CN110175383A - Fanjet characteristics of components discrimination method under the conditions of a kind of ground stand test run - Google Patents
Fanjet characteristics of components discrimination method under the conditions of a kind of ground stand test run Download PDFInfo
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- CN110175383A CN110175383A CN201910410442.6A CN201910410442A CN110175383A CN 110175383 A CN110175383 A CN 110175383A CN 201910410442 A CN201910410442 A CN 201910410442A CN 110175383 A CN110175383 A CN 110175383A
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- 238000012360 testing method Methods 0.000 title claims abstract description 83
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- 238000000034 method Methods 0.000 claims abstract description 19
- 238000013461 design Methods 0.000 claims description 62
- 238000005457 optimization Methods 0.000 claims description 36
- 238000013178 mathematical model Methods 0.000 claims description 16
- 230000000694 effects Effects 0.000 claims description 12
- 238000005259 measurement Methods 0.000 claims description 9
- 238000013401 experimental design Methods 0.000 claims description 8
- 239000008186 active pharmaceutical agent Substances 0.000 claims description 4
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- G06F30/32—Circuit design at the digital level
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- G06F30/3323—Design verification, e.g. functional simulation or model checking using formal methods, e.g. equivalence checking or property checking
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Abstract
The application belongs to aero-engine technology field, in particular to fanjet characteristics of components discrimination method under the conditions of a kind of ground stand test run.It include: to obtain engines ground bench test drive parameter；Build characteristics of components Identification Platform；The engines ground bench test drive parameter is input in the characteristics of components Identification Platform, is recognized by the characteristics of components Identification Platform, characteristics of components identification result is obtained.Fanjet characteristics of components discrimination method under the conditions of the ground stand test run of the application, method is simple, is not necessarily to complex mathematical algorithm；General Identification Platform is built, fanjet characteristics of components identification under the conditions of ground stand test run can be realized when firing test data is less.
Description
Technical field
The application belongs to aero-engine technology field, in particular to fanjet under the conditions of a kind of ground stand test run
Characteristics of components discrimination method.
Background technique
During reseach of engine, ground stand test run is the important hand for examining engine whether to reach design objective
Section.Due to starting machining, assembly etc., there are errors, and there are larger inclined for the ground stand test result and design objective of engine
Difference, this just needs to carry out detailed analysis to components such as fan, compressor, turbines, obtains reality of each component under the conditions of complete machine
Characteristic makes engine performance reach design objective so that subsequent Optimal improvements be instructed to work.It was used in addition, obtaining engine
The performance change of each component all has significance to the performance degradation research of complete machine and engine air passage fault diagnosis in journey.But
Due to the limitation of power of test, testing cost and engine this body structure, can not be obtained in ground stand complete machine commissioning process
The desired measured value of the whole of each component, therefore, going out characteristics of components parameter based on existing test measurement data identification has weight
Want meaning.
The thinking for utilizing System Discrimination in the prior art establishes engine identification model and obtains characteristics of components, and engine is distinguished
Know model and is divided into Parameter Estimation Method and characteristics of components method.Parameter Estimation Method is the identification side for being not based on engine air and moving thermodynamic model
Method, this method picks out engine mockup based on a large amount of test data and in conjunction with different mathematical algorithms, so that assessment is started
Machine overall performance, since this method need to be based on a large amount of test data, when firing test data is less, this kind of method is not applicable；And
And the mathematical algorithm selected has large effect to the precision of identification model, to obtain high-precision identification model, needs to not
Same mathematical algorithm does more research, and to the mathematical algorithm Research Ability of designer, more stringent requirements are proposed in this way.Portion
Part characteristic method is the discrimination method based on engine aerothennodynamic model, such method can be identified engine under the conditions of complete machine
Characteristics of components is generallyd use least square method at present and carries out Model Distinguish analysis to engine test data, existed using engine
The firing test data of design point corrects engine components characteristic, obtains the actual characteristic information of each component, but existing research is main
Based on engine in the firing test data of design point, engine components characteristic is corrected, so that the actual characteristic information of each component is obtained,
It is less in the characteristics of components Research on Identification of off-design point, lack general Identification Platform.
