提高发动机排气有源消声系统中次级通道辨识精度的方法与实验研究

Analysis and Experiment of a Method to Improve the Secondary Path Modeling Accuracy of the Adaptive Active Control System for Engine Exhaust Noise

在发动机排气自适应有源消声系统中的次级通道的辨识环节引入自适应线性增强器(ALE),通过理论分析和计算机仿真考察ALE对次级通道辨识精度及系统性能的影响,改进了次级通道辨识算法,并编制了相应的控制系统程序。在自行研制的实验台上进行了自适应离线、抖动信号自适应在线、以及使用ALE的抖动信号自适应在线3种次级通道辨识方法的对比实验,结果表明:应用改进后的辨识算法,能够减小次级通道传递函数估计的失真,提高次级通道的辨识精度,加快系统的收敛速度,并降低系统对外加抖动信号的功率要求。通过对铃木AX-100摩托车发动机排气噪声的有源消声实验表明,提出的发动机排气有源消声系统能够有效消除噪声源中的窄带成分,提高系统整体降噪效果。

An adaptive line enhancer （ALE） was introduced into the secondary path identification part of the adaptive active control system for engine exhaust noise. The modeling accuracy of the secondary path is greatly improved, and an additional transfer function of the secondary path is introduced. An improved algorithm was put forward, and theoretical analysis, computer simulation and experimental set-up of this method were implemented. Comparative experiments were carried out using this method against the offline adaptive modeling method and the dither noise excited online modeling method. Experimental results showed that the online modeling technique with ALE and the updated adaptive algorithm had greatly decreased the deformation of the secondary path estimation, improved the estimation accuracy, accelerated the convergence speed of the control system, and lowered the need of the pseudo signal power for the secondary path modeling. A test on SUZUKI AX-100 motorcycle engine exhaust noise by active noise control （ANC） was carried out. The results showed that the proposed ANC system could greatly eliminate the narrowband components of the noise source, and improve the whole reduction in noise.