CN102819651A - Simulation-based parameter optimizing method for precise casting process of single crystal turbine blade - Google Patents
Simulation-based parameter optimizing method for precise casting process of single crystal turbine blade Download PDFInfo
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Abstract
The invention discloses a simulation-based parameter optimizing method for a precise casting process of a single crystal turbine blade. According to the simulation-based parameter optimizing method, the technical problem of poor optimization effect of the precise casting process of the single crystal turbine blade is solved. The technical scheme provided by the invention is that the simulation-based parameter optimizing method comprises the following steps of: designing a casting system model of the single crystal turbine blade; carrying out unit division on the casting system model by adopting a finite element analysis method; obtaining a precise casting process parameter and a reasonable parameter change range which have greater influence on the dimensional precision of a precise casting blade molded surface by extracting and identifying precise casting process parameters through a single factor process test; carrying out numerical simulation on the casting process according to the established test table; estimating the deformation condition of a casting relative to the designed model by processing and analyzing the data; and gradually narrowing the search range of the parameter optimization of the precise casting process by establishing a BP (Back propagation) neural network model and adopting a small-step searching method. The optimization effect of the parameter optimization method for the precise casting process of the single crystal turbine blade is improved.
Description
Technical field
The present invention relates to a kind of single crystal turbine blade precision casting technology parameter optimization method, particularly relate to a kind of single crystal turbine blade precision casting technology parameter optimization method based on emulation.
Background technology
Complicated hollow turbine vane is the core technology of high thrust-weight ratio engine, is the most crucial parts of engine, also is easy fracture inefficacy part.Its performance level is particularly held high temperature capabilities, is the important symbol of the advanced degree of a kind of model engine, in a sense, also is the distinctive marks of a state aviation industrial level.Because its inner cooling structure complicacy, aerodynamic configuration and dimension precision requirement are higher; And long service is under strong thermal shock and complex loops thermal stress working condition, so hollow turbine vane structural design and manufacturing technology become the core technology of high thrust-weight ratio aeromotor.
Hollow turbine vane generally adopts crystallographic orientation or monocrystalline not to have the surplus hot investment casting; Because turbo blade is the thin-wall construction (wall thickness 0.5mm-2mm) that a large amount of free form surfaces and complicated inner cavity are formed; The profile precision of smart casting blade is low, the wall thickness dimension drift is big, quality is unstable, rejection rate is very high, is the bottleneck of the novel aeromotor development of restriction China always.
The smart casting of blade be a multiform become factor and multiple should, the complex dynamic process that intercouples of drag source, what influence blade dimensions also is multifactorial coupling.Domestic casting technique generally adopts " experience+test " method, promptly relies on the knowhow technological parameter, and the site test research precision casting technology parameter through repeatedly is to the influence of single crystal turbine blade Forming Quality.This method intelligence and automaticity are low, and cost is higher, and the R&D cycle is long, does not have the theoretical foundation of science, is difficult to carry out effectively the precision casting technology parameter optimization, can not adapt to the demand of modern market high speed development and cut-throat competition.
Summary of the invention
Optimize the deficiency of weak effect in order to overcome existing single crystal turbine blade precision casting technology parameter optimization method, the present invention provides a kind of single crystal turbine blade precision casting technology parameter optimization method based on emulation.This method is through design single crystal turbine blade running gate system; Adopt finite element method that the running gate system model is carried out dividing elements; To blade precision casting technology parameter extraction and discrimination, and obtain bigger precision casting technology parameter and the Reasonable Parameters variation range of smart casting blade molding surface size precision influence through single factor engineer testing; Design mutual orthogonal test, carry out the numerical simulation of casting process according to the test card of setting up, to obtain the turbo blade casting deformation situation in the casting process; Through data processing and analysis; The assessment foundry goods is with respect to the distortion situation that designs a model; Through setting up the BP neural network model; Adopt the long searching method of small step, dwindle the hunting zone of precision casting technology parameter optimization gradually, can improve the optimization effect of single crystal turbine blade precision casting technology parameter optimization method.
The technical solution adopted for the present invention to solve the technical problems is: a kind of single crystal turbine blade precision casting technology parameter optimization method based on emulation is characterized in may further comprise the steps:
Step 1: set up single crystal turbine blade running gate system model, adopt finite element method that the running gate system model is carried out dividing elements.
Step 2:, and obtain precision casting technology parameter and the Reasonable Parameters variation range bigger to single crystal turbine blade molding surface size precision influence through single factor engineer testing to single crystal turbine blade precision casting technology parameter extraction and discrimination.
