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CN-122020942-A - Turbine blade tip clearance real-time prediction method, prediction system, storage medium and computer program product

CN122020942ACN 122020942 ACN122020942 ACN 122020942ACN-122020942-A

Abstract

The invention provides a real-time prediction method, a prediction system, a storage medium and a computer program product for turbine blade tip clearance. The method for predicting the turbine blade tip clearance in real time comprises the steps of obtaining overall performance parameters of an engine, establishing a component heat transfer model of the engine, inputting the overall performance parameters of the engine into the component heat transfer model to obtain real-time average temperature of components, establishing a component deformation model of the engine, inputting the real-time average temperature of the components into the component deformation model to obtain component deformation, and obtaining the turbine blade tip clearance in real time according to the component deformation. The real-time prediction method can rapidly and accurately predict the turbine blade tip clearance.

Inventors

  • TANG YUQING
  • Lv Lulu
  • SUI DONGYU
  • GU WEI
  • Zhou Shuangzhao

Assignees

  • 中国航发商用航空发动机有限责任公司

Dates

Publication Date
20260512
Application Date
20241112

Claims (17)

  1. 1. A method for real-time prediction of turbine tip clearance, comprising: acquiring the overall performance parameters of the engine; establishing a component heat transfer model of an engine, and inputting the overall performance parameters of the engine into the component heat transfer model to obtain the real-time average temperature of the component; Establishing a component deformation model of the engine, and inputting the real-time average temperature of the component into the component deformation model to obtain the component deformation; And obtaining the real-time turbine blade tip clearance according to the deformation of the component.
  2. 2. The real-time prediction method according to claim 1, wherein the engine overall performance parameters include a combination of one or more of turbine inlet flow, turbine inlet total temperature, compressor outlet total temperature, engine speed, outer casing cooling flow, and outer casing cooling gas temperature.
  3. 3. The method of real-time prediction according to claim 2, wherein said creating a component heat transfer model of an engine, inputting said engine overall performance parameters into said component heat transfer model to obtain a component real-time temperature, comprises: Establishing a heat exchange boundary calculation module, and inputting at least one parameter of the overall performance parameters of the engine into the heat exchange boundary calculation module to obtain a convection heat exchange coefficient of a component and a heat exchange boundary loading temperature; And establishing a transient temperature calculation module, and inputting the convection heat transfer coefficient and the heat transfer boundary loading temperature of the component into the transient temperature calculation module to obtain the real-time average temperature of the component.
  4. 4. A real-time prediction method according to claim 3, wherein the heat exchange boundary calculation module is configured to: Dividing the component into a plurality of heat transfer nodes, and setting a plurality of heat exchange boundaries for each heat transfer node; And converting each heat exchange boundary of each heat transfer node by taking the heat exchange boundary of the reference working condition as a reference to obtain a convection heat exchange coefficient of the component and a loading temperature of the heat exchange boundary.
  5. 5. The real-time predictive method as set forth in claim 4, wherein said heat exchange boundary loading temperature of a component is obtained according to the relationship: Wherein k is a conversion constant, T is the loading temperature of the heat exchange boundary, T cold is the cold air temperature of the engine cold source side at the position of the heat exchange boundary, T hot is the hot air temperature of the engine heat source side at the position of the heat exchange boundary, T ref is the loading temperature of the reference boundary corresponding to the position of the heat exchange boundary under the reference working condition, T cold_ref is the cold air temperature of the engine cold source side under the reference working condition of the position of the heat exchange boundary, and T hot_ref is the hot air temperature of the engine heat source side under the reference working condition of the position of the heat exchange boundary.
  6. 6. The real-time prediction method according to claim 5, wherein the convective heat transfer coefficient of a component is obtained according to the following relation: Wherein h is the convection heat transfer coefficient, h ref is the convection heat transfer coefficient of the reference boundary corresponding to the position of the heat transfer boundary under the reference working condition, W is the main flow or the cold flow, W ref is the main flow or the cold flow of the reference boundary corresponding to the heat transfer boundary under the reference working condition, T is the loading temperature of the heat transfer boundary, T ref is the loading temperature of the reference boundary corresponding to the position of the heat transfer boundary under the reference working condition, and a and b are constants.
  7. 7. The real-time prediction method according to any one of claims 3 to 6, characterized in that the real-time prediction method further comprises: Correcting the convective heat transfer coefficient to obtain a corrected convective heat transfer coefficient, wherein the corrected convective heat transfer coefficient meets the following conditions: h i ＝k i h i_th Wherein h i_th is a theoretical convective heat transfer coefficient of a certain heat transfer boundary, k i is a correction coefficient, and h i is the corrected convective heat transfer coefficient.
  8. 8. The real-time prediction method according to claim 3, wherein the transient temperature calculation module is configured to: determining the section of each heat transfer node for convective heat transfer with the airflow according to the heat transfer nodes of which the components are divided; establishing a heat transfer equation by combining each heat transfer node and the section to obtain the temperature of each heat transfer node; and obtaining the average temperature of each heat transfer node in the component according to the temperature of each heat transfer node, and taking the average temperature as the real-time average temperature of the component.
