次级声源优化布放的局部空间有源降噪

针对区域有源降噪问题，为获得更优降噪效果，根据实际次级通路传递函数，提出次级声源优化布放的有源控制系统并详细比较了两种次级声源优化布放算法与次级声源均匀布放的实际降噪效果。应用的第一种次级声源优化算法是l2范数约束的约束匹配追踪算法，第二种次级声源优化算法是l1范数约束的稀疏正则化方法。在全消声室中利用扬声器线阵进行多通道有源降噪实验研究，实验结果表明，在200~1000 Hz，次级声源优化布放的控制系统的平均降噪量比次级声源均匀布放的控制系统的平均降噪量多5 dB左右；在1100~1900 Hz，次级声源优化布放的控制系统的平均降噪量比次级声源均匀布放的控制系统的平均降噪量多11~13 dB左右，次级声源优化布放的控制系统的降噪量分布更加均匀且次级声源输出能量更小。此外，两种优化算法中，稀疏正则化方法的降噪效果更佳。

Local active noise control with the optimized secondary source placement

For local active noise control, an active noise control system with the optimized secondary source placement based on the actual secondary path transfer function is presented in this paper. The control system is used to achieve a better control performance. The actual control performance of the system using two optimal algorithms and the system using the uniformly placed secondary sources are compared in detail in this paper. The first method is the constrained matching pursuit algorithm with l2 norm constraint. The second method is a sparsity-inducing regularization strategy with l1 norm constraint. The multi-channel active noise control experiment is carried out using a loudspeaker line array in an anechoic chamber. The experiment illustrates that compared to the system using uniformly placed secondary sources, from 200 Hz to 1000 Hz, the system using the optimal algorithms provides about 5 dB average noise reduction advantage and from 1100 Hz to 1900 Hz, the system using the optimal algorithms provides about 11 dB-13 dB average noise reduction advantage. The control system based on optimal algorithms has a lower power of secondary sources and the noise reduction is distributed more uniformly. Moreover, among the two optimal algorithms, the sparsity-inducing regularization method has a better control performance.