EMD改进算法的车内风噪提取及主动控制研究
Implementing specific required noise processing in emd active noise reduction algorithm
顾庭箐 1何陆耀 1闵佳艳 1崔怀峰1
作者信息
- 1. 宁波工程学院,浙江 宁波 315000
- 折叠
摘要
针对客户对车内噪声的抱怨较多,尤其是风噪和路噪的问题,提出一种经验模态分解(EMD)的改进算法,主要通过极值点选取方式的改进以获得更稳定的本征模态函数(IMF),并通过比较分解后本征模态函数与纯净风噪的相关系数拟合度,重构混合信号中的风噪进行主动噪声控制,从而达到对特定噪声降噪,保留其余有用的声音.此方法能够较高精度提取风噪特征,为风噪控制提供参考信号,从而实现有效降噪,提高车内乘员的乘坐舒适性,形成汽车的品牌效应,增强汽车在国内外市场中的竞争力.
Abstract
To solve complaints from customers about the noise inside the car,especially wind noise and road noise,Proposing an improved algorithm for Empirical Mode Decomposition(EMD),which mainly improves the selection of extremum points to obtain a more stable Intrinsic Mode Function(IMF).By comparing the fitting degree of the correlation coefficient between the decomposed IMF and pure wind noise,the wind noise in the mixed signal was reconstructed for active noise control,thereby achieving noise reduction for specific noise and preserving other useful sounds.This method could extract wind noise features with high accuracy,provide reference signals for wind noise control,and achieve effective noise reduction,thereby improving the comfort of passengers in the car,forming a brand effect of the car,and enhancing the competitiveness of the car in domestic and foreign markets.
关键词
经验模态分解/汽车声音/主动降噪/特征提取Key words
Empirical Mode Decomposition/car sound/active noise reduction/feature extraction引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据