Step 3: according to the mutual orthogonal test form of the precision casting technology parameter designing in the step 2.
Step 4: carry out the numerical simulation of casting process according to the mutual orthogonal test form of setting up, to obtain the turbo blade casting deformation situation in the casting process.At first apply the numerical simulation boundary condition, comprise the thermal physical property parameter of alloy material and formwork material, initial cast alloy temperature, end the interface heat exchange coefficient between alloy temperature, alloy material and the finish cast die shell of numerical evaluation, the constraint condition of model displacement.Through finding the solution of essence casting process stress field, draw the stress distribution of smart each node of casting process turbo blade grid model, and then derive the displacement of each node, set up the displacement field model.
Step 5: the simulation result that obtains according to step 3 carries out data processing and analysis.A plurality of two-dimensional sections on the parametric method intercepting blade differing heights such as use; Adopt the two-dimension displacement in the method calculating foundry goods cross section of corresponding point to distribute; Expressed the three-D displacement field of foundry goods again by the two-dimension displacement distributed collection in a plurality of cross sections, the assessment foundry goods is with respect to the distortion situation that designs a model.Mutual orthogonal test form in the integrating step three obtains train samples and best precision casting technology parameter.Concrete steps are following:
[1] the ViewCAST module through ProCAST derives the blade realistic model, and data layout is " * .sm ";
[2] be " * .STL " form with " * .sm " format conversion;
[3] step 1 is set up single crystal turbine blade running gate system model and single crystal turbine blade wax-pattern cad model importing carrying out three-dimensional registration;
[4] after three-dimensional registration, along 5～8 section lines of model short transverse intercepting, obtain single crystal turbine blade running gate system model and single crystal turbine blade wax-pattern cad model at the two-dimensional section of sustained height, derive section line simultaneously;
[5] section line to intercepting waits parameter discrete, and with the discrete point ordering, uses the UG Secondary Development Module and discrete point is read in the displacement that calculates between the corresponding discrete point;
[6] the mutual orthogonal test form in the integrating step three is done normalization processing and range analysis to data, obtains train samples and best precision casting technology parameter combinations.
Step 6: set up the BP neural network model, with the train samples neural network training that obtains in the step 5.
Step 7: the BP neural network model of setting up in the integrating step six, adopt little step length searching way, dwindle the hunting zone of precision casting technology parameter optimization gradually, finally make the corresponding profile displacement of parameters optimization less than requiring numerical value.Little step length searching optimization method process is following:
[1] near the value point that has obtained, each variable is increased and reduces small step-length δ
i(i=1,2,3,4) mix into many group precision casting technology combinations of parameters to these parameters, promptly generate new orthogonal table;
[2] calculate a series of blade profile displacement △ Z through the BP neural network model;
[3] search and obtain the corresponding precision casting technology parameter combinations of vanelets profile displacement more;
Return step [1] till blade profile displacement △ Z numerical value reaches requirement.
The invention has the beneficial effects as follows: because through design single crystal turbine blade running gate system; Adopt finite element method that the running gate system model is carried out dividing elements; To blade precision casting technology parameter extraction and discrimination, and obtain bigger precision casting technology parameter and the Reasonable Parameters variation range of smart casting blade molding surface size precision influence through single factor engineer testing; Design mutual orthogonal test, carry out the numerical simulation of casting process according to the test card of setting up, to obtain the turbo blade casting deformation situation in the casting process; Through data processing and analysis, the assessment foundry goods through setting up the BP neural network model, adopts the long searching method of small step with respect to the distortion situation that designs a model, and dwindles the hunting zone of precision casting technology parameter optimization gradually.Improved the optimization effect of single crystal turbine blade precision casting technology parameter optimization method.
Below in conjunction with accompanying drawing and embodiment the present invention is elaborated.
Description of drawings
Fig. 1 is the process flow diagram that the present invention is based on the single crystal turbine blade precision casting technology parameter optimization method of emulation.
Fig. 2 is used certain the model turbo-power leaf model figure of the inventive method.
Fig. 3 is the cad model of the used running gate system of the inventive method.
Fig. 4 be in the inventive method the profile displacement with the drawing velocity change curve.
Fig. 5 is the temperature field synoptic diagram of used certain the model turbo-power blade process of setting of the inventive method.
Fig. 6 is the inventive method BP neural metwork training process flow diagram.
Fig. 7 is that process flow diagram is optimized in the search of the little step-length of the inventive method.
