基于比例归一化LMS算法次级通道模型辨识

Secondary Path Identification Method Based on Proportionate Normalized LMS Algorithm

将主动噪声控制技术应用于地铁通风隧道的噪声控制上,其应用效果在很大程度上取决于信号处理的实时性。在保证控制算法收敛的基础上,要求算法收敛速度尽可能快,以确保对声波变化的准确跟踪,据此产生匹配的振幅相等、相位相反的次级声信号,进而对噪声进行控制。利用比例思想对LMS算法进行改进,为小系数配上小的步长因子,为大系数配上较大的步长因子。最后,将其应用在地铁通风隧道的次级声通道模型的辨识上,并与常用的LMS算法在收敛速度、稳态失调性能上做出比较。数值分析结果表明,采用改进后的LMS算法能够有效地加快算法收敛,改善算法的稳态失调性能。

When the active noise control technology is applied to the noise control of subway ventilation tunnels,the application effect depends largely on the real-time requirements of signal processing.On the basis of ensuring the convergence of the control algorithm,the convergence speed of the algorithm is required to be as fast as possible to accurate tracking the change of sound waves,it can adapt itself to changing characteristics of the noise to be cancelled and changing environment conditions that affect the acoustic field.The proportionate normalized LMS algorithm is improved by using the proportion idea with small step factors for small coefficients and large step factors for large coefficients.Finally,it is applied to the identification of the secondary path modeling of the subway ventilation tunnel,and compared with the LMS algorithm and the normalized LMS algorithm in the convergence speed and steady-state offset performance.The numerical analysis results show that the improved LMS algorithm can effectively accelerate the convergence of the algorithm and improve the steady-state offset performance of the algorithm.