电力系统自动化2017，Vol.41Issue(20)：63-69,91,8.DOI:10.7500/AEPS20170327001
基于经验小波变换的变压器振动信号特征提取
Feature Extraction for Vibration Signals of Power Transformer Based on Empirical Wavelet Transform
摘要
Abstract
In order to realize effective feature extraction for vibration signals of power transformers,a method of signal feature extraction based on empirical wavelet transform (EWT) is proposed.Firstly,transformer vibration signals in different working conditions are decomposed into several empirical wavelet functions (EWFs) through the method of EWT.Secondly,the Hilbert spectrum of each EWF is calculated,and the frequency characteristics of transformer vibration signals in different working conditions are shown in time frequency representation.Finally,the correlation coefficient of each EWF and the original signal is calculated to extract components of high correlation.The eigenvectors of signals are built according to the energy of components above to quantize the features of transformer vibration signals.It is shown by experiment that this method has a good effect on feature extraction for vibration signals of power transformers,and the different transformer winding conditions can be recognized correctly through the extracted eigenvectors.关键词
变压器/振动信号/特征提取/经验小波变换/Hilbert谱/时频表示/特征矢量Key words
power transformer/vibration signal/feature extraction/empirical wavelet transform (EWT)/Hilbert spectrum/time-frequency representation/eigenvector引用本文复制引用
赵妙颖,许刚..基于经验小波变换的变压器振动信号特征提取[J].电力系统自动化,2017,41(20):63-69,91,8.基金项目
国家重点研发计划资助项目(2016YFB0901200) （2016YFB0901200）
中央高校基本科研业务费专项资金资助项目(2017XS013).This work is supported by National Key Research and Development Program of China (No.2016YFB0901200) and Fundamental Research Funds for the Central Universities (No.2017XS013). （2017XS013）
