(6) feature fatigue life is calculated(7) fatigue life Weibull distribution function formula is obtained；(8) as reliability PsOr failure probability acquires prediction median life N when taking 0.5p；As reliability PsWhen taking 0.9987 and 0.0013 respectively, life expectance analysis result is obtained.This method considers geometric dimension effect and statistics dimensional effect simultaneously, realizes certainty life prediction, and provide life expectance result.
Description
Technical field
The present invention relates to a kind of turbine disk life expectance analysis method of the Weakest-Link methods based on SWT parameters,
Belong to aerospace technical field of engines.
Background technology
Aero-engine is a kind of limit product, is operated under the complex load/environment of high temperature, high pressure, high rotating speed etc.；Hair
The raising of motivation performance and safety indexes, it is desirable that engine weight is light, the long-life, (e.g., safe flight is to starting for high reliability
Machine structural member then requires low failure probability, up to 10-5-10-7Secondary/pilot time).Aero-engine turbine disk subjects more
Come higher temperature and mechanical load, key component and limit longevity part as engine, it is desirable that the turbine disk has higher reliability
And economy.Therefore, it is that engine improving performance and guarantee are pacified for turbine disk development accurate reliability of service life assessment comprehensively
Full necessary means.The reliability of service life assessment of the turbine disk often uses more traditional " hot spot method " (Hot Spot at present
Method), also known as " dangerous point method ", method is using structural danger point as research object, using the life level of dangerous point as knot
The life appraisal result of structure entirety.Often there is bolt hole, venthole, labyrinth seal etc. in practical wheeling disk structure and is also easy to produce stress
The geometric properties of concentration use hot spot method to carry out the influence that assessment has ignored stress gradient to fatigue life in this case,
It often provides overly conservative as a result, be easy to causeing structural redundancy, is unfavorable for the performance of abundant mining structure.
Traditional hot spot method is often based upon standard sample fatigue data and carries out reliability of service life assessment to structure, and real
Often there is larger difference in border structure and the volume of standard sample, such as the turbine disk of large-bypass-ratio engine, volume are much larger than
Standard sample.Volume is bigger, and the probability comprising fault in material is higher, and under same load level, fault in material germinating is the general of crackle
Rate is also higher, and the service life is lower.Therefore, hot spot method has ignored between sample and practical wheeling disk structure volume difference to fatigue life
It influences, being perfectly safe for the turbine disk can not be completely secured.
Invention content
The technical problem to be solved in the present invention is：It overcomes the deficiencies of the prior art and provide a kind of more fully and accurate
Turbine disk life expectance analysis method quantifies turbine disk global failure risk.
The present invention solve the technical solution that uses of above-mentioned technical problem for：A kind of Weakest-Link based on SWT parameters
The turbine disk life expectance analysis method of method includes mainly：The experiment of sample low circulation, material parameter obtain, dimensional effect is divided
Analysis, life expectance analysis.Weskest-Link method explicit physical meanings based on SWT parameters, can consider dimensioning simultaneously
Very little effect and statistics dimensional effect, and provide life expectance result.
Realize that steps are as follows：
Step (1) turbine disk sample coupon fatigue test：Smooth pole sample and stress concentration position are designed for the turbine disk
Structural simulation part is to investigate geometric dimension effect.The experiment of pole low-cycle fatigue is sampled and carried out from disk base, obtains material
Low-circulation fatigue performance；By carrying out different dimension scale center hole treadmill tests, to wheel disc stress concentration position low circulation
Fatigue life carries out test assessment, investigates statistics dimensional effect.
