首页|惩罚函数波束形成声源识别算法及应用研究

惩罚函数波束形成声源识别算法及应用研究

扫码查看
在基于传声器阵列的噪声源识别应用中,函数波束形成算法存在空间分辨率的性能瓶颈,为此提出惩罚函数波束形成声源识别算法。以归一化后的函数波束形成输出作为惩罚矩阵,计算其与加权矩阵的Hadamard积,调节加权矩阵中的导向向量;利用调节后的导向向量与互谱指数函数,计算惩罚函数波束形成输出,以此更新惩罚矩阵并实施迭代运算。通过惩罚迭代,可使点扩散函数接近狄拉克函数,改善空间分辨率性能。仿真和试验结果表明,所提算法的波束主瓣窄、旁瓣低,可有效解决函数波束形成算法空间分辨率不理想的问题。在压缩气体泄漏声源识别应用中,算法有效抑制了噪声干扰、缩减主瓣,表明其具有较好的工程应用前景。
Penalty function beamforming sound source identification algorithm and its application
In application of noise source identification based on microphone arrays,the function beamforming algorithm has performance bottleneck of spatial resolution.Here,a penalty function beamforming sound source identification algorithm was proposed.The normalized function beamforming output was taken as penalty matrix,Hadamard product between it and weighting matrix was calculated to adjust steering vector in weighting matrix.Using the adjusted steering vector and cross-spectral exponential function,penalty function beamforming output was calculated to update penalty matrix and perform iterative operations.Through punishing iterations,the point spread function could be made to be close to Dirac function,and improve spatial resolution performance.Simulation and experimental results showed that the proposed algorithm's beam has a narrow main lobe and low side lobes to be able to effectively solve the problem of poor spatial resolution in the function beamforming algorithm;in application of compressed gas leakage sound source recognition,the proposed algorithm can effectively suppress noise interference and reduce main lobe to exhibit its better engineering application prospects.

sound source identificationfunction beamformingpenalty matrixcross-spectral matrixnormalization

赵慎、李伟、覃业梅、周开军、李世玲、石少锦

展开 >

湖南工商大学智能工程与智能制造学院,长沙 410205

湘江实验室,长沙 410205

声源识别 函数波束形成 惩罚矩阵 互谱矩阵 归一化

2025

振动与冲击
中国振动工程学会 上海交通大学 上海市振动工程学会

振动与冲击

北大核心
影响因子:0.898
ISSN:1000-3835
年,卷(期):2025.44(1)