Thus, it is desirable to have a kind of technical solution overcomes or at least mitigates at least one drawbacks described above of the prior art.
Summary of the invention
The purpose of the application there is provided fanjet characteristics of components discrimination method under the conditions of a kind of ground stand test run,
With solve the problems, such as it is of the existing technology at least one.
The technical solution of the application is:
Fanjet characteristics of components discrimination method under the conditions of a kind of ground stand test run, comprising:
Obtain engines ground bench test drive parameter；
Build characteristics of components Identification Platform；
The engines ground bench test drive parameter is input in the characteristics of components Identification Platform, the component is passed through
Characteristic Identification Platform is recognized, and characteristics of components identification result is obtained.
Optionally, in the acquisition engines ground bench test drive parameter, the engines ground bench test drive parameter packet
It includes: atmospheric temperature T0, atmospheric pressure P0, rotational speed of lower pressure turbine rotor n1。
Optionally, described to build in characteristics of components Identification Platform, the characteristics of components Identification Platform is based on ISIGHT software
It builds, the characteristics of components Identification Platform includes: experimental design module and optimization design module.
Optionally, in the characteristics of components Identification Platform,
The experimental design of the experimental design module includes: to be made by coordinating each design factor level in design space
The design factor meets Optimal Distribution in the design space；The design factor is analyzed, obtaining, which influences identification, misses
The effect tendency of the design variable of poor E and the design variable to Identification Errors E；
The optimization design of the optimization design module includes: constitution optimization mathematical model；Pass through the optimization of ISIGHT software
Algorithm optimizes the optimized mathematical model.
Optionally, described horizontal by coordinating each design factor in design space, set the design factor described
Meter space meets the test design method of Optimal Distribution for the design of optimal Latin hypercube.
Optionally, the design factor includes: fan flow coefficient W1X, fan pressure ratio coefficient πfX, fan efficiency coefficient
ηfX, compressor discharge coefficient W25X, compressor pressure ratio coefficient πcX, compressor efficiency coefficient ηcX, high-pressure turbine efficiency factor ηhtX、
Low-pressure turbine efficiency factor ηttX, gas pumping coefficient y after compressor stageq9, outer culvert total pressure recovery coefficient πwhX, spout throat area A8。
Optionally, the design variable for influencing Identification Errors E includes: fan flow coefficient W1X, spout throat area A8、
Compressor efficiency coefficient ηcX, fan efficiency coefficient ηfX, high-pressure turbine efficiency factor ηhtX, low-pressure turbine efficiency factor ηttX, calm the anger
Machine discharge coefficient W25X, wherein the fan flow coefficient W1XWith the compressor discharge coefficient W25XInfluence be positive-effect, institute
State spout throat area A8, the compressor efficiency coefficient ηcX, the fan efficiency coefficient ηfX, the high-pressure turbine efficiency factor
ηhtXWith the low-pressure turbine efficiency factor ηttXInfluence be negative effect.
Optionally, in the constitution optimization mathematical model, the optimized mathematical model are as follows:
Input engines ground bench test drive parameter: atmospheric temperature T0, atmospheric pressure P0, rotational speed of lower pressure turbine rotor n1；
Given optimized variable value range, the optimized variable includes: fan efficiency coefficient ηfX, compressor efficiency coefficient
ηcX, high-pressure turbine efficiency factor ηhtX, low-pressure turbine efficiency factor ηttX, spout throat area A8And compressor discharge coefficient
W25X；
Determine that optimization aim, the optimization aim are Identification Errors E minimum.
Optionally, described during the optimization algorithm by ISIGHT software optimizes the optimized mathematical model
Optimization algorithm is DS optimization algorithm.
Optionally, the Identification Errors E are as follows:
Each survey of test is given before the optimization algorithm by ISIGHT software optimizes the mathematical model
Measure parameters weighting wi；
Wherein, m is the tractor parameter number that test measures, ytestFor test measurements, yModelFor engine mockup calculating
Value.
