Modern military and commercial aircraft require advanced diagnostic and prognostic schemes to determine engine performance in order to reduce operational and maintenance costs and improve aircraft down time. Condition Based Maintenance (CBM) can be performed on an aircraft when a fault/failure is detected. However, to streamline maintenance procedures and avoid unnecessary delays the engineers and maintainers need current and best estimates of engine performance and health before upcoming flights.Using flight condition data and situational parameters, diagnostic and prognostic schemes can be developed which help in determining engine behavior during a specific flight and predict engine performance by estimating the flight parameter conditions of future flights. This approach can provide several key benefits including:Reducing unnecessary maintenance actions and prioritize maintenance procedures based on system conditions.Increasing mission readiness and airworthiness. Improving aircraft safety.

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Modem 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 modem 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 nextgeneration commercial and military aircraft.1 23 1 1 1-4244-1488-

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