  9. 9. The real-time prediction method according to claim 8, wherein when the component is divided into two heat transfer nodes, the heat transfer equation is: Wherein T Rnode1 and T Rnode2 are temperatures of heat transfer nodes when the component is divided into two heat transfer nodes, K is a heat conduction or contact heat transfer coefficient between every two adjacent heat transfer nodes, h is a convection heat transfer coefficient, A, ρ and V, c p are heat exchange areas, material densities, node volumes and constant-pressure specific heat of materials respectively, subscripts Rnode and Rnode2 represent the heat transfer nodes of the component respectively, and subscripts 10-23 represent different heat exchange surfaces.
  10. 10. The method for predicting in real time according to claim 2, wherein said creating a component deformation model of the engine, inputting said component real-time average temperature into said component deformation model, obtaining a component deformation amount, comprises: A thermal deformation calculation module is established, and the real-time average temperature of the component is input into the thermal deformation calculation module to obtain the thermal deformation amount of the component; and establishing a centrifugal deformation calculation module, and inputting the engine rotating speed into the centrifugal deformation calculation module to obtain the centrifugal deformation of the component.
  11. 11. The real-time prediction method according to claim 10, wherein the thermal deformation amount of the member is obtained according to the following relation: dL exp an ＝α×R 0 ×(T-T 0 ) Wherein dL exp an is the thermal deformation of the component, alpha is the thermal expansion coefficient of the material, R 0 is the cold radial height or width of the component, T is the real-time average temperature of the component, T 0 is the cold temperature of the component at normal temperature, and/or The centrifugal deformation of the component is obtained according to the following relation: dL centri ＝f(R,E,v,ρ)·NH 2 dL centri is the centrifugal deformation of the component, R is the radial height of the component, E is the Young's modulus of the material, v is the Poisson's ratio of the material, ρ is the density of the material, and NH is the engine speed.
  12. 12. The real-time prediction method according to claim 10 or 11, wherein the component real-time average temperature includes a turbine disk real-time average temperature, a blade real-time average temperature, and a casing real-time average temperature, the component thermal deformation includes a turbine disk thermal deformation, a blade thermal deformation, and a casing thermal deformation, and the component centrifugal deformation includes a turbine disk centrifugal deformation and a blade centrifugal deformation; The method for establishing the component deformation model of the engine, inputting the real-time average temperature of the component into the component deformation model to obtain the component deformation amount, and further comprises the following steps: Obtaining the deformation of the turbine disc according to the thermal deformation of the turbine disc and the centrifugal deformation of the turbine disc; obtaining the deformation of the blade according to the thermal deformation of the blade and the centrifugal deformation of the blade; obtaining a case deformation amount according to the case thermal deformation amount, wherein the turbine disc deformation amount, the blade deformation amount and the case deformation amount satisfy the following conditions: dL_Rotor=dL rotor_exp an +dL rotor_centri dL_Blade=dL blade_exp an +dL blade_centri dL_Case=dL case_exp an The dL_Case is the deformation of the casing, the dL_Rotor is the deformation of the turbine disc, the dL_Blade is the deformation of the blades, the dL rotor_exp an is the deformation of the turbine disc, the dL rotor_centri is the centrifugal deformation of the turbine disc, the dL blade_exp an is the deformation of the blades, the dL blade_centri is the centrifugal deformation of the blades, and the dL case_exp an is the deformation of the casing.
  13. 13. The real-time prediction method according to claim 12, wherein said deriving real-time turbine tip clearance from said component deformation comprises: acquiring a cold turbine blade tip clearance; obtaining a real-time turbine blade tip gap according to the cold turbine blade tip gap, the turbine disc deformation, the blade deformation and the casing deformation, wherein the real-time turbine blade tip gap meets the following conditions: C tip ＝C tip_0 +dL_Case-dL_Rotor-dL_Blade wherein, C tip is the real-time turbine Blade tip clearance, C tip_0 is the cold state turbine Blade tip clearance, dL_Case is the casing deflection, dL_rotor is the turbine disk deflection, dL_blade is the Blade deflection.
  14. 14. The real-time prediction method according to claim 13, wherein the real-time prediction method further comprises: Correcting the real-time turbine blade tip clearance to obtain corrected real-time turbine blade tip clearance, wherein the corrected real-time turbine blade tip clearance meets the following conditions: C tip (t)＝C tip_0 +[K case_e dL case_exp an -(K rotor_e dL rotor_exp an +K rotor_c dL rotor_centri )-(K blade_e dL blade_exp an +K blade_c dL blade_centri ) Wherein, C tip (t) is the real-time turbine blade tip clearance after correction, K case_e is the thermal expansion correction parameter of the casing, K rotor_e is the thermal deformation correction parameter of the turbine disk, K rotor_c is the centrifugal deformation correction parameter of the turbine disk, K blade_e is the thermal deformation correction parameter of the blade, and K blade_c is the centrifugal deformation correction parameter of the blade.
  15. 15. A real-time prediction system for turbine blade tip clearances comprises a processor and a memory; The memory having stored thereon non-transitory computer instructions which, when executed by the processor, perform the method of real-time prediction of turbine tip clearance of any of claims 1-14.
  16. 16. A storage medium storing non-transitory computer instructions that, when executed, perform the steps of the turbine blade tip clearance real-time prediction method of any one of claims 1-14.
  17. 17. A computer program product comprising a computer program which, when executed by a processor, implements the steps of the turbine blade tip clearance real-time prediction method as claimed in any one of claims 1 to 14.

