摘要
针对现有信号去噪方法的不足,采用总体经验模态分解EEMD(ensemble empirical mode dcomposition)方法对变压器局部放电信号进行消噪,并将其与小波消噪方法进行对比。由于EEMD本身的分解性质及计算机性能的限制,使得对于高采样率长信号的消噪处理变得很困难,故此提出将矩形窗与EEMD算法结合起来进行去噪。研究表明EEMD去噪方法更适合于变压器的局部放电去噪,加矩形窗的EEMD去噪方法通过时间复杂度分析和实验验证,更适合此类局部放电信号的去噪。
To deal with the shortcomings of existing denoising methods,the ensemble empirical mode dcomposition（EEMD）de-noising method is applied to denoise the partial discharge signal of the transformer. Which is compared with the conventional wavelet based de-noising algorithms. Due to the restrictions of EEMD decomposition and the performance of computer,it becomes very difficult to denoise the high sampling rate signals with long time. Rectangular window is introduced here to be combined with EEMD algorithms to denoise the discharge signals. As a general result of the research,EEMD de-noising method is better than wavelet based de-noising. The time complexity analysis and experimental verification are shown that with rectangular window the EEMD de-noising method is more suitable for the high sampling rate signal.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2015年第3期54-58,共5页
Proceedings of the CSU-EPSA
基金
新能源电力系统国家重点实验室资助项目
关键词
局部放电
信号去噪
经验模态分解
矩形窗
小波去噪
partial discharge
signal denoising
empirical mode decomposition（EMD）
rectangular window
wavelet based de-noising
