An investigation of the wind noise reduction mechanism of porous microphone windscreens

Wind energy is a green way to produce electricity without carbon emissions. However, the infrasound and low frequency audible sound radiated by wind turbines may adversely affect the nearby communities. To investigate the impact of wind farm noise and to understand its noise generation mechanism and propagation, the sound level of wind farm noise must be measured under windy conditions. However, it is often a challenge to measure wind turbine noise under windy conditions in quiet rural residential areas due to wind noise, especially for infrasound and low frequency audible sound. Wind noise is the pseudo sound pressure generated on microphones due to turbulent pressure fluctuations and is indistinguishable from the acoustic signals to be measured. Various microphone windscreens have been utilized to reduce wind noise. However, the physical mechanism of wind noise reduction by windscreens has been unclear to date. The aim of this PhD research is to investigate the mechanisms of wind noise generation and the wind noise reduction mechanism of porous microphone windscreens, and then develop a new compact acoustic measurement system that is insensitive to wind noise. To achieve this objective, a critical literature review is first presented to summarise the state-of-the-art research results in the field of wind noise and its reduction. Then, the research is focused on three aspects: the mechanisms of wind noise generation, the wind noise reduction mechanism of porous microphone windscreens, and wind noise reduction with a compact spherical microphone array. In the first aspect of this thesis, the generation mechanism of wind noise is explored and two theoretical models are proposed to predict wind noise spectra. One model is for outdoor atmospheric turbulence where the Reynolds number based on the Taylor microscale varies from 4250 to 19500, and the other is for indoor fan generated turbulent flows where the Reynolds number based on the Taylor microscale is estimated to be around 432. The proposed theoretical models are validated with existing simulations and experimental results from the literature, as well as measurement results conducted as part of this thesis in a car park for outdoor wind noise and in a laboratory for wind noise from an axial fan. In the second aspect of this thesis, the mechanism of wind noise reduction by porous microphone windscreens is investigated. It is shown that the wind noise reduction of porous microphone windscreens is caused by viscous and inertial forces introduced by the porous structure. Simulation results indicate that the design of porous microphone windscreens should take into account both turbulence suppression inside and wake generation behind the windscreens to achieve optimal performance. Besides, porous windscreens are found to be the most effective in attenuating wind noise in a certain frequency range, where the windscreen diameter is approximately 2 to 4 times the turbulence wavelengths. It is also found that the wind noise reduction is related to the spatial decorrelation of the wind noise signals provided by porous microphone windscreens. The simulation findings are validated with measurement results from an axial fan in a laboratory. In the last aspect of this thesis, a method for wind noise reduction with the spherical microphone array is proposed, and the effect of wind noise on the beamforming performance of a spherical microphone array is investigated. The characteristics of the wind noise is explored and compared with the sound signals in the spherical harmonics domain, based on which a spherical harmonics domain low pass filter method is proposed to reduce wind noise without degrading the desired sound signal. Experimental results demonstrate the feasibility of the proposed method. On the other hand, the effects of wind noise on the beamforming performance of the spherical Plane Wave Decomposition (PWD), Delay and Sum (DAS) and Maximum Variance Distortionless Response (MVDR) beamformers are studied. The experimental results demonstrate that the MVDR beamformer is insensitive to wind noise and able to localise the sound source direction under windy conditions. In summary, two theoretical models are proposed in this PhD research to predict the wind noise spectra in outdoor, large Reynolds number, atmospheric turbulence and indoor, small Reynolds number, turbulent flows, respectively; the physical mechanism of wind noise reduction by porous microphone windscreens is found to be related to the spatial decorrelation effect on the wind noise signal due to the porous structure, and it is demonstrated that the design of porous windscreens should take into account both turbulence suppression inside and wake generation behind the windscreen to achieve optimal performance; the effect of wind noise on the beamforming performance of a spherical microphone array is investigated and a spherical harmonic domain low pass filtering method is proposed to attenuate wind noise without degrading the desired sound signal