DocumentCode :
3516748
Title :
Multi Source Data Integration for Aircraft Health Management
Author :
Ortiz, Estefan M. ; Clark, Gregory J. ; Babbar, Ashish ; Vian, John L. ; Syrmos, Vassilis L. ; Arita, Michael M.
Author_Institution :
Univ. of Hawaii, Honolulu, HI
fYear :
2008
fDate :
1-8 March 2008
Firstpage :
1
Lastpage :
12
Abstract :
Modern aircraft are capable of generating and collecting massive quantities of data from flight recorders, maintenance reports, logistics, and mission-readiness reporting systems. Current aircraft system health management schemes are developed based on data sources consisting of the aircraft´s system operational conditions or maintenance and repair actions; however, crucial information regarding flight condition and situational parameters are often disregarded or used in a limited sense for diagnostics due to data accessibility issues or what can be an overwhelming volume of time-series data that is collected from modern onboard aircraft data recorders. With improved access to multiple sources of aircraft data, diagnostics and prognostics capabilities may be improved allowing flight crews, engineering, maintenance, and logistics users of an interoperable data system to make more informed decisions. Improved knowledge of the actual aircraft condition, usage and component life monitoring can significantly reduce aircraft operations and support (O&S) costs. In addition, integrating multiple sources of aircraft data can reduce total ownership cost (TOC), enhance mission safety and improve aircraft performance. There is a need to develop a multi-source data integration architecture for analyzing vast quantities of disparate data obtained from both onboard and off-board data sources. The multi-source data integration will be able to accurately combine disparate data and establish interconnectivity between distinct data sources to significantly improve data interoperability across multiple data sources. This type of information fusion can serve as the basis for developing advanced diagnostic and prognostic algorithms for legacy, current, and next- generation commercial and military aircraft.
Keywords :
aerospace computing; aircraft maintenance; computerised monitoring; condition monitoring; data analysis; aircraft system health management; data accessibility; data interoperability; flight condition; mission safety; multi source data integration; total ownership cost; Aerospace engineering; Air safety; Aircraft propulsion; Condition monitoring; Costs; Data engineering; Data systems; Fusion power generation; Health information management; Logistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Aerospace Conference, 2008 IEEE
Conference_Location :
Big Sky, MT
ISSN :
1095-323X
Print_ISBN :
978-1-4244-1487-1
Electronic_ISBN :
1095-323X
Type :
conf
DOI :
10.1109/AERO.2008.4526625
Filename :
4526625
Link To Document :
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