Computational Acoustic Beamforming for Noise Source Identification for Small Wind Turbines

Area of Science:

• Acoustics
• Aerodynamics
• Mechanical Engineering

Background:

• Small wind turbines are increasingly used, but their noise generation mechanisms require detailed investigation.
• Accurate identification of noise sources is crucial for developing effective noise mitigation strategies.

Purpose of the Study:

• To develop and validate a computational acoustic beamforming (CAB) methodology for identifying noise sources in small wind turbines.
• To apply the validated CAB methodology to a commercial small wind turbine to pinpoint dominant noise generation mechanisms.

Main Methods:

• Development of a novel computational acoustic beamforming (CAB) methodology.
• Validation of the CAB methodology using NACA 0012 airfoil trailing edge noise.
• Application of CAB to a commercial small wind turbine to generate simulated acoustic maps.

Main Results:

• The CAB methodology demonstrated excellent conformance with experimental measurements during validation.
• Simulated acoustic maps for the commercial small wind turbine identified key noise sources.
• Blade-tower interaction and the wind turbine nacelle were found to be primary noise mechanisms between 100 and 630 Hz.

Conclusions:

• The developed CAB methodology is a reliable tool for identifying noise sources in small wind turbines.
• Blade-tower interaction and nacelle noise are significant contributors to the sound generated by small wind turbines in the studied frequency range.