Description

Turbine blade tip clearance real-time prediction method, prediction system, storage medium and computer program product Technical Field The present invention relates to turbine active clearance control systems, and more particularly, to a method, system, storage medium and computer program product for real-time prediction of turbine tip clearance. Background Engine turbine blade tip clearance refers to the distance between the tips of the engine turbine blades to the turbine outer ring. The blade tip clearance is increased, the leakage amount of the blade tip of the turbine is increased, the turbine efficiency is reduced, and the risk of blade collision and grinding exists when the blade tip clearance is too small. Therefore, the real-time tip clearance of the engine needs to be obtained so as to control the engine to reach the optimal state on the premise of ensuring the safety of the turbine. In order to acquire the turbine blade tip clearance change rule, the control rule design and the real-time control of the turbine blade tip clearance control system are carried out, and a calculation method is required to be established to acquire the turbine blade tip clearance states of the engine in different states. The existing blade tip clearance prediction technology mostly adopts a table look-up method or a real-time simulation method. The method for searching the table adopts test or finite element calculation to accumulate offline data, and interpolates based on real-time engine performance parameters to acquire real-time data. The real-time simulation method is used for dividing the turbine into three computing nodes of a turbine disc, blades and a casing, fitting the real-time steady-state temperature or steady-state deformation of each node according to the overall performance parameters, and computing a time constant, so that the transient change process of the turbine blade tip clearance is simulated. However, the two modes essentially simplify the deformation process of the engine part caused by temperature change and centrifugal force change to be a fitting process of a mathematical curve, lack of basic physical principle support, on one hand, the difference of heat exchange conditions in different states cannot be accurately captured, the prediction accuracy is limited, on the other hand, a large amount of test or calculation data are required to be accumulated to explore the change rule of steady-state temperature (deformation) and time constant, and the unverified state is difficult to extrapolate. Disclosure of Invention The invention aims to provide a real-time prediction method, a prediction system, a storage medium and a computer program product for turbine blade tip clearance, which can rapidly and accurately predict the turbine blade tip clearance. One aspect of the invention provides a method for predicting turbine blade tip clearance in real time, comprising the steps of obtaining overall performance parameters of an engine; the method comprises the steps of establishing a component heat transfer model of an engine, inputting the overall performance parameters of the engine into the component heat transfer model to obtain a real-time average temperature of a component, establishing a component deformation model of the engine, inputting the real-time average temperature of the component into the component deformation model to obtain a component deformation, and obtaining a real-time turbine blade tip gap according to the component deformation. In an embodiment, the engine overall performance parameters include a combination of one or more of turbine inlet flow, turbine inlet total temperature, compressor outlet total temperature, engine speed, outer casing cooling flow, and outer casing cooling gas temperature. In an embodiment, the method for establishing the component heat transfer model of the engine and inputting the overall performance parameters of the engine into the component heat transfer model to obtain the real-time component temperature comprises the steps of establishing a heat exchange boundary calculation module, inputting at least one parameter of the overall performance parameters of the engine into the heat exchange boundary calculation module to obtain a convection heat exchange coefficient and a heat exchange boundary loading temperature of the component, and establishing a transient temperature calculation module, and inputting the convection heat exchange coefficient and the heat exchange boundary loading temperature of the component into the transient temperature calculation module to obtain the real-time average component temperature. In an embodiment, the heat exchange boundary calculation module is configured to divide a component into a plurality of heat transfer nodes, set a plurality of heat exchange boundaries for each heat transfer node, and convert each heat exchange boundary of each heat transfer node with a reference working condition heat exchange boundary