基于SVD-DTCWT的局部放电信号提取方法
Partial discharge signal extraction method based on SVD-DTCWT
马星河 1张颖 1许丹 1张登奎 1朱昊哲2
作者信息
- 1. 河南理工大学电气学院,河南焦作 454003
- 2. 南水北调中线建管局河南分局,河南郑州 450016
- 折叠
摘要
针对局部放电(partial discharge,PD)信号易埋没在噪声中难以提取的问题,提出一种基于奇异值分解(singular value decomposition,SVD)和双树复小波变换(dual-tree complex wavelet transform,DTCWT)的降噪方法.该方法首先使用基于K-means聚类算法的奇异值分解抑制窄带干扰,然后对重构信号进行双树复小波多尺度变换,利用改进阈值函数对实部树、虚部树产生的每层小波系数和最高层的尺度系数分别进行处理,最后经过双树复小波逆变换得到去噪后的PD信号.仿真和实验结果表明:该方法能有效抑制白噪声和窄带干扰,去噪后的信号波形相似度高.
Abstract
In order to solve the problem that partial discharge(PD)signals are easily drowned in noise and difficult to extract,a new partial discharge noise de-noising algorithm based on dual-tree complex wavelet transform(DTCWT)and singular value decomposition(SVD)is proposed.In this method,SVD based on K-means clustering algorithm is used to select singular value reconstruction to suppress narrowband interference.Then,the reconstructed signal is multi-scalely transformed by DTCWT.The improved threshold function(ITF)is used to process the wavelet coefficients of each layer and the scale coefficients of the top layer generated by the real part tree and the imaginary part tree respectively.Finally,the de-noised local amplifier signal is obtained by inverse dual-tree complex wavelet transform.The analysis results of simulated and measured signals show that the method can effectively suppress white noise and narrowband interference,and the signal waveform similarity after de-noising is higher.
关键词
局部放电/双树复小波变换/改进阈值函数/奇异值分解Key words
partial discharge/dual-tree complex wavelet transform/improved threshold function/singular value decomposition引用本文复制引用
基金项目
河南省科技攻关项目(182102310936)
河南省自然科学基金(182300410280)
出版年
2024
NETL
NSTL
维普
万方数据