近场波束形成声源识别的改进算法

    Improved algorithm of near-field beamforming for sound source identification

    • 摘要: 为提高近场波束形成方法的声源识别性能和阵列平面上最大声压贡献量的计算精度,首先基于球面波假设,采用除自谱的互谱波束形成算法,仿真分析了阵列传声器信号幅值校正对声学成像和声源识别的影响,结果表明:幅值的校正在提高阵列平面上最大声压贡献量计算精度的同时也带来了旁瓣水平增大,动态范围缩小等诸多不足。在此基础上,提出并设计了声源定位与强度幅值校正相结合的近场波束形成阵列平面声压贡献量的改进算法,仿真分析与算例试验结果均表明:改进算法既能准确计算阵列平面上的最大声压贡献量,且旁瓣水平低,声源成像动态范围增大1.0~1.6dB。最后,利用改进算法进行了某车的声学密封性能试验,准确识别了该车的声学密封薄弱位置。

       

      Abstract: In order to improve the sound source identification performance of near-field beamforming and the calculation accuracy of maximum sound pressure contribution on the array plane, the influence of array microphone signal amplitude correction to acoustical imaging and sound source identification was analyzed by using the cross- spectra beamforming algorithm with auto-spectra exclusion based on the assumption of spherical wave. The results indicated that the calculation accuracy of the maximum sound pressure contribution on the array plane was improved, and some shortages such as the increase of the maximum side-lobe level and the reduction of the dynamic range were come out in the meantime. Ulteriorly, the improved near-field beamforming algorithm for the calculation of the sound pressure contribution on the array plane was put forward. Both results of simulation and the experiments showed that the improved algorithm could calculate the maximum sound pressure contribution accurately, and the dynamic range was increased 1.0-1.6 dB. Finally, the acoustical sealed performance test for a car was carried out by using the improved algorithm. The weak positions of the acoustical seal were identified precisely.

       

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