At least there are following advantageous effects in invention:
Fanjet characteristics of components discrimination method under the conditions of the ground stand test run of the application, method is simple, without multiple
Miscellaneous mathematical algorithm；General Identification Platform is built, whirlpool under the conditions of ground stand test run can be realized when firing test data is less
The identification of fan engine characteristics of components.
Detailed description of the invention
Fig. 1 be one embodiment of the application ground stand test run under the conditions of fanjet characteristics of components discrimination method
Universal component characteristic Identification Platform；
Fig. 2 be one embodiment of the application ground stand test run under the conditions of fanjet characteristics of components discrimination method
Characteristics of components identified parameters Pareto chart；
Fig. 3 be one embodiment of the application ground stand test run under the conditions of fanjet characteristics of components discrimination method
Characteristics of components identified parameters main effect figure；
Fig. 4 be one embodiment of the application ground stand test run under the conditions of fanjet characteristics of components discrimination method
Verification result.
Specific embodiment
To keep the purposes, technical schemes and advantages of the application implementation clearer, below in conjunction in the embodiment of the present application
Attached drawing, technical solutions in the embodiments of the present application is further described in more detail.In the accompanying drawings, identical from beginning to end or class
As label indicate same or similar element or element with the same or similar functions.Described embodiment is the application
A part of the embodiment, instead of all the embodiments.The embodiments described below with reference to the accompanying drawings are exemplary, it is intended to use
In explanation the application, and it should not be understood as the limitation to the application.Based on the embodiment in the application, ordinary skill people
Member's every other embodiment obtained without creative efforts, shall fall in the protection scope of this application.Under
Face is described in detail embodiments herein in conjunction with attached drawing.
In the description of the present application, it is to be understood that term " center ", " longitudinal direction ", " transverse direction ", "front", "rear",
The orientation or positional relationship of the instructions such as "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outside" is based on attached drawing institute
The orientation or positional relationship shown is merely for convenience of description the application and simplifies description, rather than the dress of indication or suggestion meaning
It sets or element must have a particular orientation, be constructed and operated in a specific orientation, therefore should not be understood as protecting the application
The limitation of range.
1 to Fig. 4 the application is described in further details with reference to the accompanying drawing.
This application provides fanjet characteristics of components discrimination methods under the conditions of a kind of ground stand test run, comprising:
Obtain engines ground bench test drive parameter；
Build characteristics of components Identification Platform；
The engines ground bench test drive parameter is input in the characteristics of components Identification Platform, the component is passed through
Characteristic Identification Platform is recognized, and characteristics of components identification result is obtained.
In the embodiment of the application, engines ground bench test drive parameter includes: atmospheric temperature T0, atmospheric pressure
Power P0, rotational speed of lower pressure turbine rotor n1。
As shown in Figure 1, under the conditions of the ground stand test run of the application in fanjet characteristics of components discrimination method, portion
Part characteristic Identification Platform is built based on multidisciplinary optimization software I SIGHT software, and characteristics of components Identification Platform includes that test is set
Module and optimization design module are counted, realizes characteristics of components identification in conjunction with engine aerothennodynamic model.