Step (2) passes through fatigue life to smooth pole test data and center hole plane plate specimen test data
Weibull estimation of distribution parameters values are analyzed, and are obtained Reliability Function based on Weakest-Link methods, are obtained service life profile exponent
bN；
Step (3) establishes tri- parameter Power Functions life models of SWT based on smooth pole test data, is returned by least square
Analysis is returned to obtain the index coefficient m in tri- parameter Power Functions life models of SWT；
Step (4) impairment parameter profile exponent bWAccording to the sample service life profile exponent b obtained in step (2)NAnd step
(3) index coefficient m is determined jointly in the tri- parameter Power Functions life models of SWT obtained in；
Step (5) combines the impairment parameter that center hole plane plate specimen Finite element analysis results data and step (4) obtain
Profile exponent bWEffective impairment parameter is calculated
Step (6) is according to effective impairment parameter of step (5)The tri- parameter Power Functions service life of SWT established with step (3)
Feature fatigue life is calculated in model
The feature fatigue life that step (7) is calculated according to step (6)The service life profile exponent b calculated with step (2)N,
Obtain the fatigue life Weibull distribution function formula of center hole plane plate specimen；
The fatigue life Weibull distribution function formula that step (8) is obtained according to step (7), as reliability PsOr failure is general
When rate takes 0.5, the prediction median life N of center hole plane plate specimen is acquiredp.As reliability Ps0.9987 and 0.0013 are taken respectively
When, obtain ± 3 σ life curves of center hole plane plate specimen.
In the step (2), the analysis of Weibull estimation of distribution parameters values is carried out for sample data, is based on Weakest-
Link methods are derived by Reliability Function：
Wherein, NfFor Life Cycle number,It is characterized fatigue life.Natural logrithm twice is taken to Reliability Function formula, is led to
It crosses Least Square Regression Analysis and obtains the estimated value of parameter：
Wherein, x=lnNf, y=ln [ln1/1-Pf(Nf)].Same material service life under the conditions of mutually synthermal, different loads
Profile exponent bNApproximation obeys standardized normal distribution, and the service life obtained under the conditions of each load level of different type sample distribution is referred to
Several mean values are as bNValue.
In the step (3), SWT parameters are introduced based on smooth pole test data, establish three parameter Power Functions certainty
Life model:
Nf△Wm=Nf(△WSWT-△W0)m=c
Wherein, c, m, Δ W0Three parameters are parameter related with material, pass through minimum two based on step (1) test data
Multiply regression analysis to be fitted to obtain；Δ W is impairment parameter, Δ W=Δs WSWT-ΔW0, Δ WSWT=Δ εtσmax, Δ εtFor overall strain model
It encloses, σmaxFor maximum stress.
In the step (4), impairment parameter profile exponent b is calculatedWWhen, using following methods：
In the step (5), effective impairment parameter is calculatedWhen, using following methods：
Wherein, reference volume V0 is that the examination segment body of sample accumulates；△ W are impairment parameter, are determined by step (3)；bWFor damage
Hinder parameter distribution index, is determined by step (4).
In the step (6), feature fatigue life is calculatedUsing following methods：
Wherein,For effective impairment parameter, it is calculated by step (5)；M, c is SWT tri- parameter Power Functions service life moulds
Material parameter in type is determined by step (3).
In the step (7), the fatigue life Weibull distribution function formula of foundation is：
Wherein,It is characterized fatigue life, is calculated according to step (6)；bNFor service life profile exponent, by step (2)
It determines.
The advantages of the present invention over the prior art are that：
A kind of turbine disk life expectance analysis method of the Weakest-Link methods based on SWT parameters of the present invention and tradition
Method is compared, and SWT parameters is introduced Weskest-Link methods so that be mainly used for fatigue limit and stress fatigue durability analysis
Weakest-Link methods be able to extend to low-cycle fatigue range；It is realized using the test data of smooth pole sample to lacking
The high-precision life prediction of oral examination sample；Smooth pole sample and 100% dimension scale center hole plane plate specimen number are used respectively
Realize that certainty life prediction and life expectance are analyzed according to a series of different dimension scale center hole plane plate specimens, Neng Goutong
When consider geometric dimension effect and statistics dimensional effect, provide life expectance as a result, with test value comparison have it is very high pre-
Survey precision.
Description of the drawings
Fig. 1 is the Weakest-Link method life prediction flows based on SWT parameters of the present invention；
Circular hole plane plate specimen SWT parameter Weakest-Link methods consider geometric dimension life prediction result centered on Fig. 2.
Circular hole plane plate specimen SWT parameter Weakest-Link methods consider statistics size life prediction result centered on Fig. 3.
