摘要
为对变压器有载分接开关机械故障进行诊断,提出一种结合奇异值分解SVD(singular value decompo-sition)消噪与小波包WP(wavelet packet)消噪的信号特征提取方法。首先对信号进行小波包消噪,然后进行SVD二次消噪,将消噪信号进行经验模态分解EMD(empirical mode decomposition),对得出的各阶固有模态分量进行希尔伯特-黄变换HHT(Hilbert-Huang transform)。数值仿真表明基于WP_SVD降噪的信号特征提取比小波包或SVD单独降噪的信号特征提取方法有效,并成功地将该方法应用到分接开关实际振动信号分析中。
In order to diagnose transformer on-load tap changer mechanical fault, this paper proposes a kind of signal feature extraction method combining singular value decomposition（SVD） de-noising and wavelet packet （WP） de-noising. The noise of vibration signal is eliminated firstly by wavelet packet and secondly by SVD. And it is then decomposed by empirical mode clescomposition（EMD） to get the intrinsic mode components and transformed by hilbert-Huang transformation（HHT）. Numerical simulation shows that the signal feature extraction based on WP_SVD de-nosing is more effective than the signal feature extraction based on WP or SVD de-noising separately. The method is successfully applied to the analysis of the actual vibration signal of OLTC.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2012年第5期36-41,共6页
Proceedings of the CSU-EPSA
基金
江苏省电力公司重点科技资助项目(J2008039)
关键词
奇异值分解
小波包
经验模态分解
希尔伯特-黄变换
有载分接开关
振动信号
singular value discomposition （SVD）
wavelet packet （WP）
empirical mode clescomposition（EMD）
Hilbert-Huang transform（HHT）
on-load tap changer（OLTC）
vibration sign
