A Novel Gas Turbine Engine Health Status Estimation Method Using Quantum-Behaved Particle Swarm Optimization
Joint Authors
Yang, Xinyi
Shen, Wei
Jiang, Keyi
Li, Benwei
Wang, Yonghua
Pang, Shan
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-06
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Accurate gas turbine engine health status estimation is very important for engine applications and aircraft flight safety.
Due to the fact that there are many to-be-estimated parameters, engine health status estimation is a very difficult optimization problem.
Traditional gas path analysis (GPA) methods are based on the linearized thermodynamic engine performance model, and the estimation accuracy is not satisfactory on conditions that the nonlinearity of the engine model is significant.
To solve this problem, a novel gas turbine engine health status estimation method has been developed.
The method estimates degraded engine component parameters using quantum-behaved particle swarm optimization (QPSO) algorithm.
And the engine health indices are calculated using these estimated component parameters.
The new method was applied to turbine fan engine health status estimation and is compared with the other three representative methods.
Results show that although the developed method is slower in computation speed than GPA methods it succeeds in estimating engine health status with the highest accuracy in all test cases and is proven to be a very suitable tool for off-line engine health status estimation.
American Psychological Association (APA)
Yang, Xinyi& Shen, Wei& Pang, Shan& Li, Benwei& Jiang, Keyi& Wang, Yonghua. 2014. A Novel Gas Turbine Engine Health Status Estimation Method Using Quantum-Behaved Particle Swarm Optimization. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-461693
Modern Language Association (MLA)
Yang, Xinyi…[et al.]. A Novel Gas Turbine Engine Health Status Estimation Method Using Quantum-Behaved Particle Swarm Optimization. Mathematical Problems in Engineering No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-461693
American Medical Association (AMA)
Yang, Xinyi& Shen, Wei& Pang, Shan& Li, Benwei& Jiang, Keyi& Wang, Yonghua. A Novel Gas Turbine Engine Health Status Estimation Method Using Quantum-Behaved Particle Swarm Optimization. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-461693
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-461693