Rocket Engine Health Monitoring System (MHS) via an Embedded Expert System (EES)

Reusable rocket engine maintenance, whether preventive, scheduled, or unscheduled, is a major escalating cost item. Significant progress has been made in the NASA and Air Force communities toward performance of the HMS function in instrumentation, analysis techniques, and envelope (trends and rate of change) monitoring. Current techniques require that domain experts be integrally involved in the analysis session and make on-line decisions to direct analysis. The SPARTA Embedded Expert System (SEES) is an intelligent system that directs the analysis by placing confidence factors on possible engine status, then recommends a course of action to an engineer or the engine controller. This technique can prevent catastrophic failures or costly rocket engine down time because of false alarms. Further, the SEES has potential as an on-board flight monitor for reusable rocket engine systems. The SEES methodology synergistically integrates vibration analysis, pattern recognition, and communications theory techniques with an artificial intelligence technique - the Embedded Expert System (EES). This integration affords a robustness via the analysis techniques with an ability to resolve conflicts by the expert system techniques. Results from processing real data will be presented.