Open Access

ARTICLE

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

Peng Wang^1,2, Zhiying Gao^1,2,*, Yongyan Chen¹, Rina Su^1,2, Yefei Bai², Jianlong Ma^1,2, Tianhao Zhang¹
1 College of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot, 010051, China
2 Key Laboratory of Wind Energy and Solar Energy Utilization Technology of Ministry of Education, Inner Mongolia University of Technology, Hohhot, 010051, China
* Corresponding Author: Zhiying Gao. Email:

Energy Engineering https://doi.org/10.32604/ee.2025.073862

Received 27 September 2025; Accepted 22 December 2025; Published online 09 January 2026

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.

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Keywords

Wind turbine noise; source identification; DAMAS; orthogonal matching pursuit

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