声学学报2025,Vol.50Issue(1) :187-200.DOI:10.12395/0371-0025.2023116

贝叶斯压缩感知识别管内风扇噪声单音声模态

Bayesian compressive sensing for identifying tonal acoustic modes of fan noise in the duct

王冉 白玥 余亮 董广明
声学学报2025,Vol.50Issue(1) :187-200.DOI:10.12395/0371-0025.2023116

贝叶斯压缩感知识别管内风扇噪声单音声模态

Bayesian compressive sensing for identifying tonal acoustic modes of fan noise in the duct

王冉 1白玥 1余亮 2董广明3
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作者信息

  • 1. 上海海事大学物流工程学院 上海 201306
  • 2. 西北工业大学民航学院 西安 710072;大型客机集成技术与模拟飞行全国重点实验室 上海 200126
  • 3. 大型客机集成技术与模拟飞行全国重点实验室 上海 200126
  • 折叠

摘要

风扇噪声是大涵道比发动机的重要噪声源,其可传播模态随频率增加而增多,难以通过足够的传声器进行测量,为此提出了一种用于风扇单音噪声模态识别的贝叶斯压缩感知方法来解决声模态识别中传声器数量不足的问题.管道内声场用概率模型描述,模态识别的压缩感知逆问题用贝叶斯框架表示.基于贝叶斯压缩感知的模态识别方法能稀疏恢复未知模态系数解,实现参数自适应调优.数值模拟和实验测试验证了贝叶斯压缩感知方法在模态识别中的有效性.结果表明,贝叶斯压缩感知方法可以用比传统方法少56.3%的传声器准确识别目标模态.

Abstract

Fan noise is a significant noise source for large bypass ratio engines,and its propagatable modes increase with frequency,making it difficult to be measured by a sufficient number of microphones.A Bayesian compressive sensing method for fan tonal noise mode identification is proposed to solve the problem of insufficient number of microphones in acoustic mode identification.The sound field in the duct is described by a probabilistic model,and the inverse problem of compression perception for mode identification is represented by a Bayesian framework.The mode identification method based on Bayesian compressive sensing can sparsely recover unknown mode coefficient solutions and achieve parameter adaption.Numerical simulations and experimental tests verify the effectiveness of the Bayesian compressive sensing method in mode identification.The results show that the proposed method of mode identification can accurately identify the target modes with 56.3%fewer microphones than the conventional method.

关键词

风扇噪声/周向传声器阵列/声模态识别/贝叶斯压缩感知/单音噪声

Key words

Fan noise/Circumferential microphone array/Acoustic mode identification/Bayesian compressive sensing/Tonal noise

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出版年

2025
声学学报
中科院声学所

声学学报

北大核心
影响因子:0.802
ISSN:0371-0025
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