Automated Reasoner Technology for Managing Military Aircraft
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AbstractComprehensive health monitoring systems are fielded on some Navy aircraft, including the Integrated Aircraft Health Monitoring (IAHM) on the F/A-18, and rotorcraft Health and Usage Monitoring Systems (HUMS) on a subset of the Navy’s H-60 and H-53 inventory. Due to the early successes and benefits shown by these systems, new platforms such as JSF will have even more comprehensive Prognostic Health Monitoring (PHM) capabilities. These systems generate enormous amounts of data on component and subsystem operation and health. A key issue that has emerged is that the volume of data produced by these systems is now greater than the capacity of the human analysts to review it. Clearly, as the number of aircraft equipped with HUMS and PHM continues to increase, there is a critical need to automate analysis of this data. In addition, the vast quantities of aircraft health data that are archived after flight represent a potential gold mine of information on the fleet. During Phase I, Sentient developed a prototype AutoReasoner software package that automatically processes flight data using sophisticated data fusion and reasoning logic to produce actionable information on state-of-health at the LRU level. This software was successfully demonstrated using HUMS data from the H-60 rotorcraft. In Phase II, Sentient will extend the capabilities of this AutoReasoner to include command level readiness information, and will develop data mining tools to scan the database post-flight and assess PHM system performance, emerging trends, and bad actors. F/A-18 data will be used in Phase II to stand in for JSF operational data, although the system will be targeted to the JSF platform.
* information listed above is at the time of submission.