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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

Peng Wang1,2, Zhiying Gao1,2,*, Yongyan Chen1, Rina Su1,2, Yefei Bai2, Jianlong Ma1,2, 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: email

Energy Engineering 2026, 123(6), 13 https://doi.org/10.32604/ee.2025.073862

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.

Keywords

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

Cite This Article

APA Style
Wang, P., Gao, Z., Chen, Y., Su, R., Bai, Y. et al. (2026). Identification and Analysis of Aerodynamic Sound Sources in Wind Turbines Based on the Integration of Time-Domain De-Doppler and Orthogonal Matching Pursuit Techniques. Energy Engineering, 123(6), 13. https://doi.org/10.32604/ee.2025.073862
Vancouver Style
Wang P, Gao Z, Chen Y, Su R, Bai Y, Ma J, et al. Identification and Analysis of Aerodynamic Sound Sources in Wind Turbines Based on the Integration of Time-Domain De-Doppler and Orthogonal Matching Pursuit Techniques. Energ Eng. 2026;123(6):13. https://doi.org/10.32604/ee.2025.073862
IEEE Style
P. Wang et al., “Identification and Analysis of Aerodynamic Sound Sources in Wind Turbines Based on the Integration of Time-Domain De-Doppler and Orthogonal Matching Pursuit Techniques,” Energ. Eng., vol. 123, no. 6, pp. 13, 2026. https://doi.org/10.32604/ee.2025.073862



cc Copyright © 2026 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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