管道裂纹漏磁检测信号WPES特征提取方法  

Extraction Method for Improved MFL Signal Wavelet Packet Energy Spectrum Feature

作　　者：宋志强[1] 张莹 张清民[3] 王仕军[4] 

机构地区：[1]后勤工程学院军事油料应用与管理工程系 [2]重庆海联职业技术学院民航运输系 [3]中国人民解放军72283部队 [4]中国人民解放军72353部队

出　　处：《天然气与石油》2015年第3期18-22,8,共5页Natural Gas and Oil

基　　金：重庆博士后基金资助(XM 2014099)

摘　　要：利用小波包能量谱(WPES)对漏磁检测信号进行特征提取是一种有效的信号处理方式,得到广泛应用。但对于管道裂纹缺陷漏磁检测信号而言,其在高频段的信号特征不明显,频谱变化非常分散,特征提取困难。改进后的小波包能量谱及Wigner-Ville变换算法即是以连续小波变换和离散小波变换为基本的数学工具,匹配Wigner-Ville变换的信号分析算法,在信号处理过程中,将要提取信号的特征值以能量谱的形式进行界定,将特征值的识别与提取转换为对相应信号特征能量识别与提取上,从而提高漏磁检测信号高频段信号特征准确性。Application of wavelet packet energy spectrum method in feature extraction of magnetic flux leakage(MFL) detection signals is an effective signal processing method used widely. However, sometimes MFL signal characteristics in high frequency section are not obvious, the frequency spectrum change is very fragmented, which results in difficult feature extraction. The improved algorithm integration of wavelet packet energy spectrum and Wigner-Ville transform is a signal analysis algorithm which takes continuous wavelet transform and discrete wavelet transform as basic mathematical tool for matching Wigner-Ville transform. In the process of signal processing, the characteristic values to be extracted is defined as the form of energy spectrum and identification and extraction of the characteristic values are converted to identification and extraction of corresponding signal characteristic energy so as to increase the accuracy of MFL signal characteristics in high frequency section.

关 键 词：管道裂纹缺陷 漏磁检测 特征提取 小波包能量谱 Wigner-Ville变换 

分 类 号：TE973.6[石油与天然气工程—石油机械设备]