Broadband Modal Identification Exploiting the Group-Sparse Characteristic of Aero-Engine Fan Noise Mode

Fan noise is a significant component of aircraft noise, and modal identification is an effective method to analyze duct noise. In recent years, the research on tonal noise has been deepening and maturing, and broadband noise has become a challenge for duct noise research. In this paper, a broadband duct acoustic modal identification method based on a group-sparse strategy and variational Bayesian inference is proposed based on the distribution characteristics of broadband mode. The group-sparse model is used to model the mode distribution, and the mode coefficients and associated parameters are estimated using variational Bayesian inference. The validity of the proposed method is verified through both numerical simulations and experimental tests. The results demonstrate the ability of the proposed method to determine mode coefficients accurately, and the results of the proposed method are also more consistent with the mode distribution characteristics.

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Publication Details

Journal
Journal of Theoretical and Computational Acoustics
Published
2025-07-18
DOI
https://doi.org/10.1142/s2591728525500082
Primary Topic
Vehicle Noise and Vibration Control
Type
article
Field-Weighted Citation Impact
0.00

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article

Broadband Modal Identification Exploiting the Group-Sparse Characteristic of Aero-Engine Fan Noise Mode

Guangming Dong, Xiaoping Zhou, Ran Wang, Sulei Zhu et al.
Journal of Theoretical and Computational Acoustics
Vehicle Noise and Vibration Control
article

Broadband Modal Identification Exploiting the Group-Sparse Characteristic of Aero-Engine Fan Noise Mode

Guangming Dong, Xiaoping Zhou, Ran Wang, Sulei Zhu, Hao Gu, Liang Yu, Hao Li
article en

Abstract

Fan noise is a significant component of aircraft noise, and modal identification is an effective method to analyze duct noise. In recent years, the research on tonal noise has been deepening and maturing, and broadband noise has become a challenge for duct noise research. In this paper, a broadband duct acoustic modal identification method based on a group-sparse strategy and variational Bayesian inference is proposed based on the distribution characteristics of broadband mode. The group-sparse model is used to model the mode distribution, and the mode coefficients and associated parameters are estimated using variational Bayesian inference. The validity of the proposed method is verified through both numerical simulations and experimental tests. The results demonstrate the ability of the proposed method to determine mode coefficients accurately, and the results of the proposed method are also more consistent with the mode distribution characteristics.

Journal of Theoretical and Computational AcousticsVol. 33(04)
East China University of Science and Technology (CN), Northwestern Polytechnical University (CN), Shanghai Jiao Tong University (CN), Shanghai Normal University (CN), Structural Integrity Associates (United States) (US), Shanghai Maritime University (CN)
Natural Science Foundation of Shanghai, National Natural Science Foundation of China
Openalex Percentile: Top 80%
Vehicle Noise and Vibration Control
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Broadband Modal Identification Exploiting the Group-Sparse Characteristic of Aero-Engine Fan Noise Mode — Guangming Dong, Xiaoping Zhou, et al. · Journal of Theoretical and Computational Acoustics (2025) | TGRS Research Map | TGRS