A Practical Regime Prediction Approach for HUMS Applications

A number of aircraft parameters such as attitude, altitude, airspeed, torque, etc. are currently collected and used by health usage monitoring system (HUMS) to identify regimes. For each regime, a damage factor is assigned to each component that has usage. These damage factors are assigned by the original equipment manufacturers (OEMs) based on measured stresses in the aircraft when undergoing a given maneuver. Therefore, it is important that the regimes can be recognized correctly during the flight of the aircraft to avoid either underestimated or overestimated damages for the aircraft. A number of studies have shown the effectiveness of some newly developed regime recognition algorithms. As an extension to regime recognition to improve safety and/or reduce maintenance by predicting if the aircraft will be flown in a damaging way, a regime prediction approach is presented in this paper. This approach could be used to alert the pilot, who could then avoid flying the aircraft in those damaging regimes. Potentially, this extension could be used to alert if the power required is greater than the power available for some maneuvers such as heavy lift.