Aircraft gas turbine engine blade tip clearance control
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06F-019/00
G06G-007/70
출원번호
US-0833596
(2007-08-03)
등록번호
US-8126628
(2012-02-28)
발명자
/ 주소
Hershey, John Erik
Osborn, Brock Estel
Gardner, Donald Lee
Ruiz, Rafael Jose
Herron, William Lee
출원인 / 주소
General Electric Company
대리인 / 주소
Andes, William Scott
인용정보
피인용 횟수 :
13인용 특허 :
19
초록▼
A method and system adjusts blade tip clearance between rotating aircraft gas turbine engine blade tips and a surrounding shroud in anticipation of and before an engine command that changes an engine rotational speed. The method may include determining when to begin adjusting the tip clearance by ex
A method and system adjusts blade tip clearance between rotating aircraft gas turbine engine blade tips and a surrounding shroud in anticipation of and before an engine command that changes an engine rotational speed. The method may include determining when to begin adjusting the tip clearance by expanding or contracting the shroud before the engine command and may be based on monitored aircraft and/or aircraft crew data indicative of the engine. The aircraft and/or aircraft crew data may include communications between aircraft crew and air traffic control authorities or air traffic control surrogates. Determining when to begin adjusting the tip clearance may include using learning algorithms which may use the aircraft gas turbine engine's operating experience and/or operating experience of other jet engines on an aircraft containing the aircraft gas turbine engine and/or on other aircraft.
대표청구항▼
1. A method to adjust blade tip clearance between rotating blade tips and a surrounding shroud in an aircraft gas turbine engine in flight, the method comprising: monitoring aircraft and aircraft crew data with a controller wherein the aircraft crew data includes communications between aircraft crew
1. A method to adjust blade tip clearance between rotating blade tips and a surrounding shroud in an aircraft gas turbine engine in flight, the method comprising: monitoring aircraft and aircraft crew data with a controller wherein the aircraft crew data includes communications between aircraft crew and air traffic control authorities or air traffic control surrogates,automatically changing the tip clearance in anticipation of and before an engine command that changes an engine rotational speed, andchanging of the tip clearance based on at least one of the monitored data. 2. The method as claimed in claim 1 further comprising the engine command being changing fuel flow to the engine. 3. The method as claimed in claim 1 further comprising determining when to begin adjusting the tip clearance by expanding or contracting the shroud by blowing or impinging thermal control air on thermal control rings or a turbine casing supporting the stator shroud a period of time before the engine command that changes the engine rotational speed. 4. The method as claimed in claim 3 further comprising modifying when to begin adjusting the tip clearance by using learning algorithms. 5. The method as claimed in claim 4 further comprising using the aircraft gas turbine engine's operating experience and/or operating experience of other jet engines for the learning algorithms. 6. The method as claimed in claim 5 further comprising the other jet engines being on an aircraft containing the aircraft gas turbine engine and/or on other aircraft. 7. The method as claimed in claim 3 further comprising using a statistical method for determining when to begin adjusting the tip clearance. 8. The method as claimed in claim 7 wherein the statistical method for determining when to begin adjusting the tip clearance is selected from a group consisting of statistical methods, correlation methods, multivariate statistical process analysis, and pattern recognition methods. 9. The method as claimed in claim 7 further comprising the statistical method for determining when to begin adjusting the tip clearance being a pattern recognition method selected from a group consisting of Bayesian decision theory, neural networks, fuzzy logic, Parzen windows, nearest neighbor classification, hidden Markov models, linear and non-linear discriminant analysis, Markov random fields, Boltzmann learning, classification and regression trees, and multivariate adaptive regression. 10. The method as claimed in claim 1 further comprising overriding an active clearance control flow model used to schedule desired blade tip clearance with the changing of the tip clearance in anticipation of and before an engine command that changes an engine rotational speed. 11. The method as claimed in claim 10 further comprising determining when to begin adjusting the tip clearance by expanding or contracting the shroud by blowing or impinging thermal control air on thermal control rings or a turbine casing supporting the stator shroud a period of time before the engine command that changes then engine rotational speed. 12. The method as claimed in claim 11 further comprising modifying when to begin adjusting the tip clearance by using learning algorithms. 13. The method as claimed in claim 12 further comprising using the aircraft gas turbine engine's operating experience and/or operating experience of other jet engines for the learning algorithms. 14. The method as claimed in claim 13 further comprising the other jet engines being on an aircraft containing the aircraft gas turbine engine and/or on other aircraft. 15. The method as claimed in claim 11 further comprising using a statistical method for determining when to begin adjusting the tip clearance. 16. The method as claimed in claim 15 wherein the statistical method for determining when to begin adjusting the tip clearance is selected from a group consisting of statistical methods, correlation methods, multivariate statistical process analysis, and pattern recognition methods. 17. The method as claimed in claim 15 further comprising the statistical method for determining when to begin adjusting the tip clearance being a pattern recognition method selected from a group consisting of Bayesian decision theory, neural networks, fuzzy logic, Parzen windows, nearest neighbor classification, hidden Markov models, linear and non-linear discriminant analysis, Markov random fields, Boltzmann learning, classification and regression trees, and multivariate adaptive regression. 18. The method as claimed in claim 1 further comprising determining when to begin adjusting the tip clearance by expanding the shroud by blowing or impinging thermal control air on thermal control rings or a turbine casing supporting the stator shroud a period of time before an engine command associated with climb. 