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Identification and Analysis of Aerodynamic Sound Sources in Wind Turbines Based on the Integration of Time-Domain De-Doppler and Orthogonal Matching Pursuit Techniques.

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Title: Identification and Analysis of Aerodynamic Sound Sources in Wind Turbines Based on the Integration of Time-Domain De-Doppler and Orthogonal Matching Pursuit Techniques.
Authors: Wang, Peng1,2 (AUTHOR), Gao, Zhiying1,2 (AUTHOR) hawkwarm@imut.edu.cn, Chen, Yongyan1 (AUTHOR), Su, Rina1,2 (AUTHOR), Bai, Yefei2 (AUTHOR), Ma, Jianlong1,2 (AUTHOR), Zhang, Tianhao1 (AUTHOR)
Source: Energy Engineering. 2026, Vol. 123 Issue 6, p1-24. 24p.
Subjects: Wind turbines, Orthogonal matching pursuit, Array processing, Deconvolution (Mathematics), Doppler effect, Acoustic localization, Aerodynamic noise
Abstract: We propose a novel procedure, Time-Domain De-Dopplerized Orthogonal Matching Pursuit deconvolution approach for the mapping of acoustic sources (TD-OMP-DAMAS), for separating aerodynamic noise sources distributed across wind turbine blades (WTB), a task that is typically hindered by mutual interference and spatial mixing. The proposed procedure is a two-stage, hybrid de-Doppler/sparse-reconstruction algorithm based on time-domain de-Doppler (TD, Stage 1) and an orthogonal matching pursuit (OMP)-based deconvolution scheme (Stage 2), enabling sparse-reconstruction techniques to be effectively applied in rotating-source scenarios. The method is validated using both simulated rotating-source data and wind-tunnel measurements, and its performance is systematically compared with several conventional approaches, including conventional beamforming (CBF), time-domain de-Doppler beamforming (TD-BF), and time-domain de-Doppler deconvolution approach for the mapping of acoustic sources (TD-DAMAS). Numerical results demonstrate that TD-OMP-DAMAS achieves the smallest localization error and the highest spatial resolution among all tested algorithms, while also maintaining strong robustness under low signal-to-noise ratio conditions and requiring significantly fewer iterations than TD-DAMAS to accurately converge to the true source positions. Wind-tunnel tests further show that, under an inflow velocity of 6 m/s and a tip-speed ratio of 4.5, the method improves spatial resolution by approximately 89% compared with CBF, confirming its superior capability in separating aerodynamic sources located on different WTB. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:We propose a novel procedure, Time-Domain De-Dopplerized Orthogonal Matching Pursuit deconvolution approach for the mapping of acoustic sources (TD-OMP-DAMAS), for separating aerodynamic noise sources distributed across wind turbine blades (WTB), a task that is typically hindered by mutual interference and spatial mixing. The proposed procedure is a two-stage, hybrid de-Doppler/sparse-reconstruction algorithm based on time-domain de-Doppler (TD, Stage 1) and an orthogonal matching pursuit (OMP)-based deconvolution scheme (Stage 2), enabling sparse-reconstruction techniques to be effectively applied in rotating-source scenarios. The method is validated using both simulated rotating-source data and wind-tunnel measurements, and its performance is systematically compared with several conventional approaches, including conventional beamforming (CBF), time-domain de-Doppler beamforming (TD-BF), and time-domain de-Doppler deconvolution approach for the mapping of acoustic sources (TD-DAMAS). Numerical results demonstrate that TD-OMP-DAMAS achieves the smallest localization error and the highest spatial resolution among all tested algorithms, while also maintaining strong robustness under low signal-to-noise ratio conditions and requiring significantly fewer iterations than TD-DAMAS to accurately converge to the true source positions. Wind-tunnel tests further show that, under an inflow velocity of 6 m/s and a tip-speed ratio of 4.5, the method improves spatial resolution by approximately 89% compared with CBF, confirming its superior capability in separating aerodynamic sources located on different WTB. [ABSTRACT FROM AUTHOR]
ISSN:01998595
DOI:10.32604/ee.2025.073862