학술논문

Bayesian belief networks for fault identification in aircraft gas turbine engines
Document Type
Conference
Source
Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328) Control applications Control Applications, 1999. Proceedings of the 1999 IEEE International Conference on. 1:39-44 vol. 1 1999
Subject
Robotics and Control Systems
Components, Circuits, Devices and Systems
Bayesian methods
Fault diagnosis
Intelligent networks
Aircraft propulsion
Turbines
Uncertainty
Random variables
Fault detection
Jet engines
Data analysis
Language
Abstract
Describes the methodology for usage of Bayesian belief networks (BBNs) in fault detection for aircraft gas turbine engines. First, the basic theory of BBNs is discussed, followed by a discussion on the application of this theory to a specific engine. In particular, the selection of faults and the means by which operating regions for the BBN system are chosen are analyzed. This methodology is then illustrated using the GE CFM56-7 turbofan engine as an example.