Embodiment
Following examples are with reference to Fig. 1～7.
Step 1: adopt certain model turbo-power blade, its major parameter is the long 106.10mm of blade, maximum chord length 56.21mm, maximum inscribed circle radius 5.7mm, leading-edge radius 4.12mm, trailing edge radius 1.25mm.Blade is selected second generation single crystal super alloy DD6 for use, and formwork is selected silica sand for use.According to casting feeding theory and practical production experience,, adopt the teeming formula, 2 one group to power blade design blade casting technique and running gate system.
Step 2: adopt commercial finite element pre-processing software Hypermesh (product of U.S. Altair company) model to be carried out dividing elements based on non-uniform grid subdivision technology; At first the running gate system model is imported among the Hypermesh; It is dispersed is tetrahedron element; Element quality satisfies general enterprise finite element analysis quality requirements; In the present embodiment, require the element quality more than 95% to satisfy: the unit warpage less than 5.0, length limit, unit ratio less than 5.0, deflection less than 60.0, the unit Jacobi is greater than 0.7.Tetrahedron element sum 730,000 7 thousand.
Step: 3: extract to the bigger precision casting technology parameter of turbo blade fine casting type surface accuracy size impact; Like drawing velocity, pouring temperature, formwork preheat temperature, cold copper temperature, formwork thickness, holding temperature or the like; The present invention only studies preceding four parameters, and all the other parameters keep in test fixed value.
Adopt of the influence of single factor process test research precision casting technology parameter to turbo blade profile precision size.Test card and test findings are as shown in table 1.
Table 1 single factor engineer testing table and result
In order to see influence and the rule thereof of each technological parameter more intuitively to fine casting type face size, adopt drawing instrument, be horizontal ordinate with the precision casting technology parameter, the profile displacement that thereupon changes is that ordinate is drawn.
According to the curve map of drawing, can find variation along with the precision casting technology parameter, the blade profile size presents the obvious variation rule, confirms the factor level table of the reasonable selected value and the orthogonal test of parameter with this, and is as shown in table 2.
Table 2 factor level table
Step 4: by step 2, the precision casting technology parameter that need be optimized has drawing velocity, pouring temperature, formwork preheat temperature, cold copper temperature.Each factor is chosen three levels, considers the reciprocation between drawing velocity, pouring temperature, these three factors of formwork preheat temperature simultaneously, adopts the design of L23 (313) reciprocation table, and concrete test card is following:
The mutual test card of table 3
The cold copper temperature of A drawing velocity B pouring temperature C formwork preheat temperature D
Step 5:, adopt ProCAST that turbo blade is carried out essence casting Numerical simulation according to the orthogonal test table in the step 3.Alloy is selected the DD6 high-temperature nickel-base alloy for use, and its liquidus temperature is 1380 ℃, and solidus temperature is 1310 ℃.Its pyroconductivity is 33.2W/mK, and density is 8780kg/m
3, specific heat is 99.0KJ/Kg/K.Formwork is selected silica sand for use, and its pyroconductivity is 0.59W/mK, and density is 1520kg/m
3, specific heat is 1.20KJ/Kg/K.The alloy temperature of numerical simulation termination of computations is 600 ℃.Displacement constrains is that running channel bottom and blade seeding section bottom fixing and cold copper bottom is fixing.
Step 6: handle and analysis directional solidification Numerical simulation result.The blade realistic model of accomplishing three-dimensional registration and blade cad model along 5 section lines of Z axle intercepting, highly are respectively 320mm, 330mm, 340mm, 350mm, 360mm, 370mm, 380mm, 390mm, and Treatment Analysis result is as shown in the table:
Table 4
27 groups of tests are as train samples, and best precision casting technology parameter is drawing velocity 5mm/min, 1550 ℃ of pouring temperatures, 1470 ℃ of formwork preheat temperatures, 24 ℃ of cold copper temperature.
Step 7: adopt the three-layer artificial neural network, train and set up the Neural Network Optimization model.Neural network adopts the BP network based on the Liebenberg-Marquardt optimized Algorithm, and hidden layer is a Sigmoid type activation function, and output layer is selected Purelin type activation function for use.The neural network structure of precision casting technology parameter and blade profile displacement is: 4 nodes of input layer, the precision casting technology parameter of its parameter for extracting comprises drawing velocity, pouring temperature, formwork preheat temperature, cold copper temperature.Output layer is 1 node, and its parameter is the The results of numerical simulation output quantity, i.e. the blade profile displacement.With training sample the neural network of setting up is trained, and neural network is verified, if error is in tolerance band, with the threshold value that obtains neural network and weight matrix as the neural network matrix.Set up a mapping relations model like this, can shine upon the relation between precision casting technology parameter and the blade profile displacement.Fig. 6 is BP neural network structure figure, and wherein A is a drawing velocity, and B is a pouring temperature, and C is the formwork preheat temperature, and D is cold copper temperature.
