DocumentCode
3442295
Title
The information-enhanced fault diagnosis system design of avionics power supply module
Author
Fuchao Song ; Wenkui Hou ; Long Shi
Author_Institution
Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China
fYear
2013
fDate
15-18 July 2013
Firstpage
1758
Lastpage
1761
Abstract
This paper is based on the engineering requirements of intelligent fault diagnosis technology, and designes the information-enhanced fault diagnosis system for avionics power supply module. Firstly, we designed the framework of the system, gave the information that needed for fault diagnosis and the way to get it. Then, the fuzzy neural network model was established which combines the neural network model with the fuzzy diagnostic model. Based on this, we designed the fault diagnosis hardware platform with detection chip and data acquisition function, and the software to control it. This paper provides a strong support for the research of avionics embedded intelligent diagnosis method. This paper is helpful for designing the embedded diagnostic reasoning of prognostic and health management system.
Keywords
aircraft power systems; avionics; computerised monitoring; data acquisition; embedded systems; fault diagnosis; fuzzy neural nets; power supplies to apparatus; avionics power supply module design; data acquisition function; detection chip; embedded diagnostic reasoning; engineering requirement; fault diagnosis hardware platform; fuzzy neural network model; health management system; information enhanced fault diagnosis system; intelligent fault diagnosis technology; prognostic; Aerospace electronics; Fault diagnosis; Fuzzy neural networks; Power supplies; Temperature measurement; Temperature sensors; Training; fault diagnosis; fuzzy neural network; information-enhanced; power supply module;
fLanguage
English
Publisher
ieee
Conference_Titel
Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-1014-4
Type
conf
DOI
10.1109/QR2MSE.2013.6625916
Filename
6625916
Link To Document