Neural Networks for Smoothing of Helicopter Rotors
INTELLIGENT AUTOMATION CORP SAN DIEGO CA
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A general, neural network based algorithm has been developed and applied to the problem of helicopter rotor smoothing. This approach provides non-parametric mappings between the spaces of rotor adjustment and vibration measurements, which are derived directly from empirical data, and permits to relax the usually used linearity assumption. Additionally, the rotor smoothing solutions are optimized to minimize not only the predicted vibration levels and track split but also the number of required adjustment moves. The neural network rotor smoothing system is a part of the VMEP Vibration Management Enhancement Program PC Ground Base Station program and has been successfully applied to the AH-64 Apache and UH-60 Blackhawk helicopters. Applications to other types of helicopters are under development.