Specific implementation mode
Related notion involved in the present invention is explained：
SWT parameters：When carrying out fatigue test, the life dispersivity of different loads level often has differences, load level
Lower, life dispersivity is higher.This rule is adequately described, randomization, SWT probability longevity are carried out to stress-life model
It is one such to order model.The parameter of material damage and fatigue life relationship described in SWT models, such as maximum stress σmax, answer
Luffing △ εt/ 2 equal as SWT parameters.
Critical defective density：In stress ratio R, fatigue life NfUnder conditions of, make fatigue of materials intensity σALess than or equal to stress
Amplitude σaMaterial unit volume in defects count.
Weakest-Link methods：Abundant small volume units Δ V is multiplied to obtain failure probability with critical defective density, accordingly
Survival probability or the sum of reliability and failure probability be 1, the uniform stressed material of an arbitrary volume is only each at its
A volume subelement can survive when all surviving, and the reliability of whole volume is equal to the probability of whole volume subelement survivals.
Below in conjunction with the accompanying drawings, to the present invention is based on the turbine disk life expectances of the Weakest-Link methods of SWT parameters point
The technical solution of analysis method is described further.
Geometric dimension effect and statistics dimensional effect are considered, in conjunction in the experiment of pole low-cycle fatigue and different dimension scales
Heart circular hole treadmill test data, a kind of turbine disk probability longevity for Weakest-Link methods based on SWT parameters that the present invention carries
Analysis method is ordered, flow is shown in Fig. 1.It is as follows：
Step (1) turbine disk sample coupon fatigue test：For turbine disk different parts material property and local geometric features
It separately designs structural simulation part and disk base sampling plan and carries out experiment.It is sampled from disk base and to carry out smooth pole low circulation tired
Labor is tested, and the low-circulation fatigue performance of material is obtained；By carrying out a series of different sizes such as 100%, 80%, 60%, 40%
Ratio center hole treadmill test obtains turbine disk stress concentration position low cycle fatigue life and assesses data.
Step (2) passes through fatigue for the smooth pole test data of step (1) and center hole plane plate specimen test data
Service life Weibull estimation of distribution parameters value is analyzed, to obtain FATIGUE LIFE DISTRIBUTION index bN。
The two-parameter distribution of fatigue life Follow Weibull is derived by Reliability Function based on Weakest-Link methods
For：
Wherein, NfFor Life Cycle number,It is characterized fatigue life.Natural logrithm twice is taken to Reliability Function formula, is obtained
It arrives：
Then have：
Y=bNx+β
Wherein,
X=lnNf
This method carries out Weibull estimation of distribution parameters using Least Square Regression Analysis, obtains FATIGUE LIFE DISTRIBUTION
The estimated value of index：
Same material service life profile exponent b under the conditions of mutually synthermal, different loadsNApproximation obeys standardized normal distribution,
Using the mean value of the service life profile exponent obtained under the conditions of each load level of different type sample as bNValue；
Step (3) is based on smooth pole test data and introduces SWT parameters, establishes three parameter Power Functions certainty service life moulds
Type:
Nf△Wm=Nf(△WSWT-△W0)m=c
Wherein, c, m, Δ W0Three parameters are parameter related with material, pass through minimum two based on step (1) test data
Multiply regression analysis to be fitted to obtain；Δ W is impairment parameter, Δ W=Δs WSWT-ΔW0, Δ WSWT=Δ εtσmax, Δ εtFor overall strain model
It encloses, σmaxFor maximum stress.
Step (4) impairment parameter profile exponent bWAccording to the sample service life profile exponent b obtained in step (2)NAnd step
(3) the index coefficient m in the tri- parameter Power Functions life models of SWT obtained in is determined jointly：
Step (5) carries out finite element analysis to center hole plane plate specimen, calculates its plastic-elastic stress/strain field, will be every
The result data and volume of a unit export, and numerical integration is carried out to total, in conjunction with Finite element analysis results data and
The impairment parameter profile exponent b that step (4) obtainsWCalculate effective impairment parameter
Wherein, reference volume V0It is accumulated for the examination segment body of sample.
