A global rotor noise control method based on near-field acoustic holography and sound field reproduction

Abstract

Aiming at the severe aerodynamic noise generated by the rotor of rotorcrafts, a global active noise control method is proposed based on near-field acoustic holography (NAH) and sound field reproduction (SFR). The microphone array here is not only used to evaluate errors as in existing methods, but also to predict the rotor noise by extracting acoustic modal information. The loudspeaker array reproduces a secondary sound field with the same acoustic modal components but in opposite phase to achieve global noise reduction. Specifically, by arranging microphones on the fuselage, the rotor noise prediction problem is transformed into an external domain problem of the NAH. Then, by extending the SFR to the external domain, the loudspeaker array is used to reproduce a target sound field which just achieves sound-sound cancellation with the rotor noise globally. Further, the application of the acoustic modal analysis shows that the acoustic modal distribution of the rotor noise is determined by the number of blades, which greatly reduces the scale of loudspeaker/microphone array and is conducive to on-line noise control. The acoustic modal decomposition of the rotor noise shows that the amplitude of the main acoustic mode decays the slowest with distance compared with other acoustic modes, and it is the main component of the far-field noise. The comprehensive evaluation of the model rotor noise reduction performance at different scales shows that the global noise reduction effect for controlling all acoustic modes exceeds 40 dB, while for controlling the main acoustic mode reaches 18 dB, and the required power is reduced by 84%. Finally, the global active noise control experiments for the model rotor are conducted. The results show that the global noise reduction can reach 17 dB through controlling the main acoustic mode. The GANC method shows great advantage of global noise reduction and high engineering application potential.