摘要
在阐述小波变换原理的基础上介绍了两种局部放电检测的软阈值去噪方法:即Stein无偏风险阈值法和平均阈值法,并利用MATLAB对加入白噪声的局部放电信号模型进行仿真研究。结果表明,Stein无偏风险阈值法对单指数振荡局部放电模型消噪效果好,但是对于其它3种局放模型波形失真严重,滤噪效果较差;利用平均阈值法能更好地实现从白噪声干扰中提取原信号。
The decomposition and reconstruction algorithm of two wavelet threshold de-noising methods, Stein unbiased risk estimation and average estimation for partial discharge （PD） detection were introduced. The MATLAB simulation on PD signals added with white noises was studied in this paper. The simulation results show that the method based on Stein unbiased risk estimation has a good effect on the de-noising of single index oscillation PD models, but the waves of other three PD models are seriously distorted and the effects of de-noising are weak. With the help of average estimation method, original signals can be extracted better from white noise interference.
出处
《绝缘材料》
CAS
2008年第6期67-71,共5页
Insulating Materials
关键词
小波变换
局部放电
软阈值去噪
MATLAB仿真
wavelet transform
partial discharge
soft threshold de-noising
MATLAB simulation