Effective impairment parameter that step (6) is calculated according to step (5)The tri- parameter powers of SWT established with step (3)
Function certainty life model calculates feature fatigue life
Wherein,For effective impairment parameter；M, c is the material parameter in tri- parameter Power Functions life models of SWT.
The feature fatigue life that step (7) is calculated according to step (6)The service life profile exponent b calculated with step (2)N,
Establish the fatigue life Weibull distribution function formula of center hole plane plate specimen：
Step (8) according to the fatigue life Weibull distribution function formula of step (7), use respectively smooth pole sample and
100% two kinds of service life profile exponents of dimension scale center hole plane plate specimen acquire when reliability Ps or failure probability take 0.5
The prediction median life N of 100% dimension scale center hole plane plate specimen is directed under two kinds of service life profile exponentsp。
Based on 100% dimension scale center hole plane plate specimen service life profile exponent value, for 100%, 80%, 60%,
The different dimension scale center hole plane plate specimens such as 40% carry out life prediction using this method, carry out statistics dimensional effect point
Analysis, obtaining life prediction, the results are shown in Figure 2.
Smooth pole sample is respectively adopted in step (9) and the distribution of 100% dimension scale center hole plane plate specimen service life refers to
Number, when reliability Ps takes 0.9987 and 0.0013 respectively, assesses structural life-time reliability, obtains the examination of center hole tablet
± 3 σ life curves of sample.Life expectance analysis result when Fig. 3 gives using smooth pole sample service life profile exponent, figure
Middle abscissa is fatigue life, and ordinate is the effective impairment parameter obtained using integration type, the examination of center hole plane plate specimen
Data are tested to fully fall within the scope of ± 3 σ.
Above example is provided just for the sake of the description purpose of the present invention, and is not intended to limit the scope of the present invention.This
The range of invention is defined by the following claims.It does not depart from spirit and principles of the present invention and the various equivalent replacements made and repaiies
Change, should all cover within the scope of the present invention.
Claims (5)
1. a kind of turbine disk life expectance analysis method of the Weakest-Link methods based on SWT parameters, it is characterised in that：It is real
It is existing that steps are as follows：
Step (1) turbine disk sample coupon fatigue test：Distinguish for turbine disk different parts material property and local geometric features
Design structure simulating piece and disk base sampling plan simultaneously carry out experiment, are sampled from disk base and carry out smooth pole low-cycle fatigue examination
It tests, obtains the low-circulation fatigue performance of material；By carrying out in a series of 100%, 80%, 60%, 40% different dimension scales
Heart circular hole treadmill test obtains turbine disk stress concentration position low cycle fatigue life and assesses data；
Step (2) passes through fatigue life Weibull points to smooth pole test data and center hole plane plate specimen test data
Cloth estimates of parameters is analyzed, and is obtained Reliability Function based on Weakest-Link methods, is obtained service life profile exponent bN；
Step (3) establishes tri- parameter Power Functions life models of SWT based on smooth pole test data, passes through least square regression point
Analysis obtains the index coefficient m in tri- parameter Power Functions life models of SWT；
Step (4) impairment parameter profile exponent bWAccording to the sample service life profile exponent b obtained in step (2)NIn step (3)
Index coefficient m is determined jointly in obtained tri- parameter Power Functions life models of SWT；
Step (5) combines the impairment parameter distribution that center hole plane plate specimen Finite element analysis results data and step (4) obtain
Index bWEffective impairment parameter is calculated
Step (6) is according to effective impairment parameter of step (5)The SWT tri- parameter Power Functions service life moulds established with step (3)
Feature fatigue life is calculated in type
The feature fatigue life that step (7) is calculated according to step (6)The service life profile exponent b calculated with step (2)N, in obtaining