The experimental design module of the characteristics of components Identification Platform of the application can be synthesized and coordinated in design space each design because
It is sub horizontal, so that design factor is met the Optimal Distribution in statistical significance in design space.In engine components characteristic Identification Platform
Design factor be each component tunable characteristic parameter, theoretically adjustable parameter includes fan duty coefficient, compressor characteristics system
Number, high-pressure turbine characteristic coefficient, low-pressure turbine characteristic coefficient, gas pumping coefficient and total pressure recovery coefficient and adjustable area, the application
In, the design factor of selection specifically includes that fan flow coefficient W1X, fan pressure ratio coefficient πfX, fan efficiency coefficient ηfX, calm the anger
Machine discharge coefficient W25X, compressor pressure ratio coefficient πcX, compressor efficiency coefficient ηcX, high-pressure turbine efficiency factor ηhtX, low-pressure turbine
Efficiency factor ηttX, gas pumping coefficient y after compressor stageq9, outer culvert total pressure recovery coefficient πwhX, spout throat area A8.Designer
Different test design methods can be chosen according to actual needs, in the present embodiment, which chooses optimal drawing
The design of fourth hypercube, optimal Latin hypercube design make all design factors be evenly distributed in design space as far as possible, have
It is extraordinary space filling and harmonious, it can get the higher response of nonlinear degree.By test design method to design
The factor carries out preliminary exploration, obtains the design variable being affected to Identification Errors E, specifically includes that fan flow coefficient W1X、
Spout throat area A8, compressor efficiency coefficient ηcX, fan efficiency coefficient ηfX, high-pressure turbine efficiency factor ηhtX, low-pressure turbine effect
Rate coefficient ηttXAnd compressor discharge coefficient W25X.The susceptibility of design variable analyzed, above-mentioned be affected is obtained
Effect tendency of the design variable to Identification Errors E.As the Pareto chart and Fig. 3 characteristics of components of Fig. 2 characteristics of components identified parameters are distinguished
Know the main effect figure of parameter.According to experimental design result it is found that fan flow coefficient W1XWith spout throat area A8Maximum is influenced,
Wherein fan flow coefficient W1XInfluence be positive-effect, spout throat area A8Influence be negative effect, secondly for compressor imitate
Rate coefficient ηcX, fan efficiency coefficient ηfX, high-pressure turbine efficiency factor ηhtX, low-pressure turbine efficiency factor ηttX, four parameters
Influence is negative effect, is finally compressor discharge coefficient W25X, influence for positive-effect, but test design method can not be visited automatically
The optimal design point of rope, therefore optimize on this basis.
In the optimization design module of the characteristics of components Identification Platform of the application, first according to practical problem constitution optimization mathematics
Then model optimizes mathematical model by the optimization algorithm of ISIGHT software.
In the present embodiment, the optimized mathematical model that the characteristics of components of fanjet recognizes under the conditions of ground stand test run is such as
Under:
Input condition are as follows: atmospheric temperature T0, atmospheric pressure P0, rotational speed of lower pressure turbine rotor n1；
Optimized variable are as follows: fan efficiency coefficient ηfX, compressor efficiency coefficient ηcX, high-pressure turbine efficiency factor ηhtX, low pressure
Turbine efficiency coefficient ηttX, spout throat area A8And compressor discharge coefficient W25X；
Optimization aim are as follows: Identification Errors E is minimum.
Identification Errors E are as follows:
Each measurement parameter power of test is given before optimizing by the optimization algorithm of ISIGHT software to mathematical model
Weight wi；
Wherein, m is the tractor parameter number that test measures, ytestFor test measurements, yModelFor engine mockup calculating
Value.ytestFor test measurements, indicates that the tractor parameter general measure parameter measured can be tested in engineering, chosen in the application
Measurement parameter are as follows: high pressure rotor revolving speed n2, air-flow stagnation pressure P after fan13, compressor W1Air-flow stagnation pressure P afterwards3, turbine rear exhaust it is total
Press P6, outer culvert exit flow stagnation pressure P16, total airflow temperature T after fan13/T23, total airflow temperature T after compressor3, turbine rear exhaust total temperature
T6, fan inlet flow W1, motor power F and main fuel flow Wf。
In the present embodiment, optimized mathematical model is optimized using the optimization algorithm that ISIGHT software provides, ISIGHT
A variety of optimization algorithms are provided in software, after early period is to the explorative research of a variety of optimization algorithms, comprehensively consider optimum results and
Optimization efficiency selects DS optimization algorithm.There are two configuration parameters for DS algorithm, are Simplex initial size and Optimized Iterative respectively
Maximum times, initial size indicate initially start optimizing when simplex have in design space size (0 < originate ruler
Very little≤1), when initial size is bigger, a possibility that obtaining optimal solution, is also larger.The maximum times of Optimized Iterative are integers,
Choosing value is bigger, and step needed for completing optimization is more, choosing comprehensively identification precision and optimal speed, and choosing initial size is 0.3,
The maximum times of iteration are 60.
