石油化工高等学校学报2013，Vol.26Issue(3)：69-73,5.DOI:10.3969/j.issn.1006-396X.2013.03.016
基于K-均值聚类与小波分析的声发射信号去噪
Acoustic Emission Signal Denoising Based on K-Means Clustering and Wavelet Analysis
摘要
Abstract
For accurately identifying the mode of AE signal,the noise in the AE signal must be removed.The denoising results by conventional means of filtering are unsatisfactory,the denoising method by threshold on wavelet coefficients shows unique advantages.Aiming at threshold selection risky problem in the denoising method by threshold on wavelet coefficients,K-means clustering method was used to classify the high-frequency coefficients by wavelet decomposition,determining the removal threshold for the wavelet coefficients corresponds to the noise,then the wavelet coefficients were reconstructed to achieve the de-noising purpose.Hard-threshold method and soft-threshold method was applied on denoising method by threshold on wavelet coefficients for AE signal,threshold generated by K-means clustering approach and threshold generated by the improved Donoho method were respectively used as the threshold for the denoising method by threshold on wavelet coefficients,experimental results show that in the three indicators of signal to noise ratio,root mean square error and smoothness,the proposed method is superior to the improved Donoho method.关键词
声发射信号/K-均值聚类/改进Donoho方法/小波分析/阈值/去噪Key words
Acoustic emission signal/ K-means clustering/ Improved Donoho method/ Wavelet transform/ Threshold/ Denoising分类
能源科技引用本文复制引用
周俊,刘丽川,杨继平..基于K-均值聚类与小波分析的声发射信号去噪[J].石油化工高等学校学报,2013,26(3):69-73,5.基金项目
军队后勤科研项目(油20080208) （油20080208）
重庆市博士后科研项目特别资助(XM20120049). （XM20120049）
