Feng Zhu Jie, Lin Tian Ran, Cheng Li
Qingdao Key Rail Transportation Centre for Noise and Vibration Control & Automated Fault Diagnostic, Qingdao University of Technology, China.
Department of Mechanical Engineering, Hong Kong Polytechnic University, Hong Kong, China.
J Acoust Soc Am. 2023 Dec 1;154(6):3851-3867. doi: 10.1121/10.0022574.
An adaptive variable step-size algorithm is proposed in this paper to address the impact of the real-time acoustic feedback and the real-time secondary path identification on the overall noise reduction performance of an active noise control system. An automated adjustment weight factor is introduced in the algorithm to accelerate the convergence of the acoustic feedback path as well as the secondary path identification, and to prevent possible system divergence. It is shown in this study that the proposed algorithm can resolve the trade-off between a fast convergence and a low misalignment of the virtual and the actual control paths typically found in conventional algorithms. An optimized control structure is also proposed in the study by enabling an adaptive gain adjustment based on the output of the auxiliary filter to enhance the practicality of the control system. The effectiveness of the algorithm is tested using two simulated multi-component signals and a broadband noise signal, and the results confirm that the proposed algorithm can achieve a good noise reduction with only a few iterations.
本文提出了一种自适应变步长算法,以解决实时声学反馈和实时次级路径识别对有源噪声控制系统整体降噪性能的影响。该算法引入了一个自动调整权重因子,以加速声学反馈路径以及次级路径识别的收敛,并防止可能的系统发散。本研究表明,所提出的算法可以解决传统算法中通常存在的虚拟控制路径与实际控制路径快速收敛和低失准之间的权衡问题。该研究还通过基于辅助滤波器的输出进行自适应增益调整,提出了一种优化的控制结构,以提高控制系统的实用性。使用两个模拟的多分量信号和一个宽带噪声信号对该算法的有效性进行了测试,结果证实所提出的算法只需几次迭代就能实现良好的降噪效果。