An adaptive method of helicopter track and balance is introduced to improve the search for the required blade adjustments. In this method, an interval model is used to represent the range of effect of blade adjustments on helicopter vibration, instead of exact values, to cope with the nonlinear and stochastic nature of aircraft vibration. The coefficients of the model are initially defined according to sensitivity coefficients between the blade adjustments and helicopter vibration, to include the ‘a priori’ knowledge of the process. The model coefficients are subsequently transformed into intervals and updated after each tuning iteration to improve the model’s estimation accuracy. The search for the required blade adjustments is performed according to this model by considering the vibration estimates of all of the flight regimes to provide a comprehensive solution for track and balance. The effectiveness of the proposed method is evaluated in simulation using a series of neural networks trained with actual vibration data. The results indicate that the proposed method improves performance according to several criteria representing various aspects of track and balance.

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