摘要
在窄带主动噪声控制系统中,由非声学传感器或信号发生器误差引起的频率不匹配(FM)及噪声信号自身的非平稳性会极大降低系统的降噪性能。对此结合2阶自回归(AR)模型,提出一种基于自适应函数链人工神经网络(FLANN)的FM应对方法。仿真分析表明,在噪声信号频率连续变化情形下,窄带噪声能够得到抑制,验证了该方法应对FM的有效性,同时具有较快的收敛速度。
In the narrowband active noise control system,the noise reduction performance will be greatly reduced by the large nonstationary frequency mismatch(FM),which is caused by the non-acoustic sensor ′ s aging or the error of the signal generator.In this paper,a new FM compensation method combined with a functional link artificial neural network(FLANN) based on the second order adaptive regression model was proposed.The simulation results show that in the circumstances of the continuous change of the noise signal frequency,the narrowband noise can be suppressed with a fast convergence rate,which verified the effectiveness of the method in dealing with the FM problem.
作者
王枝鑫
刘剑
WANG Zhixin;LIU Jian(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;Nondestructive Detection and Monitoring Technology for High Speed Transportation Facilities,Key Laboratory of Ministry of Industry and Information Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)
出处
《噪声与振动控制》
CSCD
北大核心
2022年第6期73-78,87,共7页
Noise and Vibration Control
基金
中央高校基本科研业务费资助项目(NJ2020014)。
关键词
声学
主动噪声控制
窄带
频率不匹配
非平稳
FLANN
acoustics
active noise control
narrowband
frequency mismatch(FM)
nonstationary
FLANN