The fatigue life Weibull distribution function formula of heart circular hole plane plate specimen；
The fatigue life Weibull distribution function formula that step (8) is obtained according to step (7), as reliability PsOr failure probability takes
When 0.5, the prediction median life N of center hole plane plate specimen is acquiredp, as reliability PsWhen taking 0.9987 and 0.0013 respectively, obtain
To ± 3 σ life curves of center hole plane plate specimen；
In the step (2), the analysis of Weibull estimation of distribution parameters values is carried out for sample data, is based on Weakest-Link
Method is derived by Reliability Function：
Wherein, NfFor Life Cycle number,It is characterized fatigue life, natural logrithm twice is taken to Reliability Function formula, passes through minimum
Square law regression analysis obtains the estimated value of parameter：
Wherein, x=lnNf, y=ln [ln1/1-Pf(Nf)], same material service life under the conditions of mutually synthermal, different loads is distributed
Index bNApproximation obeys standardized normal distribution, by the service life profile exponent obtained under the conditions of each load level of different type sample
Mean value is as bNValue；
In the step (3), SWT parameters are introduced based on smooth pole test data, established for three parameter Power Functions certainty service life
Model form is as follows：
NfΔWm=Nf(ΔWSWT-ΔW0)m=c
Wherein, c, m, Δ W0Three parameters are parameter related with material, can pass through least square based on step (1) test data
Regression analysis is fitted to obtain；Δ W is impairment parameter, Δ W=Δs WSWT-ΔW0, Δ WSWT=Δ εtσmax, Δ εtFor overall strain model
It encloses, σmaxFor maximum stress.
2. the turbine disk life expectance of a kind of Weakest-Link methods based on SWT parameters according to claim 1 point
Analysis method, it is characterised in that：In the step (4), impairment parameter profile exponent b is calculatedWWhen, using following methods：
3. the turbine disk life expectance of a kind of Weakest-Link methods based on SWT parameters according to claim 1 point
Analysis method, it is characterised in that：In the step (5), effective impairment parameter is calculatedWhen, using following methods：
Wherein, reference volume V0It is accumulated for the examination segment body of sample；Δ W is impairment parameter, is determined by step (3)；bWFor impairment parameter
Profile exponent is determined by step (4).
4. the turbine disk life expectance of a kind of Weakest-Link methods based on SWT parameters according to claim 1 point
Analysis method, it is characterised in that：In the step (6), feature fatigue life is calculatedUsing following methods：
Wherein,For effective impairment parameter, it is calculated by step (5)；M, c is in tri- parameter Power Functions life models of SWT
Material parameter, by step (3) determine.
5. the turbine disk life expectance of a kind of Weakest-Link methods based on SWT parameters according to claim 1 point
Analysis method, it is characterised in that：In the step (7), fatigue life Weibull distribution function formula form is as follows：
Wherein,It is characterized fatigue life, is calculated according to step (6)；bNFor service life profile exponent, determined by step (2).
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| CN108629092B (en) * | 2018-04-20 | 2019-03-22 | 北京航空航天大学 | One kind being based on the modified turbine disk subregion analysis method for reliability of dimensional effect |
| IT201800020743A1 (en) * | 2018-12-21 | 2020-06-21 | Milano Politecnico | SYSTEM FOR THE PROBABILISTIC EVALUATION OF FATIGUE OF PARTS IN THE PRESENCE OF MANUFACTURING DEFECTS |
| CN111693387A (en) * | 2020-06-15 | 2020-09-22 | 一汽解放汽车有限公司 | Method for determining minimum number of rapid fatigue tests |
| CN113627049B (en) * | 2021-07-16 | 2023-08-18 | 武汉钢铁有限公司 | Method for evaluating fatigue strength of ultra-high-strength steel large sample in ultra-long service life |
| CN115452395B (en) * | 2022-08-31 | 2023-11-03 | 中国航发沈阳发动机研究所 | Method for determining safety life of rotor disk of aero-engine |
| CN116013438B (en) * | 2023-01-31 | 2024-06-21 | 天津大学 | Laser cladding material-increasing fatigue life prediction method and system based on micro defect distribution |
| CN117473841B (en) * | 2023-12-28 | 2024-03-26 | 中国航发四川燃气涡轮研究院 | Wheel disc low cycle fatigue life analysis body method and system considering fatigue volume effect |
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