An Approach To Fatigue Damage Estimation Of Helicopter Rotating Components Using Computational Intelligence Techniques

In this paper we present a computational intelligence approach to estimate fatigue usage in rotating components based on real aircraft data (Australian Black Hawk S-70A-9 flight load survey data). The load time signal for the main rotor pushrod in forward level flight is first predicted using only input data from the flight state and control system parameters through a computational intelligence model. The subsequent fatigue usage is then estimated using adaptations of standard techniques, such as the Rainflow cycle counting method. More accurate fatigue accumulation and remaining life predictions can possibly be made considering the real operational flight load spectra and not just based on design mission estimations, accounting for the change in use of platforms during their in-service lives. This approach is particularly devoted to rotating components and avoids the use of additional sensors, specifically challenging when dynamic components are considered.