摘要
实现噪声控制的前提是正确识别出主要的噪声源,研究噪声源空间指向性对于噪声源的辨识和预测有重大意义。为提高复杂声源的分辨率,以单极子点源形成扩展性声源表征噪声源,引进广义逆波束形成算法对扩展性声源进行声源定位。通过仿真计算,分析了广义逆波束形成(Generalized Inverse Beamforming,GIB)算法中麦克风阵列阵元数、测量距离对定位效果的影响,系统比较了去自谱算法和GIB算法对点声源、扩展性声源(5个紧密相连的单极子点源)的分辨率。仿真表明:GIB算法中定位效果受阵元数目影响不大,相对提高了点声源的定位精度,而且能分辨出扩展性声源。
The essential requirement for noise control is to identify the noise sources accurately. The space directivities of these noises play important roles in the acoustic sources identification and prediction. To improve the space resolution of noise-source maps, the extended acoustic source (which consists of some monopole sources in a certain shape) is used to model the noise-source. The generalized inverse beamforming (GIB) algorithm is performed to discriminate the complex extended acoustic sources. Based on the simulation, the performances of GIB algorithm are discussed, such as the rela-tionship between sound sources identification performance and the number of microphones, the influence of measuring distance, the space resolution of GIB. Then the extended autospectra algorithm and GIB algorithm were compared by the identification of point source, extended sources (multiple monopole sources were closely placed). The result shows that the identification performance of GIB algorithm is not easy to be influenced by the number of microphone array. Compared with autospectra algorithm, the better performance of point sources and extended sources localization was gained.
出处
《声学技术》
CSCD
北大核心
2015年第4期368-373,共6页
Technical Acoustics
基金
国家自然科学基金项目(51275498)
质检公益性行业科研专项(201410027
201410028)资助
关键词
扩展性声源
广义逆波束形成
去自谱算法
声源定位
extended acoustic sources
generalized inverse beamforming
autospectra algorithm
sources identification