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A key technological concept for producing reliable engine diagnostics and prognostics exploits the benefits of fusing sensor data, information, and/or processing algorithms. In this paper, we consider a real-time physics based model of a commercial turbofan engine called STORM: self tuning on-board, real-time engine model. The STORM system provides a means for tracking engine module performance changes...
Accurate usage information collected by health and usage monitoring systems (HUMS) coupled with improved structural fatigue life calculation methodologies promise to reduce helicopter operational and support costs while maintaining current flight safety levels. Current fatigue life calculations assume worst-case flight profiles in determining component life. This approach may be outdated or not reflective...
Condition-based maintenance (CBM) of complex military vehicles or industrial machines presumes the capability to correctly detect faults in components or subsystems. Faults are malfunctions that are observed in the monitoring system. Two types of errors can occur during automated fault detection: (1) missed detections or (2) false alarms. The practical consequence of either type of error is that a...
The Air Force is developing a wide variety of technologies for aircraft propulsion system health management (PHM). Unfortunately, many promising new sensor technologies and new algorithms cannot easily be deployed for on-wing demonstration particularly for UAV health monitoring and control applications. We are developing a generic hardware and software system to support the creation and fielding of...
The current evolution in on-board Propulsion Health Management (PHM) systems aimed at performing real-time engine diagnostics and prognostics has placed a greater demand on model accuracy and implementation speed. The complexities in assembling accurate physics based models for real-time operation has placed greater focus on the use of hybrid engine models employing some form of empirical modeling...
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