{"title":"基于层次贝叶斯算法的航空发动机风扇声场重建","authors":"Bohan Ma, Meng Wang, Mingsui Yang, Wei Ma","doi":"10.1007/s42401-025-00345-1","DOIUrl":null,"url":null,"abstract":"<div><p>Acoustic field reconstruction for aircraft engine fans is essential for effective noise reduction. However, the use of a limited number of far-field measurement points in the reconstruction process exacerbates the ill-posedness issues, which necessitates the adoption of regularization techniques. The hierarchical Bayesian-based regularisation method has recently been applied to solve the equivalent source intensity distribution and reconstruct the sound field. However, previous methods have failed to accurately obtain the acoustic modal coefficients of the sound source, which are essential for determining the radiation type and directivity. This paper proposes a sound field reconstruction method that applies the hierarchical Bayesian algorithm to the source modal coefficient solution. Firstly, the deconvolution beamforming method obtains the sound source position. Subsequently, the hierarchical Bayesian algorithm is employed to obtain the source modal coefficients of the sound field, thereby completing the reconstruction of the sound field in the far-field region. Experimental results indicate that the proposed algorithm is highly effective in reconstructing far-field sound fields. Under free-field conditions and in mid-high frequency ranges, the average reconstruction error can be significantly reduced by using a few far-field microphones compared to traditional methods.</p></div>","PeriodicalId":36309,"journal":{"name":"Aerospace Systems","volume":"8 2","pages":"257 - 274"},"PeriodicalIF":0.0000,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sound field reconstruction of aero-engine fans using hierarchical Bayesian algorithms\",\"authors\":\"Bohan Ma, Meng Wang, Mingsui Yang, Wei Ma\",\"doi\":\"10.1007/s42401-025-00345-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Acoustic field reconstruction for aircraft engine fans is essential for effective noise reduction. However, the use of a limited number of far-field measurement points in the reconstruction process exacerbates the ill-posedness issues, which necessitates the adoption of regularization techniques. The hierarchical Bayesian-based regularisation method has recently been applied to solve the equivalent source intensity distribution and reconstruct the sound field. However, previous methods have failed to accurately obtain the acoustic modal coefficients of the sound source, which are essential for determining the radiation type and directivity. This paper proposes a sound field reconstruction method that applies the hierarchical Bayesian algorithm to the source modal coefficient solution. Firstly, the deconvolution beamforming method obtains the sound source position. Subsequently, the hierarchical Bayesian algorithm is employed to obtain the source modal coefficients of the sound field, thereby completing the reconstruction of the sound field in the far-field region. Experimental results indicate that the proposed algorithm is highly effective in reconstructing far-field sound fields. Under free-field conditions and in mid-high frequency ranges, the average reconstruction error can be significantly reduced by using a few far-field microphones compared to traditional methods.</p></div>\",\"PeriodicalId\":36309,\"journal\":{\"name\":\"Aerospace Systems\",\"volume\":\"8 2\",\"pages\":\"257 - 274\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-02-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aerospace Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s42401-025-00345-1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aerospace Systems","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s42401-025-00345-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
Sound field reconstruction of aero-engine fans using hierarchical Bayesian algorithms
Acoustic field reconstruction for aircraft engine fans is essential for effective noise reduction. However, the use of a limited number of far-field measurement points in the reconstruction process exacerbates the ill-posedness issues, which necessitates the adoption of regularization techniques. The hierarchical Bayesian-based regularisation method has recently been applied to solve the equivalent source intensity distribution and reconstruct the sound field. However, previous methods have failed to accurately obtain the acoustic modal coefficients of the sound source, which are essential for determining the radiation type and directivity. This paper proposes a sound field reconstruction method that applies the hierarchical Bayesian algorithm to the source modal coefficient solution. Firstly, the deconvolution beamforming method obtains the sound source position. Subsequently, the hierarchical Bayesian algorithm is employed to obtain the source modal coefficients of the sound field, thereby completing the reconstruction of the sound field in the far-field region. Experimental results indicate that the proposed algorithm is highly effective in reconstructing far-field sound fields. Under free-field conditions and in mid-high frequency ranges, the average reconstruction error can be significantly reduced by using a few far-field microphones compared to traditional methods.
期刊介绍:
Aerospace Systems provides an international, peer-reviewed forum which focuses on system-level research and development regarding aeronautics and astronautics. The journal emphasizes the unique role and increasing importance of informatics on aerospace. It fills a gap in current publishing coverage from outer space vehicles to atmospheric vehicles by highlighting interdisciplinary science, technology and engineering.
Potential topics include, but are not limited to:
Trans-space vehicle systems design and integration
Air vehicle systems
Space vehicle systems
Near-space vehicle systems
Aerospace robotics and unmanned system
Communication, navigation and surveillance
Aerodynamics and aircraft design
Dynamics and control
Aerospace propulsion
Avionics system
Opto-electronic system
Air traffic management
Earth observation
Deep space exploration
Bionic micro-aircraft/spacecraft
Intelligent sensing and Information fusion