A combined analytical and experimental approach is introduced to estimate the dynamic response of complex systems from a limited number of measurements. The method is based on the concept that modal information is sufficient to extrapolate the complete map of the response from experimental data through the reconstruction of modal loads. The capabilities of the algorithm are first verified via well-controlled lab experiments on a thin-walled aluminium-rotor blade. Numerical results from a comprehensive UH-60 multibody model are then compared with available experimental data. Significant improvements in the accuracy of the predicted results are achieved when simple airloads models are employed as inputs.
This paper presents an in-flight damage alleviation system for rotorcraft based upon an in-the-loop structural model which provides component damage estimates as feedback to the control system for control gain adjustment. Using a dynamic inversion control system architecture coupled with an artificial neural network based damage model, a substantial increase in the lifespan of specific rotor head structural components has been found with minimal impact to the handling qualities of the rotorcraft.
NomenclatureD = component damage D r = normalized component damage D f = final component damage ̇ = component damage rate n = number of cycles to failure N Z = vertical load factor q = pitch rate ̇ = pitch acceleration V z = vertical speed = vertical speed command W i = weighting factor ζ = damping ratio σ = stress θ = pitch attitude θ cmd = commanded pitch attitude ̇ = pitch rate ̈ = pitch acceleration τ = time constant ω n = natural frequency 1
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