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Sequential experimental design approaches to helicopter rotor tuning

Two different approaches based on sequential experimental design concepts have been studied for helicopter rotor tuning, which is the process of adjusting the rotor blades so as to reduce the aircraft vibration and the spread of rotors. One uses an interval model adapted sequentially to improve the search for the blade adjustments. The other uses a probability model to search for the blade adjustments with the maximal probability of success. In the first approach, an interval model is used 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. The coefficients of the model are initially defined according to sensitivity coefficients between the blade adjustments and helicopter vibration, to include the expert 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 blade adjustments is performed according to this model by considering the vibration estimates of all of the flight regimes so as to provide a comprehensive solution for rotor tuning. The second approach studied uses a probability model to maximize the likelihood of success of the selected blade adjustments. The underlying model in this approach consists of two segments: a deterministic segment to include a linear regression model representing the relationships between the blade adjustments and helicopter vibration, and a stochastic segment to comprise probability densities of the vibration components. The blade adjustments with the maximal probability of generating acceptable vibration are selected as recommended adjustments. The effectiveness of the proposed approaches is evaluated in simulation based on a series of neural networks trained with actual vibration data. To incorporate the stochastic behavior of the helicopter vibration and better simulate the tuning process, the probability density function of the prediction error is used to simulate noise. Due to the stochastics of the helicopter vibration, the proposed approaches cannot be evaluated by deterministic measures. Therefore, several performance measures have been devised to represent the various aspects of helicopter rotor tuning as the evaluation criteria.

Identiferoai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-4041
Date01 January 2005
CreatorsWang, Shengda
PublisherScholarWorks@UMass Amherst
Source SetsUniversity of Massachusetts, Amherst
LanguageEnglish
Detected LanguageEnglish
Typetext
SourceDoctoral Dissertations Available from Proquest

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