摘要
针对常规降噪方法应用于柴油机缸盖振动信号降噪时,自适应差且需要根据噪声环境人为调整参数的问题,在传统EEMD算法基础上提出一种改进的EEMD降噪算法,并将其应用于柴油机缸盖振动信号处理。首先对原始信号进行预处理,其次利用总体经验模态分解(EEMD)算法在非线性、非平稳信号处理时的自适应特性,分解原始信号得到各阶本征模态分量,经Savitzky-Golay平滑滤波,再将噪声占主导的高频分量进行阈值去噪,最后得到干净的本征模态分量进行重构。仿真实验和实测结果表明,在输入信号12dB的多种输入信号工况下,改进EEMD算法去噪后信噪比为17.1,比现有去噪方法提升14%。
In order to solve the problem that the conventional noise reduction method is not adaptive to the vibration signal of diesel en⁃gine cylinder head and the parameters need to be adjusted artificially according to the noise environment,this paper proposes an im⁃proved EEMD noise reduction algorithm based on the traditional EEMD algorithm,which is applied to the vibration signal processing of diesel engine cylinder head.Firstly,the original signal is preprocessed.Secondly,the adaptive characteristics of EEMD algorithm in nonlinear and non-stationary signal processing are used to decompose the original signal to get the eigenmode components of each or⁃der.After savitzky Golay smooth filtering,the high-frequency components dominated by noise are threshold denoised,and finally the clean eigenmode components are reconstructed.The simulation and experimental results show that the signal-to-noise ratio is 17.1 when the input signal is 12dB,compared with the existing denoising methods,the signal-to-noise ratio is increased by 14%.
作者
林传喜
刘维亭
张懿
魏海峰
周啸伟
LIN Chuan-xi;LIU Wei-ting;ZHANG Yi;WEI Hai-feng;ZHOU Xiao-wei(Jiangsu University of Science and Technology,Zhenjiang 212003,China;Changshu Rhett Electric Co.,Ltd Changshu,Changshu 215500,China)
出处
《软件导刊》
2020年第11期159-163,共5页
Software Guide
基金
国家自然科学基金项目(51977101)
江苏省重点研发计划(产业前瞻与共性关键技术)项目(BE2018007)。
