Helicopter rotor blade frequency evolution with damage growth and signal processing

Structural damage in materials evolves over time due to growth of fatigue cracks in homogenous materials and a complicated process of matrix cracking, delamination, fiber breakage and fiber matrix debonding in composite materials. In this study, a finite element model of the helicopter rotor blade is used to analyze the effect of damage growth on the modal frequencies in a qualitative manner. Phenomenological models of material degradation for homogenous and composite materials are used. Results show that damage can be detected by monitoring changes in lower as well as higher mode flap (out-of-plane bending), lag (in-plane bending) and torsion rotating frequencies, especially for composite materials where the onset of the last stage of damage of fiber breakage is most critical. Curve fits are also proposed for mathematical modeling of the relationship between rotating frequencies and cycles. Finally, since operational data are noisy and also contaminated with outliers, denoising algorithms based on recursive median filters and radial basis function neural networks and wavelets are studied and compared with a moving average filter using simulated data for improved health-monitoring application. A novel recursive median filter is designed using integer programming through genetic algorithm and is found to have comparable performance to neural networks with much less complexity and is better than wavelet denoising for outlier removal. This filter is proposed as a tool for denoising time series of damage indicators.