19. The method as claimed in claim 18 further comprising using a statistical method for determining when to begin adjusting the tip clearance. 20. The method as claimed in claim 19 further comprising using historical data from the engine in the statistical method for determining when to begin adjusting the tip clearance. 21. The method as claimed in claim 20 wherein the statistical method for determining when to begin adjusting the tip clearance is selected from a group consisting of statistical methods, correlation methods, multivariate statistical process analysis, and pattern recognition methods. 22. The method as claimed in claim 20 further comprising the statistical method for determining when to begin adjusting the tip clearance being a pattern recognition method selected from a group consisting of Bayesian decision theory, neural networks, fuzzy logic, Parzen windows, nearest neighbor classification, hidden Markov models, linear and non-linear discriminant analysis, Markov random fields, Boltzmann learning, classification and regression trees, and multivariate adaptive regression. 23. The method as claimed in claim 20 further comprising using aircraft and aircraft crew data indicative of the engine command in historical data. 24. The method as claimed in claim 23 further comprising the aircraft and aircraft crew data indicative of the engine command in historical data including communications between aircraft crew and air traffic control authorities or air traffic control surrogates. 25. The method as claimed in claim 1 further comprising changing the tip clearance by blowing or impinging thermal control air on structure supporting the shroud in anticipation of and before an engine command that changes an engine rotational speed. 26. The method as claimed in claim 25 further comprising monitoring aircraft and aircraft crew data indicative of the engine command and changing the tip clearance based on the monitored aircraft and aircraft crew data. 27. The method as claimed in claim 26 further comprising the aircraft and aircraft crew data indicative of the engine command in historical data including communications between aircraft crew and air traffic control authorities or air traffic control surrogates. 28. The method as claimed in claim 25 further comprising the engine command being changing fuel flow to the engine. 29. The method as claimed in claim 25 further comprising determining when to begin adjusting the tip clearance by expanding or contracting the shroud a period of time before the engine command that changes the engine rotational speed. 30. The method as claimed in claim 29 further comprising modifying when to begin adjusting the tip clearance by using learning algorithms. 31. The method as claimed in claim 30 further comprising using the aircraft gas turbine engine's operating experience and/or operating experience of other jet engines for the learning algorithms. 32. The method as claimed in claim 31 further comprising the other jet engines being on an aircraft containing the aircraft gas turbine engine and/or on other aircraft. 33. The method as claimed in claim 29 further comprising using a statistical method for determining when to begin adjusting the tip clearance wherein the statistical method for determining when to begin adjusting the tip clearance is selected from a group consisting of statistical methods, correlation methods, multivariate statistical process analysis, and pattern recognition methods. 34. The method as claimed in claim 29 further comprising using a statistical method for determining when to begin adjusting the tip clearance wherein the statistical method for determining when to begin adjusting the tip clearance being a pattern recognition method selected from a group consisting of Bayesian decision theory, neural networks, fuzzy logic, Parzen windows, nearest neighbor classification, hidden Markov models, linear and non-linear discriminant analysis, Markov random fields, Boltzmann learning, classification and regression trees, and multivariate adaptive regression. 35. The method as claimed in claim 25 further comprising overriding an active clearance control flow model used to schedule desired blade tip clearance with the changing of the tip clearance in anticipation of and before an engine command that changes an engine rotational speed. 36. The method as claimed in claim 25 further comprising determining when to begin adjusting the tip clearance by expanding the shroud a period of time before an engine command associated with climb.
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이 특허에 인용된 특허 (19)
Davison Samuel H. (Loveland OH) Kast Kevin H. (Cincinnati OH) Clark Aidan W. (Blue Ash OH), Active clearance control.
Walker Roger C. (Fairfield OH) Reese Scott P. (West Chester OH) Joyce David L. (Middletown OH) Kastrup David A. (Cincinnati OH), Active clearance control for gas turbine engine.
Schwarz Fred M. (Glastonbury CT) Crawley ; Jr. Clifton J. (Glastonbury CT) Rauseo Anthony F. (Middletown CT) Lagueux Ken R. (Berlin CT), Active clearance control with cruise mode.
Schwarz Fred M. (Glastonbury CT) Crawley ; Jr. Clifton J. (Glastonbury CT) Rausco Anthony (Middletown CT) Lagueux Ken R. (Berlin CT), Clearance control method for gas turbine engine.
Plemmons Larry W. (Fairfield OH) Proctor Robert (West Chester OH) Albers Robert J. (Park Hills KY) Gardner Donald L. (West Chester OH), Gas turbine engine case counterflow thermal control.
Schwarz Frederick M. (Glastonbury CT) Crawley ; Jr. Clifton J. (Glastonbury CT) Rauseo Anthony F. (Middletown CT), Method of restoring exhaust gas temperature margin in a gas turbine engine.
Boris Karpman ; John L. Shade ; Daniel E. Kane, System and method of controlling clearance between turbine engine blades and case based on engine components thermal growth model.
Suzuki, Hideaki; Furuno, Yoshinori; Araki, Kenji; Nakamura, Kozo; Yuda, Shinya; Takahashi, Hirotaka, Learning diagnostic system, state diagnostic device, and state learning device for working machine.
Donovan, John J; Hussain, Daniar, Systems and methods for correlating data from IP sensor networks for security, safety, and business productivity applications.
Donovan, John J; Hussain, Daniar, Systems and methods for correlating sensory events and legacy system events utilizing a correlation engine for security, safety, and business productivity.
Donovan, John J; Hussain, Daniar, Systems, methods, and apparatus for monitoring and alerting on large sensory data sets for improved safety, security, and business productivity.
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