Independent component analysis for enhanced feature extraction from NDE

被引：0

作者：

Shin, BH ^{[1
]}

Ramuhalli, P ^{[1
]}

Udpa, L ^{[1
]}

Udpa, S ^{[1
]}

机构：

[1] Michigan State Univ, Dept Elect & Comp Engn, E Lansing, MI 48823 USA

来源：

REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOLS 23A AND 23B | 2004年 / 23卷

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

A signal processing technique known as independent component analysis (ICA) is proposed for enhancing flaw information in eddy current testing. Although the observed signal itself includes relevant information about defects, it is often corrupted by noise and signals from external supports that makes the analysis challenging. ICA, along with an affine transformation as a preprocessing stage, is shown to extract the defect signal from a combination of defect, support and noise signals, while improving the SNR.

引用

页码：597 / 604

页数：8

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