Step 8: combine neural network, adopt the long searching method of small step to optimize the precision casting technology parameter.Initial small step-length δ
i(i=1,2,3,4) are respectively δ
1=0.2mm/min, δ
2=20 ℃, δ
3=20 ℃, δ
4=1 ℃, blade profile dimensional accuracy △ Z=0.185mm.After calculating for the first time, △ Zmin=0.1820mm has met accuracy requirement.The optimization precision casting technology parameter group such as the following table that finally obtain:
Table 5
| Drawing velocity | Pouring temperature | The formwork preheat temperature | Cold copper temperature | Displacement | |
| The final optimization pass scheme | 4.8 | 1550 | 1480 | 24 | 0.1820 |
Claims (1)
1. single crystal turbine blade precision casting technology parameter optimization method based on emulation is characterized in that may further comprise the steps:
Step 1: set up single crystal turbine blade running gate system model, adopt finite element method that the running gate system model is carried out dividing elements;
Step 2:, and obtain precision casting technology parameter and the Reasonable Parameters variation range bigger to single crystal turbine blade molding surface size precision influence through single factor engineer testing to single crystal turbine blade precision casting technology parameter extraction and discrimination;
Step 3: according to the mutual orthogonal test form of the precision casting technology parameter designing in the step 2;
Step 4: carry out the numerical simulation of casting process according to the mutual orthogonal test form of setting up, to obtain the turbo blade casting deformation situation in the casting process; At first apply the numerical simulation boundary condition, comprise the thermal physical property parameter of alloy material and formwork material, initial cast alloy temperature, end the interface heat exchange coefficient between alloy temperature, alloy material and the finish cast die shell of numerical evaluation, the constraint condition of model displacement; Through finding the solution of essence casting process stress field, draw the stress distribution of smart each node of casting process turbo blade grid model, and then derive the displacement of each node, set up the displacement field model;
Step 5: the simulation result that obtains according to step 3 carries out data processing and analysis; A plurality of two-dimensional sections on the parametric method intercepting blade differing heights such as use; Adopt the two-dimension displacement in the method calculating foundry goods cross section of corresponding point to distribute; Expressed the three-D displacement field of foundry goods again by the two-dimension displacement distributed collection in a plurality of cross sections, the assessment foundry goods is with respect to the distortion situation that designs a model; Mutual orthogonal test form in the integrating step three obtains train samples and best precision casting technology parameter; Concrete steps are following:
[1] the ViewCAST module through ProCAST derives the blade realistic model, and data layout is " * .sm ";
[2] be " * .STL " form with " * .sm " format conversion;
[3] step 1 is set up single crystal turbine blade running gate system model and single crystal turbine blade wax-pattern cad model importing carrying out three-dimensional registration;
[4] after three-dimensional registration, along 5～8 section lines of model short transverse intercepting, obtain single crystal turbine blade running gate system model and single crystal turbine blade wax-pattern cad model at the two-dimensional section of sustained height, derive section line simultaneously;
[5] section line to intercepting waits parameter discrete, and with the discrete point ordering, uses the UG Secondary Development Module and discrete point is read in the displacement that calculates between the corresponding discrete point;
[6] the mutual orthogonal test form in the integrating step three is done normalization processing and range analysis to data, obtains train samples and best precision casting technology parameter combinations;
Step 6: set up the BP neural network model, with the train samples neural network training that obtains in the step 5;
Step 7: the BP neural network model of setting up in the integrating step six, adopt little step length searching way, dwindle the hunting zone of precision casting technology parameter optimization gradually, finally make the corresponding profile displacement of parameters optimization less than requiring numerical value; Little step length searching optimization method process is following:
[1] near the value point that has obtained, each variable is increased and reduces small step-length δ
i(i=1,2,3,4) mix into many group precision casting technology combinations of parameters to these parameters, promptly generate new orthogonal table;
[2] calculate a series of blade profile displacement △ Z through the BP neural network model;
[3] search and obtain the corresponding precision casting technology parameter combinations of vanelets profile displacement more;
Return step [1] till blade profile displacement △ Z numerical value reaches requirement.
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