摘要
通过分析Hilbert-Huang变换(HHT)的核心经验模态分解(empirical mode decomposition,EMD)算法及其实现过程,提出了基于EMD算法的数据压缩消噪。运用仿真模型信号和实验信号对提出地消噪算法效果进行验证;对同样条件下的数据源,与基于db2小波、db8小波的数据压缩消噪的效果进行了分析比较。此外,运用研制地硬件系统,在重庆某电机厂进行实验,采集在电机运行地真实环境下局部放电超声信号,并对其进行基于EMD算法、db2小波和db8小波数据压缩消噪分析和比较。仿真和实验结果分析表明,基于EMD算法的数据压缩消噪,与基于db2小波、db8小波的数据压缩消噪能达到同样的消噪效果,甚至更优,而且不损耗原信号能量;在对真实信号处理方面,前者更优于后者。
Empirical mode decomposition（EMD） algorithm is introduded as the core of the Hilbert-huang transform（HHT）,and implementation process of EMD is analyzed.Then data compression denoising algorithm based on EMD is proposed,simulation and experimental signals are used for verification of the effect of EMD.In the same data sources,the comparison of data compression denoising approaches based on the EMD,db2 wavelet and db8 wavelet are conducted.In addition,physical experiment of the same analysis and comparisons are conducted on a running motor in a Chongqing electrical plant.Simulation and experimental results show that data compression denoising algorithm based on EMD can achieve the same denoising effect,or even better than based on db2 wavelet,db8 wavelet.The former is more perfect than the latter in the real signal processing,and denoising based on EMD is not loss of the original signal energy.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2011年第10期15-20,共6页
Journal of Chongqing University
基金
国家自然科学基金资助项目(50877081)
输配电装备及系统安全与新技术国家重点实验室自主研究项目(2007DA10512709206)
