CN110175394A - A kind of turbo blade spleen tissue extracts damage coupling Probabilistic Life Prediction calculation method - Google Patents
A kind of turbo blade spleen tissue extracts damage coupling Probabilistic Life Prediction calculation method Download PDFInfo
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Abstract
The invention discloses a kind of turbo blade spleen tissue extracts to damage coupling Probabilistic Life Prediction calculation method, comprising the following steps: S1, collects turbo blade attribute；S2, examination position is determined；S3, finite element simulation is carried out to turbo blade, obtains turbo blade examination point ess-strain information；S4, it calculates fatigue damage: fatigue life and fatigue damage information is calculated by low-cycle fatigue life model；S5, it calculates creep impairment: creep life and creep impairment information is calculated by creep life model；S6, it calculates overall impairment and carries out service life fitting of distribution；S7, it is based on cumulative damage theory, obtains the final life expectance distribution of blade in conjunction with various working life information.The present invention characterizes uncertain factor caused by the material property of turbo blade, load history, geometric dimension, error prediction model etc. with probability, it is predicted with service life of the Probabilistic Life Prediction model to turbo blade, can be improved the precision of turbine blade life prediction.
Description
Technical field
The invention belongs to aerospace technical field of engines, in particular to a kind of turbo blade spleen tissue extracts damage coupling
Close Probabilistic Life Prediction calculation method.
Background technique
Turbo blade is the important composition component of aero-engine, in high temperature, high pressure and high-revolving complex condition work
Make, will lead to serious consequence once occurring to destroy.Aero-engine failure caused by being failed due to turbo blade accounts for aviation hair
70% or more of motivation failure event, therefore Probabilistic Life Prediction is carried out to turbo blade and is of great significance.
Turbo blade working environment is badly complicated, mainly by the centrifugal load as caused by high revolving speed and aerodynamic force, heat
The effect of the factors such as stress.The dominant failure mode of turbo blade has low-cycle fatigue fracture failure, high-temerature creep failure, high week tired
Labor failure, fretting fatigue and corrosion fracture failure etc..Particularly, under the action of high centrifugal load and high-temperature load, turbine
Blade is very easy to generate fatigue fracture and high-temerature creep phenomenon, with the increase of flight time, finally generates fatigue fracture and loses
Effect and creep failure.
There are many uncertainties in the turbo blade course of work.Material property, load history, geometric dimension, prediction mould
Uncertainty caused by type error etc. can all impact the life prediction of turbo blade.Effectively quantify and to characterize these not true
It is qualitative, the service life of turbo blade can be predicted more accurately.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of by the material property of turbo blade, load
Course, geometric dimension, error prediction model etc. cause uncertain factor to be characterized with probability, with Probabilistic Life Prediction mould
Type predicts the service life of turbo blade, can be improved the turbo blade spleen tissue extracts of the precision of turbine blade life prediction
Damage coupling Probabilistic Life Prediction calculation method.
The purpose of the present invention is achieved through the following technical solutions: a kind of turbo blade spleen tissue extracts damage coupling
Probabilistic Life Prediction calculation method, comprising the following steps:
S1, turbo blade attribute is collected: to material properties, the model of turbo blade founding materials nickel base superalloy K403
The load attribute that parameter attribute and turbo blade are born is collected；
S2, it determines examination position: by input material attribute, Finite Element Simulation Analysis being carried out to turbo blade, determines whirlpool
The examination position of impeller blade；
S3, simulation analysis: the operating condition based on different condition is carried out, Latin Hypercube Sampling is carried out to revolving speed, obtains revolving speed
Information, and then finite element simulation is carried out to turbo blade, obtain turbo blade examination point ess-strain information；
S4, it calculates fatigue damage: fatigue life and fatigue damage information is calculated by low-cycle fatigue life model；
S5, it calculates creep impairment: creep life and creep impairment information is calculated by creep life model；
S6, it calculates overall impairment and carries out service life fitting of distribution: it is theoretical based on linear progressive damage, it obtains under single operating condition
The total damage information and life information that spleen tissue extracts couple in single cycle；
S7, it is based on cumulative damage theory, obtains the final life expectance distribution of blade in conjunction with various working life information.
Further, the step S4 concrete methods of realizing are as follows: selection Manson-Coffin formula be calculated tired
Labor service life and fatigue damage information；
Shown in Manson-Coffin formula expression such as formula (1):
Fatigue life information N is calculated by formula (1)f, single cycle fatigue is calculated according further to formula (2)
Damage Df:
In formula,For equivalent strain, σ 'fFor coefficient of elasticity, E is elasticity modulus, and b is elasticity indexes, ε 'fFor ductility system
Number, c is ductility index.
