Microphone array method for the reliable experimental characterization of sound sources for noise control

用于噪声控制声源可靠实验表征的麦克风阵列方法

• 批准号: 254799420
• 负责人: Professor Dr.-Ing. Ennes Sarradj
• 金额: --
• 依托单位: Fachgebiet Technische Akustik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2014
• 资助国家: 德国
• 起止时间: 2013-12-31 至 2017-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/254799420?language=en
• 关键词: Microphone; array; method; reliable; experimental

The comprehensive and reliable characterization of sound sources is of great importance in the development of noise control techniques that focus on the sound sources and aim to prevent the generation of disturbing sound. A tool that is frequently employed for that characterization is the parallel application of multiple microphones (microphone array) in combination with appropriate processing methods. In principle, this enables the information on the location, strength and directivity of multiple sources and on the coherence of their signals to be obtained at the same time. However, the different processing methods that are currently applied have a number of limitations. No method does provide all of the necessary information. Moreover, in practical applications the results of the different methods deviate and are therefore of limited value. Thus, the basic objective of this research project is a contribution to the reliable experimental characterization of sound sources using microphone arrays. To this end, three different approaches are to be pursued and novel processing methods will be elaborated. These methods are to be evaluated with the help of a Monte Carlo based procedure that will be further developed within the project. The foreseen result is a method, that is validated both theoretically and experimentally and is able to deliver information about the three-dimensional spatial distribution of sound sources and enables the simultaneous, frequency-dependent measurement of their strength, directivity and coherence while also providing information about the reliability of the results.

声源的全面、可靠的表征对于开发专注于声源并旨在防止干扰声音产生的噪声控制技术具有重要意义。经常用于表征的工具是并行应用多个麦克风（麦克风阵列）并结合适当的处理方法。原则上，这使得能够同时获得有关多个源的位置、强度和方向性及其信号相干性的信息。然而，目前应用的不同处理方法具有许多局限性。没有一种方法可以提供所有必要的信息。而且，在实际应用中，不同方法的结果存在偏差，因而价值有限。因此，该研究项目的基本目标是为使用麦克风阵列对声源进行可靠的实验表征做出贡献。为此，将寻求三种不同的方法并详细阐述新颖的处理方法。这些方法将在基于蒙特卡罗的程序的帮助下进行评估，该程序将在项目中进一步开发。预见的结果是一种经过理论和实验验证的方法，能够提供有关声源三维空间分布的信息，并能够同时、频率相关地测量其强度、方向性和相干性，同时还提供有关结果可靠性的信息。

项目成果

A Python framework for microphone array data processing

• DOI: 10.1016/j.apacoust.2016.09.015
• 发表时间: 2017-01
• 期刊: Applied Acoustics
• 影响因子: 3.4
• 作者: E. Sarradj;G. Herold

Comparison of Inverse Deconvolution Algorithms for High-resolution Aeroacoustic Source Characterization

• DOI: 10.2514/6.2017-4177
• 发表时间: 2017-06
• 作者: G. Herold;T. Geyer;E. Sarradj

A Microphone Array Method Benchmarking Exercise using Synthesized Input Data

• DOI: 10.2514/6.2017-3719
• 发表时间: 2017-06
• 作者: E. Sarradj;G. Herold;P. Sijtsma;R. M. Martínez;A. Malgoezar;M. Snellen;T. Geyer;C. Bahr;R. Porte

Performance analysis of microphone array methods

• DOI: 10.1016/j.jsv.2017.04.030
• 发表时间: 2017-08
• 期刊: Journal of Sound and Vibration
• 影响因子: 4.7
• 作者: G. Herold;E. Sarradj

Sparse $$\ell _{1}$$ℓ1 regularisation of matrix valued models for acoustic source characterisation

• DOI: 10.1007/s11081-017-9357-2
• 发表时间: 2016-07
• 期刊: Optimization and Engineering
• 影响因子: 2.1
• 作者: Laurent Hoeltgen;M. Breuß;G. Herold;E. Sarradj