摘要
为减轻一线作业工人受到的噪声聋困扰,针对工业强噪声控制问题,提出了一种使用最大相关熵准则改进的前反馈混合结构主动噪声控制方法(MCC-HANC结构算法)。为克服传统混合结构前馈部分与反馈部分耦合、误差和参考信号不准确以及整体系统不易收敛等问题,并考虑到冲压车间高强度脉冲噪声的声学特性,提出基于最大相关熵准则的误差分离部分,将其引入传统混合主动噪声控制系统中。采用3种结构算法(AMHANC、PaHANC、MCC-HANC)对工厂车间实采数据(冲击噪声和平稳噪声)进行了实验对比研究。实验结果表明,相比AMHANC、PaHANC结构算法,在工厂车间环境下使用MCC-HANC结构算法,可以在保证计算复杂度不太高的情况下具有良好的降噪效果,降噪速度最快,平均降噪量最优,且具有较快的拟合速度和较好的拟合效果。
To alleviate the noise-induced hearing loss among frontline workers,this paper proposes an improved feedforward-feedback Hybrid Active Noise Control(HANC)method using the Maximum Correntropy Criterion(MCC)to address industrial high-noise control issues.Aiming to address the limitations of conventional HANC—including coupling between the feedforward and feedback parts,signal inaccuracy,and poor convergence—while considering the acoustic characteristics of high-intensity pulsed noise in stamping workshops,the paper introduces an MCC-based error separation module into the HANC framework.The proposed MCC-HANC method is evaluated against two benchmark HANC algorithms(AMHANC and PaHANC)using real-world workshop data containing both impulsive and stationary noise components.Experimental results demonstrate that the proposed MCC-HANC algorithm achieves the best overall performance.It offers the fastest convergence rate,superior fitting capability,and an optimal average noise reduction,while maintaining computational complexity comparable to the benchmarks.
作者
王东圣
赵金涛
王冬霞
WANG Dongsheng;ZHAO Jintao;WANG Dongxia(School of Automation and Electrical Engineering,Tianjin University of Technology and Education,Tianjin 300222,China;Tianjin Key Laboratory of Information Sensing and Intelligent Control,Tianjin 300222,China)
出处
《天津职业技术师范大学学报》
2025年第4期27-33,48,共8页
Journal of Tianjin University of Technology and Education
基金
天津市科技计划项目(24KPXMRC00050)。
关键词
工业强噪声控制
混合主动噪声控制
最大相关熵准则
误差分离系统
强噪声环境
噪声聋防护
industrial noise control
hybrid active noise control(HANC)
maximum correntropy criterion(MCC)
error separation system
high noise environment
hearing protection
