基于波束形成的货车通过噪声声源识别

Identification of Truck Noise Sources under Passby Condition Based on Beamforming Method

基于互谱延迟求和波束形成理论,设计声源识别算法,开发相应软件,已知单声源、不相干声源、相干声源的模拟计算结果表明:相比于全互谱波束形成,除自谱的互谱波束形成可以在保证主瓣峰值不变的前提下降低旁瓣水平,提高声源识别精度。某货车的通过噪声声源识别试验表明:发动机为主要噪声源,为制定有效的降噪方案提供一种解决思路。

A sound source identification algorithm was designed based on cross-spectral delay and sum beamforming principle. The corresponding software was developed. Some known sources were simulated and calculated, which consisted of a single source, two incoherent sources and two coherent sources. Results show that peak of mainlobe can keep unchanged and sidelobes can be suppressed effectively by excluding the auto-spectral elements from the cross-spectral matrix, so the accuracy of sound source identification is improved. On that basis, an identification experiment of truck noise sources under passby condition was conducted. Results show that engine is the dominant noise source, which provides a guide for the establishment of the effective noise reduction scheme.