DocumentCode :
677012
Title :
Neural network based architecture for fault detection and isolation in air data systems
Author :
Garbarino, Luca ; Zazzaro, Gaetano ; Genito, Nicola ; Fasano, Giancarmine ; Accardo, Domenico
Author_Institution :
Italian Aerospace Research Center (CIRA), Italy
fYear :
2013
fDate :
5-10 Oct. 2013
Firstpage :
1
Lastpage :
28
Abstract :
❖ A FDI architecture for Air Data Systems measurements based on Artificial Neural Network was presented. ❖ CRISP-DM process was applied to flight data to find the optimal set for the design and test of the Artificial Neural Network. ❖ Different ANNs were designed to ensure a fault tolerant FDI architecture ❖ Experimental results for Indicated Airspeed and Angle of Attack were presented (the architecture was applied also for True Airspeed and Angle of sideslip). ❖ The system was success fully tested on a very light aircraft, whereas the software architecture can be reused for air data systems designed for other classes of aircraft.
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Avionics Systems Conference (DASC), 2013 IEEE/AIAA 32nd
Conference_Location :
East Syracuse, NY, USA
ISSN :
2155-7195
Print_ISBN :
978-1-4799-1536-1
Type :
conf
DOI :
10.1109/DASC.2013.6719624
Filename :
6719624
Link To Document :
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