Rotorcraft Gross Weight and Center of Gravity Prediction Using Regime Recognition

Abstract

Several U.S. Navy rotorcraft models are equipped with Health and Usage Monitoring Systems. On-board or on-ground Regime Recognition (RR) programs are used to develop individual rotorcraft usage spectrums to compute component and airframe fatigue life expended (FLE). FLE is a function of rotorcraft gross weight (GW) and center of gravity (CG), but neither are monitored by sensors. Thus GW and CG computation algorithms based on measured engine torque curves and trim equations during hover are developed and incorporated into RR. The algorithms are validated using numerous fleet flights with known GWs and CG positions. Excellent correlation between predicted and actual values is observed with low standard error of estimate. The in-flight variation of GW and CG is determined with the help of recorded fuel weight. RR is used to analyze 32,000 h of data from 111 rotorcraft to develop GW and CG utilization distributions. Furthermore, GW variation is modeled with a beta probability distribution and the joint probability distribution of GW and CG utilization is determined to assess airframe and dynamic component fatigue lives.