A simple method improving acoustic mode identification capability based on genetic algorithms

Author:

Bu Huanxian12ORCID,Han Jun1,Xiao Yuqi3,Zhou Jie34

Affiliation:

1. School of Civil Aviation, Northwestern Polytechnical University 1 , Xi'an 710072, China

2. Yangtze River Delta Research Institute of NPU 2 , Taicang, Jiangsu Province 215400, China

3. School of Aeronautics, Northwestern Polytechnical University 3 , Xi'an 710072, China

4. National Key Laboratory of Strength and Structural Integrity 4 , Xi'an 710072, China hbu@nwpu.edu.cn , hanjun@mail.nwpu.edu.cn , xiaoyq@mail.nwpu.edu.cn , jiezhou@nwpu.edu.cn

Abstract

This letter develops a simple approach of duct mode identification and reconstruction based on genetic algorithms, which can extend the azimuthal mode order range compared to the conventional method based on the (spatial) discrete Fourier transform. The underlying principle is reconstructing the dominant mode from the modal identification forward model through optimization by exploiting the sparsity of the mode amplitude vector. The performance is experimentally demonstrated for detections of one and two azimuthal modes under noisy conditions with nondominant modes. Overall, the proposed genetic-algorithm-based framework for solving acoustic inverse problems is beneficial to duct acoustic testing, particularly design evaluations of fan blades and acoustic liners for aeroengines.

Funder

Basic Research Program of Taicang

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Acoustical Society of America (ASA)

Reference12 articles.

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4. Deconvolution of azimuthal mode detection measurements;J. Sound Vib.,2018

5. Accuracy and robustness of sparse reconstruction techniques for azimuthal mode analysis of in-duct sound fields;J. Sound Vib.,2022

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