ROCKET ENGINE HEALTH MONITORING USING A MODEL-BASED APPROACH

A stable, accurate a nd computationally efficient strategy termed Generalized Data Reduction (GDR) was recently developed to support rocket engine analysis. The GDR technique is suitable for the simultaneous real-time e stimation of numerous rocket engine health parameters. As such, it has the potential to serve as the foundation for both real-time and post-test/flight rocket engine health monitoring. The previously proposed algorithm has been extended and extensively tested using MC-1 test data. Excellent agreement is shown between GDR and conventional post-test data reduction results for these test data. Results of simulated anomaly studies are presented to demonstrate GDR’s ability to identify the ca usal source of smallscale a nomalies. Likewise, the robust response of GDR to missing sensor data is shown through simulated sensor elimination results. Finally, the efficacy of the GDR approach with a small flight-like sensor suite is demonstrated.