Further, the step S5 concrete methods of realizing are as follows: by Larson-Miller formula calculate creep life and
Creep impairment information；
Larson-Miller formula expression are as follows:
lgtrupture=b0+b1/T+b2X/T+b3X2/T+b4X3/T (3)
Creep life information t is calculated by formula (3)rupture, it is further advanced by formula (4) and calculates single cycle creep
Damage Dc:
In formula, b0、b1、b2、b3And b4For the Creep Equation fitting coefficient of turbo blade founding materials；truptureFor the lasting longevity
Life；X is stress logarithm, X=lg σ；T=(9 θ/5+32)+460, θ is blade surface temperature, and unit is DEG C；tcWhen being carried to protect
Between.
Further, the step S6 includes following sub-step:
S61, it is based on formula (5) and formula (6), calculates examination point life information:
Dtotal=Df+Dc (5)
In formula, DtotalIt is always damaged for single cycle；NtotalFor the total fatigue life information of single cycle；
S62, the K-S inspection that the level of signifiance is 0.05 is carried out to the life information of examination point, meets logarithm normal distribution；
The probability density function of examination point life information are as follows:
In formula,The mean value of the normal distribution met after logarithm is taken for the examination point service life；For the examination point longevity
Life takes the standard deviation of the normal distribution met after logarithm；
S63, the service life distribution of examination point is fitted in Matlab, obtains the service life distribution map of examination point.
The beneficial effects of the present invention are: the present invention establishes the probability longevity for aero engine turbine blades spleen tissue extracts
Prediction model is ordered, by quantifying to blade loading parameter, the uncertain of model parameter, in conjunction with finite element simulation, is calculated
The fatigue damage and creep impairment of turbo blade；It is based on damage accumulation principle simultaneously, turbo blade under single operating condition is calculated
Total damage information, fitting obtain turbine blade life distribution；Various working information is finally combined, turbo blade life expectance is obtained
Distribution.The material property of turbo blade, load history, geometric dimension, error prediction model etc. are caused uncertainty by the present invention
Factor is characterized with probability, is predicted with service life of the Probabilistic Life Prediction model to turbo blade, be can be improved turbine
The precision of leaf longevity prediction.
Detailed description of the invention
Fig. 1 is the flow chart of turbo blade spleen tissue extracts damage coupling Probabilistic Life Prediction calculation method of the invention；
Fig. 2 is the service life distribution map of examination point 1 in the present embodiment；
Fig. 3 is the service life distribution map of examination point 2 in the present embodiment.
Specific embodiment
Technical solution of the present invention is further illustrated with reference to the accompanying drawing.
As shown in Figure 1, a kind of turbo blade spleen tissue extracts damage coupling Probabilistic Life Prediction calculation method, including it is following
Step:
S1, turbo blade attribute is collected: to material properties, the model of turbo blade founding materials nickel base superalloy K403
The load attribute that parameter attribute and turbo blade are born is collected；
S2, it determines examination position: by input material attribute, Finite Element Simulation Analysis being carried out to turbo blade, determines whirlpool
The examination position of impeller blade；Turbo blade is on active service in complex working condition, the load being mainly subject to be centrifugal load, aerodynamic loading and
Temperature loading.Turbo blade is divided into two parts in ANSYS software to emulate, first part is by integral shroud, blade, listrium group
At second part is to respectively obtain the Stress distribution cloud atlas of two-part turbo blade, wherein first inside blade root
The maximum stress strain divided is below second part, but first part's ess-strain maximum point temperature is 730.29 DEG C, second
It is 532.39 DEG C that the component of stress, which strains maximum point temperature,.It is thus determined that two examination positions of turbo blade are as follows, first is leaf
With the contact site of integral shroud at the top of body, second position is inside blade root.
S3, simulation analysis: the operating condition based on different condition is carried out, Latin Hypercube Sampling is carried out to revolving speed, obtains revolving speed
Information, and then finite element simulation is carried out to turbo blade, obtain turbo blade examination point ess-strain information；
According to studies have shown that aero engine turbine blades revolving speed Normal Distribution.Have in aero-engine work and " opens
Dynamic-maximum-starting ", " cruise-maximum-cruise ", " slow train-maximum-slow train " three kinds of load cycle states, below with " starting-
Calculation specifications are carried out for maximum-starting ".In " starting-maximum-starting " working cycles, with maximum (top) speed 17000rpm work
For mean value, maximum (top) speed 2.5% is used as standard deviation, carries out Latin Hypercube Sampling to revolving speed, 30 groups of rotary speed informations is obtained, to whirlpool
Impeller blade carries out stress simulation, obtains under temperature loading turbo blade stress information and turbo blade strain information is such as at room temperature
Shown in table 1.
