24 Helicopter Rotor Tuning Kourosh Danai

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University of Massachusetts

24.1 Introduction ....................................................................... 24-1

24.2 Neural Network-Based Tuning ......................................... 24-4

24.3 Probability-Based Tuning .................................................. 24-5

24.4 Adaptive Tuning ................................................................. 24-8

The Interval Model † Estimation of Feasible Region †

Selection of Blade Adjustments † Learning

24.5 Case Study .......................................................................... 24-12

Simulation Model † Interval Modeling † Performance

Evaluation

24.6 Conclusion ......................................................................... 24-17

Summary

Before a helicopter leaves the plant, its rotors need to be tuned so that the helicopter vibration meets the required

specifications during different flight regimes. For this, three different adjustments can be made to each rotor blade in

response to the magnitude and phase of vibration. In this chapter, the basic concepts for determining the blade

adjustments are discussed, and three methods with fundamentally different approaches are described. A neural

network-based method is described, which trains a feedforward network as the inverse model of the effect of the

blade adjustments on helicopter vibrations, and uses the inverse model to determine the blade adjustments. Another

is a probability-based method that maximizes the likelihood of success of the selected blade adjustments based on a

stochastic model of the probability densities of the vibration components. The third method is an adaptive method

that uses an interval model to represent the range of effect of blade adjustments on helicopter vibration, so as to cope

with the nonlinear and stochastic nature of aircraft vibration. This method includes the a priori knowledge of the

process by defining the initial coefficients of the interval model according to sensitivity coefficients between the blade

adjustments and helicopter vibration, but then transforms these coefficients into intervals and updates them after

each tuning iteration, to improve the model estimation accuracy. The details of rotor tuning are described through a

case study, which demonstrates the application of the adaptive method.

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