基于谱图分析的无人机推力模型识别

I. H. Pizetta, A. Brandão, M. Sarcinelli-Filho
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引用次数: 3

摘要

研究了鹦鹉无人机四旋翼螺旋桨气动常数的非接触辨识方法。实验装置包括一个安装在飞行舞台上的麦克风,用于记录音频数据。在方法上,采用谱图分析方法,根据滤波后的声信号估计螺旋桨速度。众所周知,在悬停机动中,当无人机质量增加时,螺旋桨旋转更快以产生必要的推力增量。在这项工作中,旋翼机以其出厂设置起飞,首先没有船体,对应的质量为413 g,之后有一个小船体,对应的质量为444 g,一个更大的船体,对应的质量为462 g。在这个序列中,螺旋桨的速度被估计为这三种情况中的每一种,使用由麦克风记录的音频频谱图,对应于四个转子产生的声音。最后,利用估计的速度来识别气动参数,从而验证了该方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
UAV Thrust Model Identification Using Spectrogram Analysis
This paper deals with a non-contact method to identify the aerodynamic propeller constants of the Parrot AR.Drone quadrotor. The experimental setup consists of a microphone installed in the flight arena to record audio data. In terms of methodology, a spectrogram analysis is adopted to estimate the propeller velocity based on the filtered sound signal. It is known that, in a hovering maneuver, when the UAV mass increases, the propellers rotate faster to produce the necessary thrust increment. In this work, the rotorcraft takes off with its factory settings, first with no hull, corresponding to a mass of 413 g, and after with a small hull, corresponding to a mass of 444 g, and a bigger hull, corresponding to a mass of 462 g. In the sequence, the velocity of the propellers are estimated for each of these three cases using spectrograms of audio recorded by a microphone, corresponding to the sound generated by the four rotors. Finally, the estimated velocity is used to identify the aerodynamic parameters, thus validating the proposal.
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