Robust Particle Filters for Fatigue Crack Growth Estimation in Rotorcraft Structures

Fatigue crack growth propagation in critical rotorcraft structures is much more complex than fixed-wing aircrafts in part due to the random and vibratory nature of the rotorcraft flight load spectrum. Existing physical damage models, which are originally developed for the uniform cyclic loads of fixed-wing platforms, are not accurate enough for rotorcraft structures. Such inaccuracy often results in increased risk of operation and higher cost of maintenance. The goal of this paper is to present an integrated diagnostic framework for accurate fatigue life estimation of critical rotorcraft structures by combining the predictions of a physical damage model and evidence from real-time diagnostic sensor data. The diagnostic framework obtains the most probable crack size at each inspection interval using a sequential Monte Carlo method known as particle filters. To validate the framework, three representative rotorcraft principal structural elements were tested using an actual rotorcraft flight load spectrum. Results show that the crack size estimation error of the method presented here is much lower than any of the currently available physical damage models.