Table 1: turbo blade examination point ess-strain information table
S4, it calculates fatigue damage: fatigue life and fatigue damage information is calculated by low-cycle fatigue life model；?
Guarantee it is sufficiently low at a temperature of, turbo blade do not generate creep reaction, can be obtained by the Low Cycle Fatigue Calculation formula of the alloy
To fatigue life.Concrete methods of realizing are as follows: Manson-Coffin formula is selected to carry out that fatigue life and fatigue damage is calculated
Information；
Manson-Coffin formula is most widely used formula in engineering practice, Manson-Coffin formula table
Up to shown in formula such as formula (1):
Fatigue life information N is calculated by formula (1)f, single cycle fatigue is calculated according further to formula (2)
Damage Df:
In formula,For equivalent strain, σ 'fFor coefficient of elasticity, E is elasticity modulus, and b is elasticity indexes, ε 'fFor ductility system
Number, c is ductility index.
Pass through literature survey: K403 alloy fatigue curve data is as follows:B=-0.11, ε 'f=0.022, c
=-0.84.For progress Probability estimate, damage parameters are considered as basic input variable, wherein { b, c, E } is considered as constant, { σ 'f,ε
′fIt is considered as stochastic variable, equally it is sampled with the 2.5% of mean value.Above data is substituted into formula (1), the fatigue being calculated
Damage is as shown in table 2.
Table 2: fatigue damage information table
S5, it calculates creep impairment: creep life and creep impairment information is calculated by creep life model；Turbo blade
Creep life is influenced by factors such as centrifugal load, stress, temperature.Creep life and compacted is calculated by Larson-Miller formula
Become damage information；
Larson-Miller formula expression are as follows:
lgtrupture=b0+b1/T+b2X/T+b3X2/T+b4X3/T (3)
Creep life information t is calculated by formula (3)rupture, it is further advanced by formula (4) and calculates single cycle creep
Damage Dc:
In formula, b0、b1、b2、b3And b4For the Creep Equation fitting coefficient of turbo blade founding materials；truptureFor the lasting longevity
Life；X is stress logarithm, X=lg σ；T=(9 θ/5+32)+460, θ is blade surface temperature, and unit is DEG C；tcWhen being carried to protect
Between.
The K403 high temperature alloy Creep Equation fitting coefficient obtained by literature survey is as follows: b0=-31.921；b1=
4.56×105；b2=-5.11 × 105；b3=2.28 × 105；b4=-3.43 × 104.To two examination point temperature respectively with
The normal distribution that mean value is 730.29, variance is 18.28 and mean value is 532.39, variance is 13.31 is sampled, by coefficient generation
Enter formula (3) and formula (4), it is as shown in table 3 that turbo blade single cycle creep impairment is calculated.
Table 3: turbo blade single creep impairment information table
S6, it calculates overall impairment and carries out service life fitting of distribution: it is theoretical based on linear progressive damage, it obtains under single operating condition
The total damage information and life information that spleen tissue extracts couple in single cycle；Including following sub-step:
S61, linear damage accumulation theory are thought: in each loaded cycle, load accumulated damage is constant, between load
Reciprocation and load load history are unrelated.When total damage reaches 1, turbo blade is broken.Based on formula (5) and formula (6),
The life information of two examination points is calculated:
Dtotal=Df+Dc (5)
In formula, DtotalIt is always damaged for single cycle；NtotalFor the total fatigue life information of single cycle；
S62, for most metals material, service life general Normal Distribution, logarithm normal distribution or Weibull point
Cloth carries out the K-S that the level of signifiance is 0.05 to the life information of examination point 1 and examination point 2 and examines, meets lognormal point
Cloth；The probability density function of examination point life information are as follows:
In formula,The mean value of the normal distribution met after logarithm is taken for the examination point service life；For the examination point longevity
Life takes the standard deviation of the normal distribution met after logarithm；
S63, the service life distribution of examination point 1 and examination point 2 is fitted in Matlab, the distribution difference being fitted
Are as follows: ln Nf11~N (10.2146,0.44762) and ln Nf12~N (9.1097,0.41172), service life distribution map such as Fig. 2 and figure
Shown in 3.
S7, it is based on cumulative damage theory, obtains the final life expectance distribution of blade in conjunction with various working life information.Turbine
Blade has " starting-maximum-starting ", " cruise-maximum-cruise ", " slow train-maximum-slow train " three kinds of operating conditions." cruise-most
Greatly-cruise " is in operating condition, because turbo blade meets with stresses small, leaf longevity is greater than 107, it is considered as infinite life, therefore only examine
Consider " starting-maximum-starting " and " slow train-maximum-slow train " two kinds of operating conditions.With identical method, it is calculated " slow train-is most
The service life distribution of turbo blade examination point 1 under greatly-slow train " operating condition: ln Nf21~N (11.6838,0.4237), the longevity of examination point 2
Life distribution: ln Nf22~(10.4583,0.4146).Based on Miner rule, turbo blade can be calculated in convolution (8)
The distribution of outfield working time, i.e. life expectance are distributed:
In formula, n is the cycle-index of turbo blade in 800 hours loading spectrums.