Fanjet characteristics of components discrimination method under the conditions of the ground stand test run of the application, it is special building above-mentioned component
On the basis of property Identification Platform, fanjet characteristics of components under the conditions of ground stand test run specifically can be realized in the steps below
Identification:
Input engines ground bench test drive parameter: atmospheric temperature T0, atmospheric pressure P0, rotational speed of lower pressure turbine rotor n1；
Fan flow coefficient W is given according to test engine inlet flow rate measured value1X；
Given optimized variable value range, optimized variable includes: fan efficiency coefficient ηfX, compressor efficiency coefficient ηcX, it is high
Press turbine efficiency coefficient ηhtX, low-pressure turbine efficiency factor ηttX, spout throat area A8And compressor discharge coefficient W25X；
Given test measurement parameters weighting wi；
It is recognized by characteristics of components Identification Platform, obtains identification result.
According to above-mentioned steps, which is verified, verification result is as shown in figure 4, each parameter as we know from the figure
(high pressure rotor revolving speed n2, air-flow stagnation pressure P after fan13, compressor W1Air-flow stagnation pressure P afterwards3, turbine rear exhaust stagnation pressure P6, outer contain out
Implication stream stagnation pressure P16, total airflow temperature T after fan13/T23, total airflow temperature T after compressor3, turbine rear exhaust total temperature T6, fan inlet
Flow W1, motor power F, main fuel flow Wf, fan efficiency ηf, compressor efficiency ηc, high-pressure turbine efficiency etaht, low pressure whirlpool
Take turns efficiency etatt, spout throat area A8, compressor flow W25) identification relative error within 0.22%.
Fanjet characteristics of components discrimination method under the conditions of the ground stand test run of the application, without a large amount of test number
According to without complex mathematical algorithm research, fanjet component is special under the conditions of can rapidly and accurately realizing ground stand test run
Property identification.
The above, the only specific embodiment of the application, but the protection scope of the application is not limited thereto, it is any
Within the technical scope of the present application, any changes or substitutions that can be easily thought of by those familiar with the art, all answers
Cover within the scope of protection of this application.Therefore, the protection scope of the application should be with the scope of protection of the claims
It is quasi-.
Claims (10)
1. fanjet characteristics of components discrimination method under the conditions of a kind of ground stand test run characterized by comprising
Obtain engines ground bench test drive parameter；
Build characteristics of components Identification Platform；
The engines ground bench test drive parameter is input in the characteristics of components Identification Platform, the characteristics of components is passed through
Identification Platform is recognized, and characteristics of components identification result is obtained.
2. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 1
It is, in the acquisition engines ground bench test drive parameter, the engines ground bench test drive parameter includes: atmospheric temperature
T0, atmospheric pressure P0, rotational speed of lower pressure turbine rotor n1。
3. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 2
It is, described to build in characteristics of components Identification Platform, the characteristics of components Identification Platform is based on ISIGHT software and builds, the portion
Part characteristic Identification Platform includes: experimental design module and optimization design module.
4. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 3
It is, in the characteristics of components Identification Platform,
The experimental design of the experimental design module includes: to be made described by coordinating each design factor level in design space
Design factor meets Optimal Distribution in the design space；The design factor is analyzed, obtaining influences Identification Errors E's
The effect tendency of design variable and the design variable to Identification Errors E；
The optimization design of the optimization design module includes: constitution optimization mathematical model；Pass through the optimization algorithm of ISIGHT software
The optimized mathematical model is optimized.
5. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 4
It is, it is described horizontal by coordinating each design factor in design space, meet the design factor in the design space
The test design method of Optimal Distribution is the design of optimal Latin hypercube.
6. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 5
It is, the design factor includes: fan flow coefficient W1X, fan pressure ratio coefficient πfX, fan efficiency coefficient ηfX, compressor stream
Coefficient of discharge W25X, compressor pressure ratio coefficient πcX, compressor efficiency coefficient ηcX, high-pressure turbine efficiency factor ηhtX, low-pressure turbine efficiency
Coefficient ηttX, gas pumping coefficient y after compressor stageq9, outer culvert total pressure recovery coefficient πwhX, spout throat area A8。
7. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 6
It is, the design variable for influencing Identification Errors E includes: fan flow coefficient W1X, spout throat area A8, compressor efficiency
Coefficient ηcX, fan efficiency coefficient ηfX, high-pressure turbine efficiency factor ηhtX, low-pressure turbine efficiency factor ηttX, compressor discharge coefficient
W25X, wherein the fan flow coefficient W1XWith the compressor discharge coefficient W25XInfluence be positive-effect, the spout venturi
Area A8, the compressor efficiency coefficient ηcX, the fan efficiency coefficient ηfX, the high-pressure turbine efficiency factor ηhtXWith it is described
Low-pressure turbine efficiency factor ηttXInfluence be negative effect.
8. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 7
It is, in the constitution optimization mathematical model, the optimized mathematical model are as follows:
Input engines ground bench test drive parameter: atmospheric temperature T0, atmospheric pressure P0, rotational speed of lower pressure turbine rotor n1；
Given optimized variable value range, the optimized variable includes: fan efficiency coefficient ηfX, compressor efficiency coefficient ηcX, it is high
Press turbine efficiency coefficient ηhtX, low-pressure turbine efficiency factor ηttX, spout throat area A8And compressor discharge coefficient W25X；
Determine that optimization aim, the optimization aim are Identification Errors E minimum.
9. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 8
It is, during the optimization algorithm by ISIGHT software optimizes the optimized mathematical model, the optimization algorithm is
DS optimization algorithm.
10. fanjet characteristics of components discrimination method, feature under the conditions of ground stand test run according to claim 9
It is, the Identification Errors E are as follows:
Each measurement ginseng of test is given before the optimization algorithm by ISIGHT software optimizes the mathematical model
Number weight wi；
Wherein, m is the tractor parameter number that test measures, ytestFor test measurements, yModelFor engine mockup calculated value.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2013149518A (en) * | 2013-11-07 | 2015-05-20 | Открытое Акционерное Общество "Уфимское Моторостроительное Производственное Объединение" (Оао "Умпо") | METHOD FOR TESTING AN EXPERIENCED GAS TURBINE ENGINE |
| CN108106849A (en) * | 2017-12-14 | 2018-06-01 | 中国航发沈阳发动机研究所 | A kind of fanjet component feature parameter identification method |
| CN108647428A (en) * | 2018-05-08 | 2018-10-12 | 南京航空航天大学 | A kind of fanjet self-adaptive component grade simulation model construction method |
-
2019
- 2019-05-17 CN CN201910410442.6A patent/CN110175383A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2013149518A (en) * | 2013-11-07 | 2015-05-20 | Открытое Акционерное Общество "Уфимское Моторостроительное Производственное Объединение" (Оао "Умпо") | METHOD FOR TESTING AN EXPERIENCED GAS TURBINE ENGINE |
| CN108106849A (en) * | 2017-12-14 | 2018-06-01 | 中国航发沈阳发动机研究所 | A kind of fanjet component feature parameter identification method |
| CN108647428A (en) * | 2018-05-08 | 2018-10-12 | 南京航空航天大学 | A kind of fanjet self-adaptive component grade simulation model construction method |
Non-Patent Citations (3)
| Title |
|---|
| 唐兰等: "基于ISIGHT软件的地面台架试车条件下涡扇发动机部件特性辨识方法", 《航空发动机》 * |
| 王军等: "整机条件下涡扇发动机部件特征参数辨识", 《航空动力学报》 * |
| 陈玉春 等: "《涡扇发动机特性仿真中的Zooming技术研究》", 《计算机仿真》 * |
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Application publication date: 20190827 |