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Journal of Aerospace Engineering and Mechanics最新文献

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Helicopter Tail Rotor and the Training of a Recurrent Neural Network 直升机尾桨与递归神经网络的训练
Pub Date : 1900-01-01 DOI: 10.36959/422/461
Castillo-Rivera S
This work presents the training of a Recurrent Neural Network (RNN) for the identification of dynamics behaviour in aeronautical systems. The network is used to model flap motion on the tail rotor at determined dynamics conditions. The study the tail rotor performance agrees with the expected outcomes. The modelling is not a straightforward task and the dynamics observed in the rotor display that the model could be a suitable tool for monitoring performance under certain conditions.
这项工作提出了一个递归神经网络(RNN)的训练,用于识别航空系统的动力学行为。利用该网络对尾桨在一定动力学条件下的襟翼运动进行建模。对尾桨性能的研究符合预期结果。建模并不是一项简单的任务,在转子中观察到的动力学表明,该模型可以是在某些条件下监测性能的合适工具。
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Journal of Aerospace Engineering and Mechanics
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