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Separation of Main and Tail Rotor Noise from Ground-Based Acoustic Measurements

机译：从地面声学测量中分离出主旋翼和尾旋翼噪声

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摘要

A new method of characterizing the external noise radiation of rotorcraft is presented, making use of ground-based acoustic measurements. The method employs time-domain de-Dopplerization to transform the acoustic pressure time-history data collected from a fixed array of ground-based microphones to the equivalent time-history signals observed by an array of virtual in-flight microphones traveling with the helicopter. The now-stationary signals observed by the virtual microphones are then periodically averaged with the main and tail rotor blade passages, which are inferred from the acoustic signals using wavelet analysis. The averaging process suppresses noise that is not periodic with the respective rotor, allowing for the separation of main and tail rotor pressure tune histories. The averaged measurements are then interpolated across the range of directivity angles captured by the microphone array in order to generate separate acoustic hemispheres for the main and tail rotor noise sources. This method facilitates a more direct comparison of ground-based noise measurements of rotorcraft with theoretical predictions and wind tunnel measurements of isolated rotors. The new method is successfully applied to ground-based microphone measurements of a Bell 206B3 helicopter and demonstrates the strong directivity characteristics of harmonic noise radiation from both the main and tail rotors of that helicopter.
机译：提出了一种利用地面声学测量方法表征旋翼飞机外部噪声辐射的新方法。该方法采用时域去多普勒化技术，将从固定的地面麦克风阵列中收集到的声压时程数据转换为与直升机一起飞行的虚拟机上麦克风阵列所观测到的等效时程信号。然后，将虚拟麦克风观测到的当前平稳信号与主旋翼和尾旋翼叶片通道进行定期平均，然后通过小波分析从声学信号中推断出这些信号。平均过程抑制了各个转子之间非周期性的噪声，从而使主转子和尾转子的压力调整历史得以分离。然后，在麦克风阵列捕获的方向角范围内进行平均测量，以便为主旋翼和尾旋翼噪声源生成独立的声半球。这种方法有助于更直接地比较旋翼飞机的地面噪声测量值与理论预测值以及孤立旋翼的风洞测量值。新方法已成功应用于Bell 206B3直升机的地面麦克风测量，并演示了该直升机主旋翼和尾旋翼的谐波噪声辐射的强指向性特征。

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  • 来源
    《Journal of Aircraft》 |2014年第2期|464-472|共9页
  • 作者

    Eric Greenwood; Fredric H. Schmitz;

  • 作者单位

    NASA Langley Research Center, Hampton, Virginia 23681;

    University of Maryland, College Park, Maryland 20742;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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