• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.7
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• pp.524-531
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• 2013

This work aims at developing a RTB (Rotor Track and Balance) system to alleviate imbalances originating from various sources encountered during blade manufacturing process and environmental factors. The analytical RTB model is determined based on the linear regression analysis to relate the RTB adjustment parameters and their track and vibration results. The model is validated using the flight test data of a full helicopter. It is demonstrated that the linearized model has been correlated well with the test data. A hybrid optimization problem is formulated to find the best solution of the RTB adjustment parameters using the genetic algorithm combined with the PSO (Particle Swarm Optimization) algorithm. The optimization results reveal that both track deviations and vibration levels under various flight conditions become decreased within the allowable tolerances.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.11
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• pp.989-996
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• 2016

This paper intends to develop the rotor track and balance (RTB) algorithm using the nonlinear RTB models and a real-coded hybrid genetic algorithm. The RTB response data computed using the trim solutions with variation of the adjustment parameters have been used to build nonlinear RTB models based on the quadratic interpolation functions. Nonlinear programming problems to minimize the track deviations and the airframe vibration responses have been formulated to find optimum settings of balance weights, trim-tab deflections, and pitch-link lengths of each blade. The results are efficiently resolved using the real-coded genetic algorithm hybridized with the particle swarm optimization techniques for convergence acceleration. The nonlinear RTB models and the optimized RTB parameters have been compared with those computed using the linear models to validate the proposed techniques. The results showed that the nonlinear models lead to more accurate models and reduced RTB responses than the linear counterpart.