现代信息科技2024，Vol.8Issue(1)：77-83,7.DOI:10.19850/j.cnki.2096-4706.2024.01.016
基于变分模态分解和稀疏表示的局部放电信号去噪算法
Partial Discharge Signal Denoising Algorithm Based on Variational Modal Decomposition and Sparse Representation
钟俊 1刘桢羽 1赵晓坤 2唐妮妮 2毕潇文1
作者信息
- 1. 四川大学 电气工程学院,四川 成都 610065
- 2. 国网成都供电公司,四川 成都 500642
- 折叠
摘要
Abstract
Considering the interference of various noises on partial discharge signals,this paper proposes a partial discharge signal denoising algorithm based on variational modal decomposition and sparse decomposition.Based on the characteristics of partial discharge signals,the sparse representation algorithm is used as the core to construct an overcomplete dictionary,and then the matching and tracking algorithm is used to search for the best matching atomic set of the original signal in the overcomplete dictionary to reconstruct the signal;to solve the problem of excessive search times caused by excessive dimensionality in an overcomplete dictionary,the variational modal decomposition algorithm and kurtosis value screening are introduced for preprocessing and pre reconstruction;the optimized method can limit the search range and dictionary parameters of the sparse decomposition algorithm to reduce computational complexity.Simulation verification and denoising results on measured signals in engineering environments show that this method has better denoising effects,and can still extract effective partial discharge signals even in extremely low signal-to-noise ratios.关键词
局部放电信号/变分模态分解/峭度/稀疏表示/机器学习/匹配追踪算法/自适应Key words
partial discharge signal/variational modal decomposition/kurtosis/sparse representation/Machine Learning/matching and tracking algorithm/self-adaption分类
信息技术与安全科学引用本文复制引用
钟俊,刘桢羽,赵晓坤,唐妮妮,毕潇文..基于变分模态分解和稀疏表示的局部放电信号去噪算法[J].现代信息科技,2024,8(1):77-83,7.
