Author: Patrick C. Murphy
Publisher:
ISBN:
Category : Aerodynamics
Languages : en
Pages : 66
Book Description
A Methodology for Airplane Parameter Estimation and Confidence Interval Determination in Nonlinear Estimation Problems
Author: Patrick C. Murphy
Publisher:
ISBN:
Category : Aerodynamics
Languages : en
Pages : 66
Book Description
Publisher:
ISBN:
Category : Aerodynamics
Languages : en
Pages : 66
Book Description
NASA Reference Publication
Scientific and Technical Aerospace Reports
NASA Scientific and Technical Publications
Scientific and Technical Information Output of the Langley Research Center for Calendar Year 1986
Author: Langley Research Center. Research Information and Applications Division
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 270
Book Description
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 270
Book Description
NASA SP.
The Aeronautical Journal
A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics
Author: Takahisa Kobayashi
Publisher:
ISBN:
Category :
Languages : en
Pages : 18
Book Description
In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.
Publisher:
ISBN:
Category :
Languages : en
Pages : 18
Book Description
In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.
AGARD Conference Proceedings
Author: North Atlantic Treaty Organization. Advisory Group for Aerospace Research and Development
Publisher:
ISBN:
Category : Aerodynamics
Languages : en
Pages : 296
Book Description
Publisher:
ISBN:
Category : Aerodynamics
Languages : en
Pages : 296
Book Description
Aeronautical Engineering
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 712
Book Description
A selection of annotated references to unclassified reports and journal articles that were introduced into the NASA scientific and technical information system and announced in Scientific and technical aerospace reports (STAR) and International aerospace abstracts (IAA)
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 712
Book Description
A selection of annotated references to unclassified reports and journal articles that were introduced into the NASA scientific and technical information system and announced in Scientific and technical aerospace reports (STAR) and International aerospace abstracts (IAA)