Paper
7 September 2022 Experimental study on noise characteristics of tower surface under blade tower interaction
Peiwu Zhang, Zhiying Gao, Cuiqing Zhang, Jianwen Wang, Xiaoxue Zhang, Huijie Wu
Author Affiliations +
Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 1232943 (2022) https://doi.org/10.1117/12.2646758
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China
Abstract
In order to study the influence of blade tower interaction on tower surface noise in wind turbine operation, the surface noise of the horizontal axis wind turbine tower was tested by the surface microphone in the wind tunnel opening experiment section. The influence of tower relative position on noise and surface noise spectrum was analyzed. The results show that with the increase of the relative position of the tower, the surface noise energy decreases, which is only different from other surfaces on the front surface. The maximum increment of sound pressure level on the front and rear surfaces is 0.71R at the relative position of the tower and does not change with wind speed. The surface noise spectrum mainly shows the characteristics of the blade rotating noise, and the energy difference of each measuring point on the left and right surfaces is more obvious than that of the front and rear surfaces in the middle and high-frequency range. The relevant results can provide ideas for the optimization design of wind turbine tower noise.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peiwu Zhang, Zhiying Gao, Cuiqing Zhang, Jianwen Wang, Xiaoxue Zhang, and Huijie Wu "Experimental study on noise characteristics of tower surface under blade tower interaction", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 1232943 (7 September 2022); https://doi.org/10.1117/12.2646758
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KEYWORDS
Wind turbine technology

Wind energy

Acoustics

Analytical research

Wind measurement

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