It is sampled calculating with Monte Carlo method, the service life of turbo blade is distributed substitution formula (8), obtains turbine leaf
The life expectance distribution of piece examination point 1 and examination point 2 are as follows: lnTf1~N (9.5086,0.36922), lnTf2~N (8.3810,
0.33582).Therefore the last turbo blade life expectance relatively obtained is distributed as lnTf~N (8.3810,0.33582)。
Those of ordinary skill in the art will understand that the embodiments described herein, which is to help reader, understands this hair
Bright principle, it should be understood that protection scope of the present invention is not limited to such special statement and example.This field it is general
Logical technical staff disclosed the technical disclosures can make according to the present invention and various not depart from the various other of essence of the invention
Specific variations and combinations, these variations and combinations are still within the scope of the present invention.
Claims (4)
1. a kind of turbo blade spleen tissue extracts damage coupling Probabilistic Life Prediction calculation method, which is characterized in that including following step
It is rapid:
S1, turbo blade attribute is collected: to the material properties, model parameter attribute and turbo blade of turbo blade founding materials
The load attribute of receiving is collected；
S2, it determines examination position: by input material attribute, Finite Element Simulation Analysis being carried out to turbo blade, determines turbine leaf
The examination position of piece；
S3, simulation analysis: the operating condition based on different condition is carried out, Latin Hypercube Sampling is carried out to revolving speed, obtains rotary speed information,
And then finite element simulation is carried out to turbo blade, obtain turbo blade examination point ess-strain information；
S4, it calculates fatigue damage: fatigue life and fatigue damage information is calculated by low-cycle fatigue life model；
S5, it calculates creep impairment: creep life and creep impairment information is calculated by creep life model；
S6, it calculates overall impairment and carries out service life fitting of distribution: it is theoretical based on linear progressive damage, obtain single under single operating condition
The total damage information and life information of spleen tissue extracts coupling in recycling；
S7, it is based on cumulative damage theory, obtains the final life expectance distribution of blade in conjunction with various working life information.
2. a kind of turbo blade spleen tissue extracts damage coupling Probabilistic Life Prediction calculation method according to claim 1,
Be characterized in that, the step S4 concrete methods of realizing are as follows: select Manson-Coffin formula be calculated fatigue life and
Fatigue damage information；
Shown in Manson-Coffin formula expression such as formula (1):
Fatigue life information N is calculated by formula (1)f, single cycle fatigue damage is calculated according further to formula (2)
Df:
In formula,For equivalent strain, σ 'fFor coefficient of elasticity, E is elasticity modulus, and b is elasticity indexes, ε 'fFor ductility factor, c
For ductility index.
3. a kind of turbo blade spleen tissue extracts damage coupling Probabilistic Life Prediction calculation method according to claim 1,
It is characterized in that, the step S5 concrete methods of realizing are as follows: creep life and creep impairment are calculated by Larson-Miller formula
Information；
Larson-Miller formula expression are as follows:
lgtrupture=b0+b1/T+b2X/T+b3X2/T+b4X3/T (3)
Creep life information t is calculated by formula (3)rupture, it is further advanced by formula (4) and calculates single cycle creep impairment
Dc:
In formula, b0、b1、b2、b3And b4For the Creep Equation fitting coefficient of turbo blade founding materials；truptureFor creep rupture life；X
For stress logarithm, X=lg σ；T=(9 θ/5+32)+460, θ is blade surface temperature, and unit is DEG C；tcThe time is carried to protect.
4. a kind of turbo blade spleen tissue extracts damage coupling Probabilistic Life Prediction calculation method according to claim 1,
It is characterized in that, the step S6 includes following sub-step:
S61, it is based on formula (5) and formula (6), calculates examination point life information:
Dtotal=Df+Dc (5)
In formula, DtotalIt is always damaged for single cycle；NtotalFor the total fatigue life information of single cycle；
S62, the K-S inspection that the level of signifiance is 0.05 is carried out to the life information of examination point, meets logarithm normal distribution；Examination
The probability density function of point life information are as follows:
In formula,The mean value of the normal distribution met after logarithm is taken for the examination point service life；It is taken for the examination point service life
The standard deviation of the normal distribution met after logarithm；
S63, the service life distribution of examination point is fitted in Matlab, obtains the service life distribution map of examination point.
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