Abstract:
Monitoring of actual aircraft structural usage and loads would enhance rotorcraft safety while enabling reduced operating costs via usage-based maintenance (UBM) credits. While flight regime recognition (RR) algorithms have been demonstrated, they have not been fully validated, and regime-based UBM credits remain elusive due to both technical and certification challenges. This paper describes a viable method, which was developed by Sikorsky Aircraft Corporation under an R&D effort funded by the Federal Aviation Administration Technical Center, for achieving UBM retirement credits for a representative life-limited component based on individual aircraft RR usage statistics calculated from Health and Usage Monitoring System (HUMS) operational fleet data recorded on S-92® rotorcraft. A RR post-processing technique for addressing key technical challenges is described and validation results against flight test data are presented. The RR post-processing method is applied to operational HUMS data resulting in individual aircraft usage statistics across the fleet. Usage statistics are compared to the composite worst case (CWC) usage spectrum by individual tail number to identify the best candidates for UBM life credits. Finally, a UBM component retirement credit is calculated for a specific tail number using reliability factors and validated within a probabilistic framework that assures the goal of six-nines (0.999999) fatigue reliability is maintained.